Chang S, Wong K W, Zhang W, Zhang Y
Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China.
Appl Opt. 1999 Aug 10;38(23):5032-8. doi: 10.1364/ao.38.005032.
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.
提出了一种利用霍普菲尔德网络优化双极互连权重矩阵的算法。通过计算机模拟和光学实现验证了该算法的有效性。在神经网络的光学实现中，互连权重被偏置以产生非负权重矩阵。此外，增加了一个阈值子通道，以便系统能够在单个通道中实时实现双极加权求和。展示了从关联存储器和具有旋转不变性的多目标分类应用中获得的初步实验结果。
