1 February 1991 Implementing neural-morphological operations using programmable logic
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Proceedings Volume 1382, Intelligent Robots and Computer Vision IX: Neural, Biological, and 3D Methods; (1991) https://doi.org/10.1117/12.25202
Event: Advances in Intelligent Robotics Systems, 1990, Boston, MA, United States
Abstract
Neural network models have been studied for a number of years for achieving human-like performances in the fields of image and speech recognition. There has been a recent resurgence in the field of neural networks caused by new topologies and algorithms analog VLSI implementation techniques and the belief that massive parallelism is essential for high performance image and speech recognition. This paper presents an idea of implementing neural networks with Boolean programmable logic models. Though the approach didn''t adopt continuous analog framework commonly used in related research it can handle a variety of neural network applications and avoid some of the limitations of threshold logic networks. Dynamically programmable logic modules (or DPLM''s) can be implemented with digital multiplexers. Each node performs a dynamically-assigned Boolean function of its input vectors. Therefore the overall network is a combinational circuit and its outputs are Boolean global functions of the network''s input variables. 1.
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Frank Yeong-Chya Shih, Frank Yeong-Chya Shih, Jenlong Moh, Jenlong Moh, } "Implementing neural-morphological operations using programmable logic", Proc. SPIE 1382, Intelligent Robots and Computer Vision IX: Neural, Biological, and 3D Methods, (1 February 1991); doi: 10.1117/12.25202; https://doi.org/10.1117/12.25202
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