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Applied Optics

Applied Optics


  • Vol. 38, Iss. 23 — Aug. 10, 1999
  • pp: 5032–5038

Algorithm for optimizing bipolar interconnection weights with applications in associative memories and multitarget classification

Shengjiang Chang, Kwok-Wo Wong, Wenwei Zhang, and Yanxin Zhang  »View Author Affiliations

Applied Optics, Vol. 38, Issue 23, pp. 5032-5038 (1999)

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An algorithm for optimizing a bipolar interconnection weight matrix with the Hopfield network is proposed. The effectiveness of this algorithm is demonstrated by computer simulation and optical implementation. In the optical implementation of the neural network the interconnection weights are biased to yield a nonnegative weight matrix. Moreover, a threshold subchannel is added so that the system can realize, in real time, the bipolar weighted summation in a single channel. Preliminary experimental results obtained from the applications in associative memories and multitarget classification with rotation invariance are shown.

© 1999 Optical Society of America

OCIS Codes
(070.5010) Fourier optics and signal processing : Pattern recognition
(200.3050) Optics in computing : Information processing
(200.4260) Optics in computing : Neural networks
(200.4490) Optics in computing : Optical buffers
(200.4650) Optics in computing : Optical interconnects
(200.4860) Optics in computing : Optical vector-matrix systems

Original Manuscript: July 20, 1998
Revised Manuscript: April 30, 1999
Published: August 10, 1999

Shengjiang Chang, Kwok-Wo Wong, Wenwei Zhang, and Yanxin Zhang, "Algorithm for optimizing bipolar interconnection weights with applications in associative memories and multitarget classification," Appl. Opt. 38, 5032-5038 (1999)

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