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An accurate analysis method for complex IC analog neural network-based systems using high-level software tools

For current microelectronic integrated systems, the design methodology involves different steps that end up in the full system simulation by means of electrical and physical models prior to its manufacture. However, the higher the circuit complexity, the more time is required to carry out these simulations, and the convergence of the numerical methods and, hence, the validity of the results are not guaranteed. This paper shows the use of a high-level tool based on Matlab to simulate the operation of an artificial neural network implemented in a mixed analog-digital CMOS process. The proposed tool enables modifying the neural model architecture to adapt its characteristics to those of the electronic system, and provides accurate behavioral models, predicting the microelectronic system operation under different circumstances before its physical implementation.