A Constructive Approach for Finding Arbitrary Roots of Polynomials By Neural Networks  

Oleh:

Huang, De-Shuang

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 15 no. 2 (Mar. 2004), page 477-491.
Topik: unit root; constructive approach; arbitrary roots; polynomials; neural network

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.10 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

This paper proposes a constructive approach for finding arbitrary (real or complex) roots of arbitrary (real or complex) polynomials by multilayer perceptron network (MLPN) using constrained learning algorithm (CLA), which encodes the a priori information of constraint relations between root moments and coefficients of a polynomial into the usual BP algorithm (BPA). Moreover, the root moment method (RMM) is also simplified into a recursive version so that the computational complexity can be further decreased, which leads the roots of those higher order polynomials to be readily found. In addition, an adaptive learning parameter with the CLA is also proposed in this paper ; an initial weight selection method is also given. Finally, several experimental results show that our proposed neural connectionism approaches, with respect to the non neural ones, are more efficient and feasible in finding the arbitrary roots of arbitrary polynomials.

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