Linear Noisy Networks with Stochastic Components

All circuit components have uncertainties inherent to the underlying fabrication process that, in large networks, may change the overall circuit response unpredictably. In the absence of a robust general model to incorporate individual component uncertainties and the concomitant stochastic thermal noise characteristics, under-simulating from the massively high-dimensional experiment space via Monte Carlo techniques and over-designing the final product against potentially undiscovered faults have become de facto standard. Such practices do not only cost simulation time, circuit area, and power, but also provide a partial understanding of the underlying uncertainty and of ways to exploit it. This paper investigates the impact of component uncertainties in linear resistive networks, where individual elements are subject to Johnson-Nyquist noise.