Multistability of Discrete-Time Recurrent Neural Networks With Unsaturating Piecewise Linear Activation Functions  

Oleh:

Kok, Kiong Tan ; Yi, Zhang

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 15 no. 2 (Mar. 2004), page 329-336.
Topik: NEURAL NETWORKS; multistability; discrete - time; neural networks; piecewise linear activation; functions

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 studies the multistability of a class of discrete - time recurrent neural networks with unsaturating piecewise linear activation functions. It addresses the nondivergence, global attractivity, and complete stability of the networks. Using the local inhibition, conditions for nondivergence are derived, which not only guarantee nondivergence, but also allow for the existence of multi equilibrium points. Under these nondivergence conditions, global attractive compact sets are obtained. Complete stability is studied via constructing novel energy functions and using the well - known Cauchy Convergence Principle. Examples and simulation results are used to illustrate the theory.

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