Modeling of 8-bit Logarithmic Analog to Digital Converter Using Artificial Neural Network in MATLAB

Author: Pooja S. Shukla, Archana B. Yadav, Rakesh K. Pate Current Trends in Systems & Control Engineering-STM Journals Issn: 2249 – 4715 Date: 2012-07-17 05:25 Volume: 2 Issue: 1-3 Keyworde: Artificial neural network (ANN), perceptron, logarithmic analog to digital converter Full Text PDF Submit Manuscript Journals


An artificial neural network (ANN), usually called “neural network” (NN), is a mathematical or computational model that tries to simulate the structure and/or functional aspects of biological neural networks. It consists of an interconnected group of artificial neurons and processes information using a connectionist approach to computation. In most cases an ANN is an adaptive system that changes its structure based on external or internal information that flows through the network during the learning phase. Modern neural networks are non-linear statistical data modeling tools. They are usually used to model complex relationships between inputs and outputs or to find 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. Logarithmic ADC also provides a non-uniform quantization, thus compressing the input signal to digital. This is widely used in communications, 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.

Keywords: Artificial neural network (ANN), perceptron, logarithmic analog to digital converter

Keyworde: Artificial neural network (ANN), perceptron, logarithmic analog to digital converter

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