DocumentCode :
2334925
Title :
Applying non-ideal mixed analog-digital multipliers in electronic processing circuits based on neural networks
Author :
Lajusticia, Carlos ; Medrano, Nicolás ; Zatorre, Guillermo ; Martin, Bonifacio
Author_Institution :
Electron. Design Group, Zaragoza Univ., Spain
Volume :
2
fYear :
2003
fDate :
16-19 Sept. 2003
Firstpage :
362
Abstract :
This paper analyses effects of component mismatching and non-linearities in mixed analog-digital multipliers used in analog implementation of artificial neural networks. Function estimation and classification problems using a multilayer perceptron are studied, analyzing their results, accuracy requirements and network modifications required.
Keywords :
analogue processing circuits; analogue-digital conversion; function approximation; multilayer perceptrons; artificial neural networks; electronic processing circuits; embedded systems; function classification; function estimation; mixed analog-digital multipliers; multilayer perceptron; Analog-digital conversion; Artificial neural networks; Circuits; Energy consumption; Intelligent networks; Intelligent sensors; Multilayer perceptrons; Neural networks; Neurons; Resistors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Emerging Technologies and Factory Automation, 2003. Proceedings. ETFA '03. IEEE Conference
Print_ISBN :
0-7803-7937-3
Type :
conf
DOI :
10.1109/ETFA.2003.1248722
Filename :
1248722
Link To Document :
بازگشت