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Author:

Bo, Yingchun (Bo, Yingchun.) | Qiao, Junfei (Qiao, Junfei.) (Scholars:乔俊飞) | Wang, Shuwei (Wang, Shuwei.)

Indexed by:

CPCI-S

Abstract:

Aim to solve the problems of structure design and parameters selection about conventional ESN, a small world property ESN (SWESN) is proposed in this paper. Neuron space growth algorithm is adopted to generate a physical network with small world topology on 2-D plane firstly, and then the nodes and the connections of the physical network are mapped into the neurons in reservoir of SWESN, Thus the dynamic neuron reservoir (DNR) in SWESN has small world characteristic. In addition, different typical neurons are adopted in the reservoir. the simulation experiments confirms that the SWESN generated by this method could create more abundant dynamic behavior than conventional ESN, and SWESN exceeds conventional ESN both at robustness and at anti-disturbance ability.

Keyword:

small world dynamic neurons reservoir echo state network robustness

Author Community:

  • [ 1 ] [Bo, Yingchun]Beijing Univ Technol, Coll Elect & Control Engn, Beijing 100124, Peoples R China
  • [ 2 ] [Qiao, Junfei]Beijing Univ Technol, Coll Elect & Control Engn, Beijing 100124, Peoples R China
  • [ 3 ] [Wang, Shuwei]Beijing Univ Technol, Coll Architecture & Civil Engn, Beijing 100124, Peoples R China

Reprint Author's Address:

  • [Bo, Yingchun]Beijing Univ Technol, Coll Elect & Control Engn, 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: 52-,

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: 14

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