Feedforward associative memory switched-capacitor artificial neural networks

Observed spatiotemporal firings of biological neurons have lead many researchers to believe that the rate of firings of these biological neurons is what conveys neuronal information in the brain. In this paper we seek to highlight parallels between biological neurons and observed effects in real neurons, with artificial neurons implemented as switched-capacitor structures. One such effect is the heavy use of lateral inhibition observed in the brain that is often modeled by winner-take-all analog circuits. This paper introduces a novel winner-take-all circuit using switched capacitors that truly mimics this effect seen in biological systems. In addition, we show how switched-capacitor structures can also cater to both binary and bipolar coding of input data vectors, as required by many artificial neural network paradigms today. Applications of switched-capacitors artificial neural networks to pattern recognition and character recognition problems using feedforward associative neural networks are also discussed, and two examples are provided. Simulations using both HSPICE and SWITCAP2 confirm all our expectations.

[1]  Ernest W. Kent,et al.  The Brains of Men and Machines , 1981 .

[2]  Richard P. Lippmann,et al.  An introduction to computing with neural nets , 1987 .

[3]  K. Suyama,et al.  Simulation of mixed switched-capacitor/digital networks with signal-driven switches , 1990 .

[4]  Brent Maundy,et al.  A self-organizing switched-capacitor neural network , 1991 .

[5]  Brent Maundy,et al.  Switched-capacitor neural networks using pulse based arithmetic , 1990 .

[6]  E.I. El-Masry,et al.  Pulse arithmetic in switched capacitor neural networks , 1990, Proceedings of the 33rd Midwest Symposium on Circuits and Systems.

[7]  Malcolm R. Haskard,et al.  Analog VLSI design - nMOS and CMOS , 1988, Prentice Hall Silicon systems engineering series.

[8]  J. Mann,et al.  A self-organizing neural net chip , 1988, Proceedings of the IEEE 1988 Custom Integrated Circuits Conference.

[9]  Teuvo Kohonen,et al.  The self-organizing map , 1990 .

[10]  R. Perfetti.  «Winner-take-all» circuit for neurocomputing applications , 1990 .

[11]  E. I. El-Masry,et al.  A switched capacitor bidirectional associative memory , 1990 .

[12]  J J Hopfield,et al.  Neurons with graded response have collective computational properties like those of two-state neurons. , 1984, Proceedings of the National Academy of Sciences of the United States of America.

[13]  Carver Mead,et al.  Analog VLSI and neural systems , 1989 .

[14]  Alan F. Murray,et al.  Analogue computation using VLSI neural network devices , 1990 .

[15]  Teuvo Kohonen,et al.  Self-Organization and Associative Memory , 1988 .

[16]  W. T. Illingworth,et al.  Practical guide to neural nets , 1991 .

[17]  Massimo A. Sivilotti,et al.  Real-time visual computations using analog CMOS processing arrays , 1987 .