Evidence map›Paper›PMID 25972981›Full record

ArticleCognitive neurodynamics2015

Deterministic convergence of chaos injection-based gradient method for training feedforward neural networks.

Huisheng Zhang, Ying Zhang, Dongpo Xu, Xiaodong Liu

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Article in Cognitive neurodynamics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Huisheng ZhangDepartment of Mathematics, Dalian Maritime University, Dalian, 116026 People's Republic of China ; Research Center of Information and Control, Dalian University of Technology, Dalian, 116024 People's Republic of China.
Ying ZhangDepartment of Mathematics, Dalian Maritime University, Dalian, 116026 People's Republic of China.
Dongpo XuCollege of Science, Harbin Engineering University, Harbin, 150001 People's Republic of China.
Xiaodong LiuResearch Center of Information and Control, Dalian University of Technology, Dalian, 116024 People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It has been shown that, by adding a chaotic sequence to the weight update during the training of neural networks, the chaos injection-based gradient method (CIBGM) is superior to the standard backpropagation algorithm. This paper presents the theoretical convergence analysis of CIBGM for training feedforward neural networks. We consider both the case of batch learning as well as the case of online learning. Under mild conditions, we prove the weak convergence, i.e., the training error tends to a constant and the gradient of the error function tends to zero. Moreover, the strong convergence of CIBGM is also obtained with the help of an extra condition. The theoretical results are substantiated by a simulation example.

Indexed as

Batch learningChaos injection-based gradient methodConvergenceFeedforward neural networksOnline learning

Identifiers

PMID25972981
PMCPMC4427592

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.