Abstract

The winner-take-all (WTA) network is useful in database management, very large scale integration (VLSI) design, and digital processing. The synthesis procedure of WTA on single-layer fully connected architecture with sigmoid transfer function is still not fully explored. We discuss the use of simultaneous recurrent networks (SRNs) trained by Kalman filter algorithms for the task of finding the maximum among N numbers. The simulation demonstrates the effectiveness of our training approach under conditions of a shared-weight SRN architecture. A more general SRN also succeeds in solving a real classification application on car engine data.

Department(s)

Electrical and Computer Engineering

Sponsor(s)

Mary K. Finley Missouri Endowment
National Science Foundation (U.S.)

Keywords and Phrases

Backpropagation Through Time (BPTT); Extended Kalman Filter (EKF); Simultaneous Recurrent Network (SRN); Winner-Take-All (WTA)

Document Type

Article - Journal

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2007 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

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