Artificial neural networks: principles and VLSI implementation

Jan Van der Spiegel; Paul Mueller; David Blackman; Christopher Donham; Ralph Etienne-Cummings; Pervez Aziz; A. Choudhury; L. Jones; J. Xin

doi:10.1117/12.26307

1 November 1990 Artificial neural networks: principles and VLSI implementation

Jan Van der Spiegel, Paul Mueller, David Blackman, Christopher Donham, Ralph Etienne-Cummings, Pervez Aziz, A. Choudhury, L. Jones, J. Xin

Author Affiliations +

Proceedings Volume 1405, 5th Congress of the Brazilian Society of Microelectronics; (1990) https://doi.org/10.1117/12.26307
Event: 5th Congress of the Brazilian Society of Microelectronics, 1990, Sao Paulo, Brazil

Abstract

This paper gives an overview of the principles and hardware realizations of artificial neural networks. The first section describes the operation of neural networks, using simple examples to illustrate some of its key properties. Next the different architectures are described, including single and multiple perceptron networks, Hopfield and Kohonen nets. A brief discussion of the learning rules employed in feedforward and feedback networks follows. The final section discusses hardware implementations of neural systems with emphasis on analog VLSI. Different approaches for the realizations of neurons and synapses are described. A brief comparison between analog and digital techniques is given.

Citation Download Citation

Jan Van der Spiegel, Paul Mueller, David Blackman, Christopher Donham, Ralph Etienne-Cummings, Pervez Aziz, A. Choudhury, L. Jones, and J. Xin "Artificial neural networks: principles and VLSI implementation", Proc. SPIE 1405, 5th Congress of the Brazilian Society of Microelectronics, (1 November 1990); https://doi.org/10.1117/12.26307

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