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A general neural minimization algorithm which can be applied to arbitrary types of polynomial energy functions is presented. The algorithm can be operated in a synchronous as well as asynchronous way. The synchronous algorithm can be implemented by highly parallel optical systems.
© 1989 Optical Society of America
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