Current position: Home >> Scientific Research >> Paper Publications

CONVERGENCE OF SPLIT-COMPLEX BACKPROPAGATION ALGORITHM WITH A MOMENTUM

Release Time:2019-03-09  Hits:

Indexed by: Journal Article

Date of Publication: 2011-01-01

Journal: NEURAL NETWORK WORLD

Included Journals: EI、SCIE、Scopus

Volume: 21

Issue: 1

Page Number: 75-90

ISSN: 1210-0552

Key Words: Complex-valued neural networks; split-complex backpropagation algorithm; convergence

Abstract: This paper investigates a split-complex backpropagation algorithm with momentum (SCBPM) for complex-valued neural networks. Convergence results for SCBPM are proved under relaxed conditions and compared with the existing results. Monotonicity of the error function during the training iteration process is also guaranteed. Two numerical examples are given to support the theoretical findings.

Prev One:CONVERGENCE OF GRADIENT METHOD FOR DOUBLE PARALLEL FEEDFORWARD NEURAL NETWORK

Next One:A NOVEL SPIKING PERCEPTRON THAT CAN SOLVE XOR PROBLEM