Clenshaw algorithm

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In numerical analysis, the Clenshaw algorithm[1] is a recursive method to evaluate a linear combination of Chebyshev polynomials. It is a generalization of Horner's method for evaluating a linear combination of monomials.

It generalizes to more than just Chebyshev polynomials; it applies to any class of functions that can be defined by a three-term recurrence relation.[2]

Clenshaw algorithm[edit]

Suppose that \phi_k,\; k=0, 1, \ldots is a sequence of functions that satisfy the linear recurrence relation

\phi_{k+1}(x) = \alpha_k(x)\,\phi_k(x) + \beta_k(x)\,\phi_{k-1}(x),

where the coefficients \alpha_k and \beta_k are known in advance. Note that in the most common applications, \alpha(x) does not depend on k, and \beta is a constant that depends on neither x nor k.

Our goal is to evaluate a weighted sum of these functions

S(x) = \sum_{k=0}^n a_k \phi_k(x)

Given the coefficients a_0, \ldots, a_n, compute the values b_k(x) by the "reverse" recurrence formula:

  b_{n+1}(x) = b_{n+2}(x) = 0,

  b_{k}(x) = a_k + \alpha_k(x)\,b_{k+1}(x) + \beta_{k+1}(x)\,b_{k+2}(x).

The linear combination of the \phi_k satisfies:

S(x) = \phi_0(x)a_0 + \phi_1(x)b_1(x) + \beta_1(x)\phi_0(x)b_2(x).

See Fox and Parker[3] for more information and stability analyses.

Horner as a special case of Clenshaw[edit]

A particularly simple case occurs when evaluating a polynomial of the form

S(x) = \sum_{k=0}^n a_k x^k.

The functions are simply

  \phi_0(x) = 1,

  \phi_k(x) = x^k = x\phi_{k-1}(x)

and are produced by the recurrence coefficients \alpha(x) = x and \beta = 0.

In this case, the recurrence formula to compute the sum is

b_k(x) = a_k + x b_{k+1}(x)

and, in this case, the sum is simply

S(x) = a_0 + x b_1(x) = b_0(x),

which is exactly the usual Horner's method.

Special case for Chebyshev series[edit]

Consider a truncated Chebyshev series

p_n(x) = a_0 + a_1T_1(x) + a_2T_2(x) + \cdots + a_nT_n(x).

The coefficients in the recursion relation for the Chebyshev polynomials are

\alpha(x) = 2x, \quad \beta = -1,

with the initial conditions

T_0(x) = 1, \quad T_1(x) = x.

Thus, the recurrence is

b_k(x) = a_k + 2xb_{k+1}(x) - b_{k+2}(x)

and the final sum is

p_n(x) = a_0 + xb_1(x) - b_2(x).

One way to evaluate this is to continue the recurrence one more step, and compute

b_0(x) = 2a_0 + 2xb_1(x) - b_2(x),

(note the doubled a0 coefficient) followed by

p_n(x) = b_0(x)-x b_1(x)-a_0=\frac{1}{2}\left[b_0(x) - b_2(x)\right].

Geodetic applications[edit]

Clenshaw's algorithm is extensively used in geodetic applications where it is usually referred to as Clenshaw summation.[4] A simple application is summing the trigonometric series to compute the meridian arc. These have the form

m(\theta) = C_0\,\theta + C_1\sin \theta + C_2\sin 2\theta + \cdots + C_n\sin n\theta.

Leaving off the initial C_0\,\theta term, the remainder is a summation of the appropriate form. There is no leading term because \phi_0(\theta) = \sin 0\theta = \sin 0 = 0.

The recurrence relation for \sin k\theta is

\sin (k+1)\theta = 2 \cos\theta \sin k\theta - \sin (k-1)\theta,

making the coefficients in the recursion relation

\alpha_k(\theta) = 2\cos\theta, \quad \beta_k = -1.

and the evaluation of the series is given by

  b_{n+1}(\theta) = b_{n+2}(\theta) = 0,

  b_k(\theta) = C_k + 2\cos \theta \,b_{k+1}(\theta) - b_{k+2}(\theta),\quad\mathrm{for\ } n\ge k \ge 1.

The final step is made particularly simple because \phi_0(\theta) = \sin 0 = 0, so the end of the recurrence is simply b_1(\theta)\sin(\theta); the C_0\,\theta term is added separately:

m(\theta) = C_0\,\theta + b_1(\theta)\sin \theta.

Note that the algorithm requires only the evaluation of two trigonometric quantities \cos \theta and \sin \theta.

Sometimes it necessary to compute the difference of two meridian arcs in a way that maintains high relative accuracy. This is accomplished by using trigonometric identities to write

  m(\theta_1)-m(\theta_2) = \sum_{k=1}^n 2 C_k

Clenshaw summation can be applied in this case[5] provided we simultaneously compute m(\theta_1)+m(\theta_2) and perform a matrix summation,

  \mathsf M(\theta_1,\theta_2) = \begin{bmatrix}
  (m(\theta_1) + m(\theta_2)) / 2\\
  (m(\theta_1) - m(\theta_2)) / (\theta_1 - \theta_2)
  \end{bmatrix} =
  C_0 \begin{bmatrix}\mu\\1\end{bmatrix} +
  \sum_{k=1}^n C_k \mathsf F_k(\theta_1,\theta_2),


  \mathsf F_k(\theta_1,\theta_2)=
       \cos k \delta \sin k \mu\\
  \displaystyle\frac{\sin k \delta}\delta \cos k \mu

\delta = \textstyle\frac12(\theta_1-\theta_2), and \mu = \textstyle\frac12(\theta_1+\theta_2). The first element of \mathsf M(\theta_1,\theta_2) is the average value of m and the second element is the average slope. \mathsf F_k(\theta_1,\theta_2) satisfies the recurrence relation

  \mathsf F_{k+1}(\theta_1,\theta_2) =
  \mathsf A(\theta_1,\theta_2) \mathsf F_k(\theta_1,\theta_2) -
  \mathsf F_{k-1}(\theta_1,\theta_2),


   \mathsf A(\theta_1,\theta_2) = 2\begin{bmatrix}
      \cos \delta \cos \mu & -\delta\sin \delta \sin \mu \\
      - \displaystyle\frac{\sin \delta}\delta \sin \mu &   \cos \delta \cos \mu

The standard Clenshaw algorithm can now be applied to yield

  \mathsf B_{n+1} &= \mathsf B_{n+2} = \mathsf 0, \\
  \mathsf B_k &= C_k \mathsf I + \mathsf A \mathsf B_{k+1} -
  \mathsf B_{k+2}, \qquad\mathrm{for\ } n\ge k \ge 1,\\
  \mathsf M(\theta_1,\theta_2) &=
    C_0 \begin{bmatrix}\mu\\1\end{bmatrix} +
    \mathsf B_1 \mathsf F_1(\theta_1,\theta_2),

where \mathsf B_k are 2\times2 matrices. Finally we have

  \frac{m(\theta_1) - m(\theta_2)}{\theta_1 - \theta_2} =
  \mathsf M_2(\theta_1, \theta_2).

In the limit \theta_2 \rightarrow \theta_1, this relation correctly evaluates the derivative dm(\theta_1)/d\theta_1, providing that, in evaluating \mathsf F_k and \mathsf
A, we take \lim_{\delta\rightarrow0}(\sin k\delta)/\delta =

See also[edit]


  1. ^ Clenshaw, C. W. (July 1955). "A note on the summation of Chebyshev series". Mathematical Tables and other Aids to Computation 9 (51): 118–110. doi:10.1090/S0025-5718-1955-0071856-0. ISSN 0025-5718.  edit Note that this paper is written in terms of the Shifted Chebyshev polynomials of the first kind T^*_n(x) = T_n(2x-1).
  2. ^ Press, WH; Teukolsky, SA; Vetterling, WT; Flannery, BP (2007), "Section 5.4.2. Clenshaw's Recurrence Formula", Numerical Recipes: The Art of Scientific Computing (3rd ed.), New York: Cambridge University Press, ISBN 978-0-521-88068-8 
  3. ^ L. Fox; I. B. Parker (1968), Chebyshev Polynomials in Numerical Analysis, Oxford University Press, ISBN 0-19-859614-6 
  4. ^ Tscherning, C. C.; Poder, K. (1982), Some Geodetic applications of Clenshaw Summation, Bolletino di Geodesia e Scienze Affini 41 (4): 349–375 
  5. ^ Karney, C. F. F. (2014), Clenshaw evaluation of differenced sums