Self-clocking modulator as analog neuron

Abstract

A self-clocking (or self-oscillating) modulator in signal processing, similar to a ΣΔ modulator, with particular application in the design of neural networks based on such modulators is described. A system of multiple self-clocking modulators and supporting structures may be configured to perform a calculation similar to that of an analog computer, such as a neural network, at lower power and smaller size than a digital implementation. Such a system constructed using the present approach does not require a sequential solution, but rather converges on a solution in one step; unlike the typical prior art, it thus requires no clock and operates asynchronously in a manner similar to a conventional analog computer. The self-clocking modulator can function as a neuron in a neural network, receiving a sum-of-products signal and generating an output stream like that of a ΣΔ modulator that represents this sum-of-products, potentially also including an activation function and offset.