Modeling & Simulation of An 8-Bit Logarithmic Analog-to-Digital Converter in Matlab using Artificial Neural Network

Abstract

An artificial neural network (ANN), sometimes known as a "neural network" is a mathematical or computer model that attempts to imitate the structure and/or functions of biological neural networks. It is made up of a network of artificial neurons that processes data using a connectionist approach to computing. During the learning phase, an ANN is typically an adaptable system that changes its structure depending on external or internal information that passes through the network. Modern neural networks are statistical data modelling methods that are non-linear. They are often used to model complicated input-output interactions or to detect patterns in data. The Logarithmic Analog to Digital Converter gives Logarithmic digital output of the given Analog input signal. Basically it is used to increase input dynamic range. The non-uniform quantization provided by a logarithmic ADC compresses the input signal to digital. This is common in communications and instrumentation, medical instruments like Deep Brain Stimulation etc. In this paper, we have tried to have Logarithmic analog to digital Converter with neural network in MATLAB using a perceptron design.