An algorithm for the vandermonde matrix-vector multiplication with reduced multiplicative complexity

0Citations
Citations of this article
1Readers
Mendeley users who have this article in their library.

You may have access to this PDF.

Abstract

In this chapter an algorithm for computing the Vandermonde matrix-vector product is presented. The main idea of constructing this algorithm is based on the using of Winograd’s formula for inner product computation. Multiplicative complexity of the proposed algorithm is less than multiplicative complexity of the schoolbook (naïve) method of calculation. If the schoolbook method requires MN multiplications and M(N−1) additions, the proposed algorithm takes only M + N(M + 1)/2 multiplications at the cost of extra additions compared to the naïve method. From point of view its hardware realization on VLSI where the implementation cost of multiplier is significantly greater than implementation cost of adder, the new algorithm is generally more efficient than a naïve algorithm. When the order of the Vandermonde matrix is relatively small, this algorithm will have smaller multiplicative complexity than the well-known “fast” algorithm for the same task.

Cite

CITATION STYLE

APA

Cariow, A., & Cariowa, G. (2017). An algorithm for the vandermonde matrix-vector multiplication with reduced multiplicative complexity. In Advances in Intelligent Systems and Computing (Vol. 534, pp. 185–194). Springer Verlag. https://doi.org/10.1007/978-3-319-48429-7_17

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free