VLSI cellular array of coupled delta-sigma modulators for random analog vector generation

Parallel VLSI generation of random analog vectors with controlled statistics from deterministic chaos is the key to applications such as analog encryption and secure communications, analog built-in self-test, stochastic neural networks, and simulated annealing optimization as well as perturbation learning in neural hardware. We present a class of analog additive cellular automata which generate parallel streams of statistically independent, uniformly distributed random analog values. The underlying noise-shaping mechanism is essentially that of a MASH cascade of delta-sigma modulators. We present theory on the noise-shaping properties, scalable parallel VLSI architectures, and include experimental results from an analog VLSI prototype with 65 channels. The cell for each channel implements a switched-capacitor delta-sigma modulator, and measures 100 /spl mu/m/spl times/120 /spl mu/m in 2 /spl mu/m CMOS technology. The 65 cells are connected in a chain on a 2-D grid, and can be rearranged for use in various VLSI applications that require a parallel supply of random analog vectors.