DocumentCode :
356064
Title :
A one bit neural A/D converter
Author :
Alarid, J.
Author_Institution :
Dept. of Comput. Sci., New Mexico Highlands Univ., Las Vegas, NM
Volume :
1
fYear :
1999
fDate :
1999
Firstpage :
360
Abstract :
A well-known class of one-bit A/D converters are delta modulators. There are two main classes of delta modulators; linear and adaptive. In this paper an adaptive delta modulator, where adaptation is achieved with a neural network, is described. The network is of the perceptron type and consists of five inputs, one hidden layer and an output. We have simulated signal-to-noise ratio for three different types of delta modulators, and results have shown the newly proposed delta modulator has better signal to noise ratio over given dynamic range
Keywords :
analogue-digital conversion; delta modulation; neural chips; perceptrons; 1 bit; adaptive delta modulator; dynamic range; hidden layer; neural A/D converter; perceptron type; signal-to-noise ratio; Computer science; Delta modulation; Dynamic range; Frequency; Neural networks; Neurofeedback; Noise level; Sampling methods; Shift registers; Signal to noise ratio;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1999. 42nd Midwest Symposium on
Conference_Location :
Las Cruces, NM
Print_ISBN :
0-7803-5491-5
Type :
conf
DOI :
10.1109/MWSCAS.1999.867280
Filename :
867280
Link To Document :
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