Behavioral circuit modeling using neural networks

Stephen V. Kosonocky

doi:10.1117/12.172495

1 February 1994 Behavioral circuit modeling using neural networks

Stephen V. Kosonocky

Proceedings Volume 2093, Substance Identification Analytics; (1994) https://doi.org/10.1117/12.172495
Event: Substance Identification Technologies, 1993, Innsbruck, Austria

Abstract

A technique is presented for automatic generation of Analog Behavioral circuit models using feed-forward neural networks in static and dynamic configurations. These models are generated, by using the data output from an accurate SPICE simulation to train a neural network to model a particular circuit function. Results are given using two types of neural networks, a static neural network to model an analog multiplier, and a recurrent neural network for modeling the dynamics of a bandlimited circuit. Simulations show that neural networks are able to learn the essential nonlinear and dynamic properties found in these circuits using the training technique described.

Citation Download Citation

Stephen V. Kosonocky "Behavioral circuit modeling using neural networks", Proc. SPIE 2093, Substance Identification Analytics, (1 February 1994); https://doi.org/10.1117/12.172495

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