作者: J. Choi , B.J. Sheu
DOI: 10.1109/IJCNN.1992.226916
关键词:
摘要: The design of an analog VLSI neural network processor for scientific and engineering applications such as pattern recognition image compression is described. backpropagation self-organization learning schemes in artificial networks require high-precision multiplication summation. presented performs high-speed feedforward computation parallel. A digital signal or a host computer can be used updating synapse weights during the phase. computing blocks consist matrix input output neuron arrays. composed current-to-voltage converter sigmoid function generator with controllable voltage gain. An improved Gilbert multiplier design. neurons are tailored to reduce settling time minimize silicon area that implementation. >