Convergence of split-complex backpropagation algorithm with momentum

Title:

Convergence of split-complex backpropagation algorithm with momentum

Creator:

Zhang, Huisheng and Wu, Wei

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:5de37b9c-3879-418c-9895-54d79865607a
uuid:5de37b9c-3879-418c-9895-54d79865607a
doi:10.14311/NNW.2011.21.006

Subject:

Cpmplex-valued neural networks, split-complex backpropagation algorithm, and convergence

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

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.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2011 Volume:21 | Number:1

Harvested from:

CDK

Metadata only:

false