Multichannel processing element simulation for neural networks applications

In recent years, hardware implementation of neural networks has received increasing attention from researchers. Various techniques for implementation have been used, such as analog, digital and a hybrid of both. This thesis describes the design and simulation of a digital hardware processing element. It focuses on the implementation of digital neural hardware based on bit-serial transmission and information processing which is known as the Pulse-Stream Implementation (PSI). Stochastic computing is an important PSI technique, and currently two techniques of stochastic computing are in use; they are binary stochastic computing (BSC) and pulse density modulation (PDM). As a model of neural hardware, the mapping network for modelling of freeform surfaces is discussed in geometrical terms.Master of Engineerin