Implementation of Neural Hardware with the Neural VLSI of URAN in Applications with Reduced Representations

Part of Advances in Neural Information Processing Systems 7 (NIPS 1994)

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Il Han, Ki-Chul Kim, Hwang-Soo Lee


implement Korean

This paper describes a way of neural hardware implementation with the analog-digital mixed mode neural chip. The full custom neural VLSI of Universally Reconstructible Artificial Neural network (URAN) is used system. A to multi-layer perceptron with is trained successfully under the limited accuracy in computations. The network with a large frame input layer is tested to recognize spoken korean words at a forward retrieval. Multichip hardware module is suggested with eight chips or more for the extended performance and capacity.