On Fault Probabilities and Yield Models for Analog VLSI Neural Networks

We investigate the estimation of fault probabilities and yield for analog VLSI implementations of neural computation. Our analysis is limited to structures that can be mapped directly onto silicon as truly distributed parallel processing systems. Our work improves on the framework suggested recently by Feltham and Maly [3] and is also applicable to analog… CONTINUE READING