Implementation of Neural Hardware with the Neural VLSI of URAN in Applications with Reduced Representations
نویسندگان
چکیده
Ki-Chul Kim Dept. of Info and Comm KAIST Seoul, 130-012, Korea 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 to implement Korean speech recognition system. A multi-layer perceptron with linear neurons 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. 812 ll-Song Han, Hwang-Soo Lee, Ki-Chul Kim
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