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Author:

Yang, Gang (Yang, Gang.) | Qiao, Junfei (Qiao, Junfei.) (Scholars:乔俊飞) | Yuan, Mingzhe (Yuan, Mingzhe.)

Indexed by:

CPCI-S

Abstract:

We propose a Spatial Artificial Neural Network (SANN) with spatial architecture which consists of a multilayer feedforward neural network with hidden units adopt recurrent lateral inhibition connection, all input and hidden neurons have synapses connections with the output neurons. In addition, a supervised learning algorithm based on error back propagation is developed. The proposed network has shown a superior generalization capability in simulations with pattern recognition and non-linear function approximation problems. And, the experimental also shown that SANN has the capability of avoiding local minima problem.

Keyword:

multilayer feedforward network spatial span connection lateral inhibition mechanism

Author Community:

  • [ 1 ] [Yang, Gang]Beijing Univ Technol, Coll Elect Informat & Control Engn, Intelligent Syst Inst, Beijing 100124, Peoples R China
  • [ 2 ] [Qiao, Junfei]Beijing Univ Technol, Coll Elect Informat & Control Engn, Intelligent Syst Inst, Beijing 100124, Peoples R China
  • [ 3 ] [Yuan, Mingzhe]Chinese Acad Sci, Inst Automat, Shenyang 110016, Peoples R China

Reprint Author's Address:

  • [Yang, Gang]Beijing Univ Technol, Coll Elect Informat & Control Engn, Intelligent Syst Inst, Beijing 100124, Peoples R China

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Source :

ADVANCES IN NEURAL NETWORKS - ISNN 2011, PT I

ISSN: 0302-9743

Year: 2011

Volume: 6675

Page: 495-,

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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