General neural computer architecture and its ANN-based task assignment method for parallel-distributed processing

Hu Chao; Sylvian R. Ray; Nanning Zheng

doi:10.1117/12.211998

16 June 1995 General neural computer architecture and its ANN-based task assignment method for parallel-distributed processing

Hu Chao, Sylvian R. Ray, Nanning Zheng

Author Affiliations +

Proceedings Volume 2488, Visual Information Processing IV; (1995) https://doi.org/10.1117/12.211998
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

Abstract

A new DSP-based neural simulating computer architecture and its ANN-based assignment method for parallel distributed processing are proposed. The hardware of the proposed neural simulating computer can be reconfigured in terms of a variety of research interests and requirements of pattern recognition. The software programming environment utilizes an intelligent compiler to perform static task assignment in both the cases of single-task muliprocessor and multitask processor. An improved Hopfield neural network which can converge to global optical solution is employed by the compiler to map different tasks or neurons to their corresponding real processors. An approach of introducing hidden layer to increase the computation ability of the neural simulating computer is also developed. Finally, a proof is given which shows that the use of improved Hopfield algorithm and the modification to network structure doesn't change the intrinsic properties of the original network.

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Hu Chao, Sylvian R. Ray, and Nanning Zheng "General neural computer architecture and its ANN-based task assignment method for parallel-distributed processing", Proc. SPIE 2488, Visual Information Processing IV, (16 June 1995); https://doi.org/10.1117/12.211998

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