A Collaborative Neurodynamic Approach to Sparse Coding

Hangjun Che, Jun Wang, Wei Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Citations (Scopus)

Abstract

In this paper, a collaborative neurodynamic approach is proposed for sparse coding. As the formulated sparse coding optimization problem with l0 -norm objective function is NP-hard, it is reformulated as a global optimization problem based on an inverted Gaussian function. A group of neurodynamic optimization models is employed to solve the reformulated problem by gradually decreasing the value of the parameter of the inverted Gaussian function. The experimental results show the superior performance of the proposed approach.

Original languageEnglish
Title of host publicationAdvances in Neural Networks – ISNN 2019 - 16th International Symposium on Neural Networks, ISNN 2019, Proceedings
EditorsHuchuan Lu, Huajin Tang, Zhanshan Wang
PublisherSpringer Verlag
Pages454-462
Number of pages9
ISBN (Print)9783030227951
DOIs
Publication statusPublished - 2019
Externally publishedYes
Event16th International Symposium on Neural Networks, ISNN 2019 - Moscow, Russian Federation
Duration: 10 Jul 201912 Jul 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11554 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Symposium on Neural Networks, ISNN 2019
Country/TerritoryRussian Federation
CityMoscow
Period10/07/1912/07/19

Keywords

  • Collaborative neurodynamic optimization
  • Signal reconstruction
  • Sparse coding

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