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00:00 I think it's better that they're I didn't want to see.

00:42 Okay. On the screen. So I'm encouraged. Mm hmm.

00:57 recording is happening. Yes. So to public today on to the next

01:05 in the book at this uh Interpolation. Another way of saying it

01:16 do finding. Okay. The function inter plate or fit. It's a

01:30 fit to accept the data. That's today functions will be polynomial. But

01:41 that. Later on in later lectures talked about other ways of feeling um

01:49 accommodation to accept the data that you . So. Mm hmm.

02:03 So anyway, so this is what will be. It will be about

02:12 keeping data today and talk about the words of doing it. And first

02:19 bit yes, motivations. Who Well, polynomial are quite often used

02:27 terms of instant computer graphics. It's case where to discourage surfaces in a

02:35 sized neighborhood in terms of pulling over so that it doesn't mean that you

02:40 a single polynomial to describe it total but to take pieces of it.

02:46 you often use again following on else describe. Mm hmm. The surface

02:53 for other for rendering what other Um and that's simple for example of

03:04 you may want to fit some analytic to the collection of data. So

03:09 this case it's just somebody took measurements his caustic attitude temperatures and general development

03:16 four data points. And then let's it um sometimes that is convenient to

03:23 analytics description of what might happen. doesn't mean that the underlying physics is

03:32 represented. It just means that So it could be that you

03:36 you get this analytic function that estimate discuss it would be at some other

03:45 than the four temperature subtraction initiative. you may have done that in some

03:51 to some other courses, probably getting the point where the enough so never

03:58 is what its function obviously do. The simplest possible why I was almost

04:05 specifically straight down between the pair of . And if you want to have

04:10 costed it's for instance straight down five and 10. And then you

04:15 the straight time and seem to get eight degrees and rivalries whatever the rather

04:21 on the line at that point. a simple way. Maybe a good

04:26 way, but not necessarily the best . That's a lot. Or do

04:32 want to try to do something where So I have an analytic function that

04:38 all before measurement points. That in case may not be a sequence of

04:44 lines but you have something that also some curvature change and that's supposed to

04:51 collection of straight line segments. So comes into polynomial with straight line.

04:57 a simple polynomial of degree what? But then it can have other polynomial

05:07 . It's all four points for another case. It's not like to

05:11 a degree one because to be a one, that would mean that the

05:16 time will actually perfectly fit all four points which is not like that.

05:23 on. So another version is that a polynomial and as I mentioned you

05:31 you can do a collection of straight between this pair of points and that

05:37 them the principal collection of falling They won't talk about that today But

05:44 difficult on as spikes and there will in Chapter six we'll talk about saturday

05:50 of full installments instead of a Mhm Yeah. So you can also

06:00 but the functions pulling almost no means only set of analytic functions that is

06:06 for fitting to the contrary other functions actually I will say more frequently use

06:14 polynomial except in terms of computer garden possible. So so and the I'll

06:26 to that much at some future class on the issues so these functions that

06:34 used to um trying to model data some other function but generally on a

06:42 basis functions and the trajectory is too basis functions that captures a lot of

06:56 properties of the data that they So that means you can use found

07:03 in a few of these basic functions that's kind of was the basis for

07:12 it for compression. So in that the older the institutes cause I understand

07:19 and the impact standards and the point for a lot of different. I

07:25 make this mostly in that case it take that many. So the call

07:30 platforms to capture the essence of the . So that's the largest. And

07:36 the only thing you need to communicate the coefficients um for the basis

07:43 So the senator and the receiver agree what the basis function is. So

07:47 you get the coefficients, you can the data based on just the

07:53 we'll talk much more about that So just to point out that today

07:57 will be enormous. That's by no the only functions we used to produce

08:07 and the other thing one needs to if one wants to exactly ah at

08:15 match. So the data points that may have or for that matter is

08:20 try to make the simple representation of complex function if you want to have

08:25 . Exactly. That's the favor on . And the point is if this

08:31 like and this suggests the case is measurement data measurements are really perfect for

08:38 areas. So you may not necessarily to perfectly that's the point. Have

08:44 measure of goodness of fit instead of and that's uh what comes up in

08:50 guest tonight. So all this. I think I'm pretty much said what

08:59 on the next few slides in this uh documentation. But this is that

09:04 can get up to design. you the perfect exactly or not or if

09:12 want an approximate trip and then it's notion of quite simple Sylvia is again

09:19 make something that captures the essence of data were function and that this simple

09:29 whichever means you find simple belief for particular application targeting. So So what

09:41 said one, can you polynomial polynomial not necessarily what it says in this

09:48 should be an example of an exercise suffering is simple to write down simple

09:54 evaluate but they are not necessarily the for you approximating the second. As

10:01 said in the next slide, I'm to sure what may happen. So

10:07 is kind of a very simple Kind of a nice bell curve if

10:13 like. And what this slow tends show is what happens to think that

10:22 higher degree polynomial you have the better of the data. So and this

10:30 just trying to show that that's not the case. So this black dots

10:37 equally spaced points In the interval between and one. And this application here's

10:43 function and the just kind of follow dots and that shows what the function

10:50 actually are. And then it's uh uh attend to gratefully. Normally the

10:59 that you don't use all the black . You just use a subset of

11:02 . Then the black dots are basically the case to use 40 of them

11:08 . Yeah, hopefully very good approximation now you're trying to make sure that

11:13 polynomial matches all Than 40 black dots that case. But if you do

11:20 to get the polynomial. So when look at the polynomial values between the

11:26 where you make the fitting as you see in these areas, they're highly

11:33 there is nowhere close to what the function that saw if you move away

11:37 the interpolation points. So that's one the drawbacks that high degree polynomial.

11:45 have a very prospect or behavior and why the reason why you may not

11:51 calling on me having him money. wants some other function. The betting

11:55 pass to the essence of this So this was kind of the preamble

12:03 the getting into. Yeah. The of using pulling normal approximations. Any

12:10 or comments on the behavior of So this is amusing polynomial for that

12:22 not be as effective for functions that passed. Right. Right. because

12:29 if they're higher than zero or then must either approach me in a deeper

12:34 more and right. And it's also that we'll talk about in a future

12:43 . So it turns out a little of this social cultural behavior is also

12:46 by the notion that is straightforward Take your interpolation points as equally spaced

12:56 in the interval. So if you it on and choose different ah distances

13:04 the population points, you can keep same number. But they move them

13:08 the village. And then you can find out that yes you do.

13:12 you can avoid some of the So it's just a yeah melanomas are

13:21 many ways great. But it tends be best when you have a limited

13:26 of points. So yes, you see the blue ghost that swings off

13:32 it never behaves as badly as the . So it tends to be that

13:38 of having a high degree polynomial it's sometimes better to use the daughter

13:46 build degree polynomial to approximate the And that's spine centers. Think I'm

13:52 popular and we'll talk about spines in later venture. So that's instead of

13:57 a high, high degree polynomial to many points to use the collection all

14:05 . And then we'll come back to initial collection. The first thing then

14:12 just to go through the exercise and , oh what? Okay. Now

14:16 going to look at the mechanics of polynomial approximations. And this mechanics will

14:24 used for the gun When we talk spines. It's just the difference is

14:27 spine, once they have a law from enormous. But the mechanics

14:32 That's right. So, um I guess that's mostly introducing vocabulary points

14:45 nodes. The points in this case this collection of terrorized values that you

14:52 in your little table and have an variable presumably to the X. And

14:57 dependent points up for every X. , I have a corresponding. So

15:03 paradigm is known as the points um you want to find a polynomial that

15:10 exactly for today's manager. Now the files themselves, it's known as

15:21 So many times you can have, know, not just single division,

15:26 have a surface, you can have Z coordinates every next time. So

15:33 are there's three the coordinate values for you want to do an approximation of

15:40 function value in this case. It's to have distinction. Clear points and

15:52 And that's the one. So now is the trivial and talking ridiculous.

15:59 , it's doing the interpolation of the for instance, that's the concept.

16:03 no wonder what you can do. that's the degree of this polynomial of

16:08 zero. And of course then the thing that is also simple. You

16:12 two points and you can do a line between two points Polynomial of degree

16:23 . So and of this land investment reopened it in two different ways.

16:31 1 1 is this form of an . So you can see here by

16:37 minute X and the variable it's free access to X. one. Then

16:45 thing turns into zero and X one X zero. So this parenthesis becomes

16:50 one. So that's one This on normal evaluates the white one and you

16:56 plug in zero. Then this term and this becomes the one and then

17:01 value is Or the point of almost . So it clearly perfectly represents the

17:09 points that we're giving. Excellent 41 . 01 Singapore. Another way of

17:16 the same thing is just can't be it. Perhaps more common to look

17:21 this. The equation for the line in this case X660 then disappear.

17:30 we get the same thing again there on the polynomial zero is 0.

17:36 if you put in X one then this one, chancellor and you've got

17:41 two things so that what's left is . So it's just two different ways

17:45 writing the same polynomial in the sense pleased to ways of writing the polynomial

17:55 in the same value for any given . So in that sense they were

18:01 same even though they're written in two ways and that's what an important.

18:07 talk about that a little bit more . So that's um uh the other

18:16 yes. Yes. Perhaps reflect about that we have one point. The

18:24 has degree zero. Now we have points and the polynomial is everyone.

18:32 the whole the role is that if have endpoints, the degree of the

18:40 that to use green for its opponents of order N -1 or no

18:47 It can be a higher degree but we can put the higher order polynomial

18:53 goes around that you don't have enough to make what you need. So

18:58 only way you can get a unique is selected degrees at most one lower

19:05 the number of points. It may lower if all the points fall on

19:10 street. So um Yeah. And see it's all. So this is

19:20 at that. Right? So now a couple of names here. So

19:25 way of writing the polynomial is known the formulation and this way of writing

19:31 political is known as a good Yes, we'll talk about the constructive

19:39 in the event and questions on So I think an example concrete next

19:51 to do this thing. So it a few points straight time and um

19:55 what was photographed from the previous One thing uh huh was the notion

20:06 this brilliant. So it looks like would think perhaps that would write things

20:15 left to right and increasing X But in this case, you

20:19 this was used as the first 2nd point and it's in the lower

20:26 value. So that's what you find this thing do that. That's the

20:31 as for the two data points from previous draft. So it's one point

20:36 come back to later. Is that interpolations. The results should be independent

20:42 which order they happen to write in faith. So that's an important aspect

20:48 the approximations. So, um um this is just working it down in

20:56 of the the ground formulation has the point, That was x 1.4 minus

21:04 distance to the other point. So have this question like it's so in

21:11 denominator is the difference between The interpolation in this case that still wouldn't explain

21:18 next zero so that we will see both of them, but they're ordered

21:23 defense of they've got for the first point X ah was the next one

21:37 very welcome. 25 and then we the X value and the function

21:43 It's zero Mostel 3.7 that comes from . And the other one is the

21:49 point to three point. So it's pretty straightforward just plugging in X zero

21:55 X one and the correspondent by values this regard for relations or you can

22:04 in the needs of what and and of which way you write it,

22:09 can simplify it. Uh this for the expressions. So um any questions

22:21 that. Yeah. So now a bit more kind of formal and generally

22:35 the first simple taste with us two but in general dig out some polynomial

22:46 that looks like this in terms of growing formulation, in terms of

22:50 it kind of ends up generalizing in what we are going to use both

22:57 them future and past for other chapters the book but to this significant differences

23:06 I want to point out so and like our formulation, one of its

23:15 features is that they um the grinch multipliers or expressions the health. They

23:31 totally independent of the function doctors. you can construct this and this totally

23:39 of what the interpretation points are. they only need to know the

23:47 They need to all the nodes So you don't need anything about my

23:54 function. But in order to be to construct that's not true in the

24:01 formulations, Newton's formulation will actually have obviously part of the city of the

24:10 and the suppression of. So you also see it in this little two

24:16 version here that you have a function is so this is kind of a

24:21 and this is a one. So can see that coefficients in this whole

24:26 expression. Then in fact it becomes on the function. So in that

24:32 you can have two. The construction's the polynomial without knowing function values.

24:38 this case you can construct the polynomial you need the function. That is

24:42 they want it. Okay. Not . This is right. So this

24:52 what I said already. Mhm. So now I guess it was the

24:59 we're talking about that obviously the ground works and this was just well these

25:09 and almost Sorry? No, I ah these are what these panels are

25:17 and they are constructed in such a that one there at the corner of

25:25 for the same. No, to the index of the polynomial, then

25:32 one and all the other notes it's and maybe let's let's go back.

25:43 . It's always said So again this kind of zero and then you can

25:51 that it's a plug in ah Say one and the first one that becomes

25:58 And the X. one and the one that becomes about. So if

26:03 want to evaluate this next one and got to talk to me. So

26:09 just going to see that depending on term you have in this corner of

26:18 Is either zero or 1. The interpolation points. So they've got for

26:28 words is sincere. So when you 100 this expression and one of the

26:38 points, the access for which quantifying . It's only one. It is

26:49 . but it is at the east whole point and then the function then

26:55 the value is one. And so the plus P of X. I

27:00 too um the function value or the values, we wanted to interpolate exactly

27:08 that. And if you then plug a different thanks value Then this is

27:14 . So basically, yes. Um term in the summation is only equal

27:22 the function bezel. Um at the you are safe in simple.

27:34 Okay so yeah it's on this machine plug in any pleasure for ex um

27:47 is fine. It's all about an ah for the east polynomial most firstly

27:56 -1 terms because to take the distance the I don't know to respect each

28:06 or the other ones but not to because that will be division zero and

28:12 them from the nominator you have X the distance from X to the respective

28:20 contextual 13 discipline. So it's easy see regarding what thanks noble values.

28:30 plug in. The only point where again it's it's not equal to

28:37 I. Then. And one of Factors in the expression is going to

28:44 zero. So pickaxe through our X and visible on the screen and this

28:52 be zeros of the whole product. it's true for any one of their

28:57 except thanks bye. Because except hiring not present in any one of the

29:06 . So that's about it. Except then all the factors a lot.

29:14 that's the worry one. And it a disease that this is oh and

29:19 of the cardinal doctors is only one one of the nodal points and

29:28 Okay so mhm. So there's some what I said and then I have

29:34 complete example of this a little bit it looks like the different forms of

29:41 . So zero make it completely depends the next slide. So and the

29:53 you have a different factors and we're down all this way. Her

30:02 That was the first one was like was my smart. I think so

30:09 was. And the -5. So mm hmm. Ex miners and Sarah

30:22 mm hmm. Right. Right. I looked at the slides before the

30:30 but hopefully mm hmm. The restaurant . No. Anyway, I'm sorry

30:45 got confused now no one can help . This is supposed to be ah

30:56 somewhere now for risers for the four points to expect the ones we are

31:05 looking at. And then what's already confused at this point. Yeah,

31:16 right. Okay. You're buying Right. Right. You can start

31:22 the back. So this is the one. The next one is one

31:25 then six points. That's my next . And so they exclude the first

31:31 . So that's why it's for Zero. We excluded zero points.

31:36 they start with the first one. . So that's what it is similar

31:40 is to go to um the ones enterprising there um Second Novel Point Sort

31:48 X. one. We have it's here which is finest X. Zero

31:53 X. 01 minus one plus Go on with this. Just

32:00 There you go. A little point which the paranormal is supposed to be

32:05 question. Yeah. So so anyway another thing to look at and that

32:15 come back to the center point is this case the corner polynomial. Czar

32:22 um particularly to him. But you see some of them are kind of

32:30 So they became other ones that are hostile territory but they're always down there

32:35 plus and minus one and we can that that's the case it seems.

32:43 they have bounded isolation even though between . So that's one other good

32:52 The cardinal points. So how many ? So it's fairly straightforward how to

33:01 them. The good point again is the only depends on the nodal

33:09 It does not but then on the violence just gives you a way of

33:15 together in some sense the functional value pondering at some point between okay points

33:25 approximation. No no no. Okay in America example now three points.

33:35 see if we can write the So Again start with zero. So

33:42 just um The distance to the X and X two. So X one

33:50 minus a quarter Or -11 is the and X two is the one.

33:57 it's and then in the denominator you that's zero. Um Two. It's

34:05 song and it's zero and it's one next zero. And it's two from

34:09 against you. The government expression a cardinal polynomial that is designed to

34:20 And the function value at zero And the next time not paranormal is to

34:26 the function at X one. So under this will have x minus X

34:32 and x minus X two. And the correspondent thinks the denominator and the

34:39 between that. Thanks for X one should say in X zero and X

34:48 and X two. We got a one and similar To the other

34:54 So now you can write it So these are the three corner

35:00 Is this for capture the function value functions in the function value attacks

35:06 And they have these expressions and now can write down the whole pulling normal

35:15 . So four the function value Um that's gonna record another polynomial for

35:26 zero X one X two. And It's obvious so that this kind of

35:32 a look at the functional value was . And function earlier is too so

35:37 what it takes -36 and constant transfer value seven. I think that the

35:46 ones and it's just trying to straightforward too. Yes or no, probably

35:53 . Well That exactly matches the function of these three. I gotta go

36:00 . Okay. Mm hmm. So now the next thing I want

36:08 talk about community formulation. I want right. So one. Oh yes

36:19 the book, come on makes It's kind of incremental. So it's

36:26 like started the lecture things Just one . But it's a concept and then

36:32 points and the strength time and three will probably get a second order polynomial

36:39 it happens to be kind of So this is basically the kind of

36:45 the curse is broken and that the of the polynomial. So at some

36:50 you have a calling on your friend and then you have one more.

36:54 for this expression suppose you have a organization just it's the perfect fit thing

37:01 k points. Take plus one points and you add one more point and

37:08 you can that's the right thing done you have the following normal you have

37:17 it and then you add the new , that is basically taking the new

37:24 whole point. But if it's k one and its distance to all the

37:30 total points. And if you plug the value now on the polynomial at

37:40 no notable point, then it should the new in population at that

37:46 That is okay. Plus one. because so this polynomial yes, basically

38:03 preserves the property of perfectly matching all previous points that you have. Because

38:13 if you replace in this equation Xscape was one where any one of

38:20 previous no level points. one of terms in this one of these factors

38:28 this term is going to be So for any one of the bridges

38:32 points. Ah this extra term is to be zero. So basically says

38:39 interpolation property. Always construction work that done before adding this new point is

38:46 . And if you don't make this stick then obviously your computer. See

38:52 this is the question is true Then does seem to police 20.6 outfits.

39:01 I think that's what I guess just to say. I'm just that

39:07 So our business is business fallen on for the party. A simple example

39:17 how to do this now. five points. So they can do

39:25 and they didn't success the white soul this incremental or inductive way that's We

39:31 from one point. So the polynomial is a constant Then it's best to

39:39 because They wanted for X0 To be . It's actually for any extra minus

39:46 . And that's certainly true for the points That stuck with me now.

39:52 that was produced and now we want include one more point. So then

39:59 form is it has the previous polynomial some suitable constant. Times the distance

40:05 the new point through the previous interpolation this case. Now we know what

40:13 is. That's mine, it's And now we have the condition to

40:17 also the new points. So somehow one x equals one Day one at

40:26 was one is supposed to be my tsunami thing was plugged in and this

40:31 so I've got to write it in opposite order was minus five plus

40:36 Times X equals one. Then the should be three. So how do

40:41 have an equation? It's just is the computer see then we now have

40:48 pulling over the congress to park and we just keep repeating that I

40:57 So it can start from to you . That was the thing we have

41:01 we want to The next point x two. So now we have the

41:05 polynomial. Now there are the term then this one and then in terms

41:10 the factor is the product of the between them. And then um Kalla

41:17 or the X values too. Each of the previous interpolation. That was

41:22 the factor because this guarantees that this disappears for any one of the previously

41:29 points. So in this case for see what plus You're plugging in at

41:37 . And it's one and the expression zero or zero. So that just

41:41 the X. And the next time the X. One this one.

41:47 now we have also the condition and new polynomial P two should have the

41:53 minus 15 if they can gain XP minus one. So now we have

41:59 conditions are not known to see from . Yes. And so we can

42:03 it in and it should be solution minus force. And now you have

42:08 Newport. We also know that in the degree increases by one each

42:16 But now we have three points of ingredients two years before the at

42:23 Then the number of points for And that means you keep the

42:30 All right. And I don't do the steps but testimony is all said

42:35 done and I have five points the order polynomial. And that means you're

42:41 . And it turns out to be will be specific to the fourth.

42:50 so but this is one way right the hole. No money. You

42:57 write it in this kind of honor nested formal talked about turning up uh

43:03 then just evaluated. That's one way you can also Right then. And

43:11 other negative forms of the form is necessarily but it's the same principle.

43:18 the same polynomial. Then call this . You picked value of this polynomial

43:26 in this way or this way or way is all the same. It's

43:31 different way of writing it. But principle it's the same for you know

43:38 it may not be obvious but they where to take this expression for instance

43:45 unravel. All the multiplication is hidden the parenthesis and collect the terms of

43:53 powers of X. You got an that looks like this. So this

43:58 kind of perhaps symbols. Common way writing the polynomial, different powers of

44:05 with the different topical efficient for And if you have it in this

44:10 can sort of fairly easy to see this this expression is a nested version

44:16 this 3X. That comes from the order and then you have the

44:22 So that means this expression is multiplied X. So the third to get

44:26 right answer. Yeah, they are . And then The -70 seconds or

44:32 , you know, I didn't tell in terms of so just again,

44:38 ways of right things all along. is values for exactly the same.

44:50 hmm. No. Now the next of clients are totals in some different

44:58 . Okay. But I think the is actually following this Warner's idea and

45:04 more complicated his shoes and have to they get the coefficients of the book

45:14 the standard procedure to and remember from newton formulations, the coefficients are dependent

45:20 the function the construction that was So, um, also, so

45:36 was just the general form. It a previous slide and one can essentially

45:44 do it step by step. So can start during the evaluation that was

45:56 some of the previous slides and get one of the conditions and use it

46:02 get more and more of the conditions or evaluated in the nested form once

46:08 have the coefficients best unravel it from innermost expression in his domestic point that's

46:19 we did early on in her previous . Um one thing that they will

46:25 back to ah towards the end of class today if I get there are

46:30 ones next time is if you look now this expression that is basically multiplying

46:39 coefficients. Um so this is the of does not have the function values

46:47 it. Um They they have behaved differently compared to the cardinal pulling owners

46:55 the laboratory expression. So as I commented by one of you more

47:03 Right so the higher order polynomial you see that it's got to be

47:07 Ah that's so nicely. Okay substitution up the lower order ones are I

47:14 behave but the highest degree then they become difficult to be able to potentially

47:20 America what? So this is just simple routine as domestic evaluation center.

47:32 . To the same in terms of homeowner So now the thing that has

47:39 principal also fairly simple just following the that they actually live in the examples

47:47 at one Point. Ah that is because of the the constant districts afterwards

47:55 there function value you want to approximately first point and once you have that

48:01 can move on as they did they one more point. Now you know

48:04 one and then you can evaluate the from the next equation and jim

48:12 So um brother mhm. To you kind of have wherever you are

48:21 so this is something that you have previous conditions and figure out this

48:27 take the new functions. Uh There's difference basically everything except the new coefficients

48:36 you're trying to value. So this is done and moving to the left

48:39 side and then divide by this thing and then finds out the partition.

48:46 that's kind of one way of doing . And there is another way that

48:53 described in the book, has certain that will use later on. So

49:00 something um Yes, yes, I so. It's mhm Yes um known

49:13 divided difference and that's the and describing idea of the differences. Obviously this

49:25 that these coefficients and they don't polynomial kind of food as a function of

49:37 the previous or previous including the current point. In fact both the local

49:46 the X values but also the function is remember this is supposed to

49:51 So this just stresses the facts and and the general notation instead of having

49:58 proficiently doesn't display just simple that doesn't the dependence on nodes and function values

50:09 that use this kind of notation instead shows how these professions is actually dependent

50:17 um all the interpolation points that you been working on until that point.

50:22 that's what I'm going to be seeing some of the coming slides. Um

50:29 . In terms of the simple it's A K. But it's also

50:34 dependencies in a different way. Alright, bye. Okay.

50:43 Okay. And this notion of dividing on the bottom side until they come

50:52 . But I think first of what call the direct evaluation, which was

50:57 what was used in the previous So now take the successive points and

51:04 before day zero was 3. The equations 13 and takes a constant

51:11 Next turn ah uh expand. So difference between these two which is a

51:20 of five. So that's what for proper science. So just keep going

51:24 you get a one a zero a a two. And now in this

51:28 of organization that meets That one is and one Class. Now with two

51:34 1 and four. And the coefficient a two was a one was punished

51:43 . And then we have the state symbol to get a three and a

51:47 or a two, sorry, and was etcetera. So it's just linking

51:53 notations. Very complete example. But same procedure as before. Ah

52:05 Okay. Well, yes. So think the only point of this particular

52:11 . Yes, essentially. Um looking the product in disease and in this

52:21 it may be the case of the index is lower than lower index of

52:27 . Starch. The world starts on standard assumption that the survivor, I

52:34 basically what? So it doesn't divide into service. And that was the

52:41 of do we agree that it's this the product of and one is one

52:48 so against agreed again increases by one every no point. So I'm going

53:00 let's see what's going on with this . Okay, so now the soviet

53:06 of divided differences. So here's something a one uh first of 080.

53:19 the next term is to compute a Therefore X 1 0. And

53:27 but it is getting these two nodal . Yeah. And a zero was

53:33 fact that felt like sarah. so in this sense, what part

53:39 beginning this notion of providing difference as is basically expressing the slope of the

53:47 between 2.60. They forget zero on . And but so for me

53:58 it's kind of nice late there aren't want to talk about association.

54:07 I can think of this again. just, it's the second they can

54:12 to me about it and they will be used for food finding or otherwise

54:16 approximation of the derivative as a So that's kind of the difference gives

54:25 something of emotional stop. Mhm mm , okay, that's what's that.

54:34 then it's been out and go back say, oh come forward. And

54:39 think the next to his expression then can rewrite it. So manipulate this

54:48 and that's what they have. This The best for the slope of the

54:54 between these two points 10 0 and their corresponding function values. And this

55:01 now the slope which means ah X and X two solvents. Thanks for

55:08 space stone, first between the First points and then take steps on between

55:13 2nd 2 points. And then So that's the difference between the two

55:19 down slopes And then divided by the now between the two endpoints. So

55:29 it's that's why this notion again divided you take in this case difference between

55:36 slopes between the neighboring segments if you if you were to have straight line

55:42 and then take kind of the average these. So this is also why

55:52 about America differentiation and approximation of This is kind of the way also

55:57 time construct an approximation of the second derivative of the curvature. So that

56:05 like to me it helps a little have intuition of looking at interpreting what

56:13 kind of this question tried to model capture. So, so this is

56:26 I guess I didn't manipulate this expression everyone wants to follow what I

56:30 I have to come from one to thank you. So this is something

56:37 they have now trying to do this I guess is what's going to happen

56:44 . So I started lately that was using this petition together square brackets is

56:51 and points On interpolation. So that just one and the next one is

56:58 jam packed two points of one under and that was going to stay forward

57:04 didn't have before and we get a that's the famous. Mm hmm.

57:11 then the next one here I guess just keep doing it the same thing

57:16 the expression that was derived in terms the divided difference notion and yes,

57:26 eventually To this now 8-7 and mhm , hopefully. So when we did

57:39 more direct version and not trying to it uses divided different notion of deriving

57:47 . Um as you can see when get the same results, it's a

57:50 way of getting to it that disposes a little bit more of properties of

57:58 points are related to the subject because notion of first and secondary looking for

58:04 trying to tell the truth curvature and this blindly thinking about the point should

58:11 corrected. Mhm I don't see what is more no. Mm hmm.

58:28 . Um that perhaps shows a little again the defendants and the expressions of

58:36 is Yeah and right, zero Day which is like a two with the

58:45 for the truck. Um so let's . So this is. Yeah.

59:00 so if one does start this expression ah Finding the coefficients from 1 to

59:12 other. Ah yeah. In fact is. And to show that it

59:20 on this particular form. So a bit talk about of the figure a

59:33 . This is certainly in that case was just looking at the slopes between

59:37 adjacent segments and then taking Kind of average between the endpoints zero and 2

59:45 that face. So the broadcast the of these functions, You can see

59:54 differences here that shifted by one. They started and they started zero.

60:02 it's kind of intuitively communities But taking two segments but now they're over that

60:08 but they're shifted by one and then kind of the average by the lion

60:14 the total distance covered by all the that's the way you get. Can

60:23 coefficients? So, so if you one of the proficiency investments, take

60:30 difference between these two proficient and divide transformer. Mm hmm. What?

60:47 . and uh I guess one this one and that kind is used in

60:54 of it. So I said, is that? And made the comment

61:01 on today. And there was that very first example of X0 and two

61:05 in a straight line between and I but this and do it In increasing

61:15 of importance. six zeros. That there was 1.25 and 1.4 and then

61:21 x four tasted before the X mm One that was 1/25 cents X zero

61:29 zero. And the lower right hand X. One Y. One Closer

61:34 the X. equals to zero. the straight line between the two doesn't

61:39 on which order it happened. So is just trying to explore that which

61:46 you happen to label the points. should get the same and that's what

61:52 invariants trying to say the the procedure all of these things. That's the

61:58 thing. Regardless of they have put labor reform and what's so I'm not

62:12 . So what's the difference formula and example here. And then I think

62:18 have it actually kind of a real of how to do these things.

62:24 we need to do this divided different . Weren't convinced to happen. Find

62:29 simple steamer and like the council and of these point is historic kind of

62:41 four. And such other points. then you have the corresponding function

62:48 So in this case yeah you can with them all the interpolation In this

62:56 like 0 - 60 in the correspondent values. And then you take this

63:01 differences. So now you take them wise and bear wise and then they

63:05 to the next column that's opening up difference between events and divided by the

63:12 range of all the time. So just what I'm going to do.

63:19 , So basically we got 30 this . You use these two points.

63:24 get the next one here. You're to use these two points. That's

63:29 . And then you keep going the of this to have at least divided

63:34 and invested the slope between reversal The next one we want to try

63:39 get one more to get captured curvature then the best can take Again,

63:46 adjacent shifted by one and the They won't have the distance between the

63:53 points. And then again in the months from now the best they have

64:00 the coefficients in the polynomial company. than this for the simple steel.

64:11 , so that's what sin. Ah , no. I think that being

64:21 concrete example. Next let's stop and if there's questions. So, so

64:34 see first. Not using expressive. , let's see what I am.

64:47 we have the difference right between um hmm. Function value as on the

64:56 points. It was zero and So this is uh, function function

65:04 . And the distance between them was . Um Sorry, it's um

65:15 and nine. So I'm just gonna retracted it and then you take success

65:20 neighboring points and the distance between It was zero and three halves.

65:26 this one and then another 10. then you move on to trying to

65:34 the bracketed ones the next. So basically the difference between these two

65:40 comfortably used um to this one and one and the extreme points industrious.

65:48 you don't have to And similar for next one is between expanding nicely.

65:57 you guys can keep doing nothing for head on ingredients side. Yeah.

66:05 now let's they want one has the is actually going to use and the

66:14 for the hard work. I thought would have been the next slide.

66:18 this is just taking what the yeah that these were here. The function

66:25 is on the table and this is using the schema, I don't know

66:33 on the previous slide and these are this chapter once and then you can

66:40 down so this is a gun. coefficients for this is the constant.

66:45 is a proficient for the first longer . That was Yes, it's Sarah

66:50 that's one and that is the next order ah coefficient in the new Kampala

66:58 . All shows up on the diagonal . So, but in order to

67:03 the diagonal the investor needs to and back and have the kind of triangular

67:10 and figure out what's included in order get those points. So what kind

67:16 property from the left in this then I had it. So then

67:22 have it and then you can write , they got an expression for the

67:29 , but it's just sort of divided . If one has this kind of

67:34 sets up its service simple and straightforward figure out. You gotta take the

67:41 between the function values and the distance and all points for those function values

67:49 uh yeah uh to progress basically between points, the first one is the

67:56 value itself, The next one that on the difference between these coordinates and

68:02 fairways. And then they get to one mr defected from the students and

68:08 for the distance from the holding. , by construction. So the order

68:16 which you happen to write down is don't have to order them in terms

68:20 you know Professor the increasing or decreasing family, they can write them down

68:26 several water and it still comes Okay, so um now this is

68:41 the sooner called it down there and it. So so this was,

68:49 the doctor has a pseudo code to the coefficients based on adoption values.

68:54 And then earlier we talked about the of using this next the corner first

69:02 have to complete proficiency and then they for whatever experiment they want, right

69:10 . And this has pretty much been I've said three things. Oh,

69:19 let's see um yeah, I'm gonna kind of an example here. Any

69:28 so far on this. Sure, little bit more complicated. Again,

69:33 cost function. Um the construction involving the trunk and now it's an example

69:46 computing an approximation of the same function a polynomial. And then this gets

69:54 . Let's and so the idea is you for this example that you introduced

70:02 number of points um or I understand Points between zero and 1.6875 that they

70:16 to have the exact representation. And we kind of tried this. That's

70:21 good is it by looking at what's difference between the same function the polynomial

70:29 other points than the interpolation points. I picked a few points between the

70:34 points and have a look at what pulling over value and what is the

70:38 value that gives you something? They estimating the error in the approximation for

70:44 points of the population. So remember supposed of the bell curve in the

70:52 of the lecture And and the purple isolated the lots in that case the

70:57 between the polynomial and actually function value some places were quite dark. So

71:05 is kind of a standard checked when tried to figure out the paranormal.

71:08 this was something that says that this looks at it from this place for

71:14 example that we're I guess the point between each barrel insulation points of

71:21 the four times as many the violation as interpolation points, it turns out

71:29 not every loss one of these That was not too bad. Just

71:36 single position influence in terms of divided the test points. If you like

71:48 three points in between the interpolation it doesn't mean that any one of

71:53 three points was actually one of the for if you have taken 100

71:59 they would have not gotten a larger different sampling in this case someone needs

72:08 , mm hmm. Okay. My is never get a chance to talk

72:15 that. So this is the saying the thing I'm trying to say and

72:19 is over. Is that the different way you're right velma in a sense

72:26 mean it's a different falling over in sense that regardless of what was written

72:32 , if the value is to the value requirement. But any X values

72:38 about this. The forum looks But argument seems to a polynomial to

72:45 the same boring America approximations and around . If you have infinite position you

72:56 get this thing and this is what says. And it's just a simple

73:01 . The argument is supposed they were different for the same interpolation points.

73:06 will be their friends and okay, they may actually difference. But it

73:13 if you look at taking the difference these two points, it's the agreed

73:20 difference is also having The same degree either one of the two. But

73:26 also means that this polynomial, The polynomial is zero, it's all the

73:34 . And since any paranormal cannot have roads are busier and more points ah

73:46 the I guess one degree less of paranormal degrees. So that means effectively

73:51 forces the coefficients in the polynomial is in the proper way and to be

73:56 same. So because of the number routes, because the difference polynomial is

74:01 . As all the speculation points, forces us to the pediatricians in the

74:09 up a lot of sense. And I guess, I don't know,

74:17 just have this as into two the lecture. So I just said in

74:26 beginning of all enormous are by no the only functions one use. So

74:31 general what problems to do is to some combination of some as mentioned basis

74:40 . Just fired on the stones. there's some linear combinations of things 19

74:47 maybe approximate or it perfectly represents a of points like we did today.

74:56 was trying to have the funding over equally. They function by the closing

75:03 points. Um but one and potentially to pick any other type of function

75:16 gave the example of the compression. You're better anyone else or if zero

75:26 pretty much almost identical to the function . Um That for the rest of

75:32 thing as a restaurant and you get basis function. So if you have

75:39 example where they sine function. So if your function F is in

75:48 trigger event of functions sine and cosine your basis function happens to be signed

75:53 call sign, They only need one function and the coefficient just needs to

76:00 the magnitude and face right except on head. And then they have

76:06 It takes quite a few terms to the variable approximation of the project and

76:13 can get it. Take a serious gives you an idea of what the

76:17 you need and the polynomial. But the places function wouldn't is that it

76:22 a trick function and a couple which just been treatments. So so normally

76:31 ends up doing it. The general we have a bunch of coefficients then

76:41 to the value of the basis activities, population points ends up being

76:46 matrix arrived in the question for each of the double points um correspondent function

76:53 unpardonable points. So then to find professions, you have to solve the

76:58 of equations and I will talk more that lady And here's a little bit

77:09 in principle I can think of the as the basis functions being what's known

77:15 the more no meals. That is various parts of that. Mhm So

77:21 have first the constant and x itself X square. So these are the

77:27 basis functions Uh That was effectively used I was just calling over approximation.

77:36 here we can see the behavior of . Well, normal is only into

77:40 became 11 very nicely and some not much and couple more minutes. So

77:50 in this case if one looks at Manami als um So here's the questions

77:56 Uh constant, the first degree 2nd so on. And for the different

78:02 points and the correspondent, its values you get the matrix of this type

78:07 is known as the Mhm. Then mold matrix. And it turns out

78:11 that's not something you really want to with. Unfortunately the constant tends to

78:16 that this matrix is very conditioned sort things. Getting numerical accuracy in doing

78:21 this way. It's not so And we'll come back to that in

78:27 future lecture. So there's something for . And so here we saw the

78:33 Poland almost. That is also true but it's about the oscillation and that's

78:40 true for the newton. And then all males in the interval is starting

78:44 headbutt. Not so good. Next we talk about other basis functions and

78:52 want to get a drink functions. that's when you're on the other polynomial

78:59 nice behavior. seven. That's two great questions. Okay, thank

79:19 so much. Thank

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