DocumentCode :
3441489
Title :
Behavioral testing of cellular neural networks
Author :
Willis, John ; De Gyvez, José Pineda
Author_Institution :
Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA
Volume :
6
fYear :
1994
fDate :
30 May-2 Jun 1994
Firstpage :
229
Abstract :
This paper addresses the functional behavior of Cellular Neural Networks (CNN). The impact of variable convergence times on the proper operation of the network is discussed A test method is presented to determine the functionality of the network. The function fault models assume that the cells are unable to switch between limiting states. The proposed method attains 100% stuck-at fault coverage without any extra hardware for its implementation. Moreover, the required number of test vectors is constant and independent of the array size which makes it suitable for practical implementations. The paper discusses the new fault model, presents the algorithmic procedures and shows simulated testing results
Keywords :
cellular neural nets; convergence; fault diagnosis; testing; algorithmic procedures; behavioral testing; cellular neural networks; fault model; functional behavior; stuck-at fault coverage; variable convergence times; Cellular neural networks; Circuit faults; Convergence; Fault detection; Hardware; Neural networks; Nonlinear circuits; Switches; Testing; Voltage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1994. ISCAS '94., 1994 IEEE International Symposium on
Conference_Location :
London
Print_ISBN :
0-7803-1915-X
Type :
conf
DOI :
10.1109/ISCAS.1994.409569
Filename :
409569
Link To Document :
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