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An efficient A/D converter using electronic neurons

Title:

An efficient A/D converter using electronic neurons

Zheng, Ke Wei (2006) An efficient A/D converter using electronic neurons. Masters thesis, Concordia University.

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Abstract

Analog to digital converter (ADC) is an important building block for modern electronic design. There exist different type of ADC, such as Integrating ADC; Successive approximation ADC; Flash ADC and so on. Each of them usually focuses on one or more design consideration. For example Flash ADC has high working frequency but it consume more power than other type of ADCs. We are also aware of that human brain works by receiving minute electrical information signals produced by nerve cells known as neurons. A neuron 'fires' (i.e., turns on) when it receives a stimulus of sufficient strength, and emits a number of narrow pulses known as 'action potentials'. The number of such pulses is proportional to the strength of the stimulus. Inspired by this physiological nature of functioning of a neuron, i.e., production of a bundle of actions potentials proportional to the level of a stimulus, an ADC with the architecture of 'electronic neuron cell plus counter' is implemented using transistors in a standard CMOS integrated circuit technology. The approach is simple and the result is a low voltage low power unipolar A/D converter working in middle frequency range. The converter is very competitive with other known converters in terms of 'energy per sample'. Furthermore, by using a new calibration method, our ADC affords to very good linearity performance

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Thesis (Masters)
Authors:Zheng, Ke Wei
Pagination:xiv, 95 leaves : ill. ; 29 cm.
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Electrical and Computer Engineering
Date:2006
Thesis Supervisor(s):Raut, Rabin
Identification Number:LE 3 C66E44M 2006 Z54
ID Code:8714
Deposited By: Concordia University Library
Deposited On:18 Aug 2011 18:33
Last Modified:13 Jul 2020 20:05
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