Horner's scheme for sine Tailor's series computatioin stability

In summary, the standard Horner's scheme for the computation of Taylor's series for sine is unstable because of the alternating signs of the terms in the series. To make it stable, the scheme can be modified by multiplying each term with the sign of its previous term.
  • #1
Touchkin
6
0
Hi all! Please help me answer these questions:
1. Why is the standard Horner's scheme for the computation of Taylor's series for sine unstabil?
The standard scheme is sin(x) = x(1 + x^2(-1/3! + x^2(1/5! + x^2(-1/7! + ... x^2(-1/(2n-1)! + x^2/(2n+1)!)...)

2. How can we modify the scheme to make it stabil?

I think instability is somehow connected with the changing sign of the terms in the Taylor's series, but I am not sure how. If you have any ideas ar you know the answer it will be interesting to hear. :rolleyes:
 
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  • #2
The instability of the standard Horner's scheme for the computation of Taylor's series for sine is due to the fact that the terms in the series switch between positive and negative values. To make the scheme more stable, it can be modified by multiplying each term in the series with the sign of its previous term. This way, all terms in the series will have the same sign, which makes the scheme more stable.
 
  • #3


Hello! I can provide some insight on the stability of Horner's scheme for the computation of Taylor's series for sine. The instability in this scheme is caused by the alternating signs of the terms in the series. This can lead to a large accumulation of round-off errors, especially for larger values of x. This can result in inaccurate or even divergent results.

To modify the scheme and make it more stable, we can use an alternating series summation method. This involves rearranging the terms in the series so that the alternating signs are eliminated. This can be done by grouping the terms in pairs and using the identity sin(x) = sin(x/2)cos(x/2) to simplify the terms. This results in a new series that converges more quickly and reduces the accumulation of round-off errors.

Another approach is to use a more accurate representation of the sine function, such as a Chebyshev series or a Taylor's series with higher order terms. This can also help to reduce the effects of round-off errors and improve the stability of the computation.

In summary, the instability in Horner's scheme for the computation of Taylor's series for sine can be addressed by modifying the scheme itself or by using more accurate representations of the sine function. Hope this helps!
 

1. What is Horner's scheme for sine Tailor's series computation stability?

Horner's scheme is a method used to evaluate mathematical series, such as the Taylor series for sine, in a more stable and efficient manner. It involves rearranging the terms of the series in a way that reduces the error accumulation, resulting in a more accurate approximation.

2. How does Horner's scheme improve stability in sine Tailor's series computation?

Horner's scheme improves stability by reducing the number of floating-point operations needed to evaluate the series. This reduces the accumulation of rounding errors, which can greatly affect the accuracy of the final result.

3. Can Horner's scheme be applied to other mathematical series?

Yes, Horner's scheme can be applied to a wide range of mathematical series, including polynomial, exponential, and trigonometric series. It is a general method for improving stability in series computation.

4. Is Horner's scheme always more accurate than traditional methods of evaluating series?

Not necessarily. Horner's scheme may not always result in a more accurate approximation, but it is generally more stable and efficient than traditional methods. The accuracy also depends on the number of terms used in the series and the precision of the calculations.

5. Are there any disadvantages to using Horner's scheme for series computation?

One potential disadvantage of Horner's scheme is that it may not be as intuitive as traditional methods, and it may require some mathematical knowledge to understand and implement. Additionally, it may not always result in a significant improvement in stability or accuracy, depending on the series being evaluated.

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