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Robust functional testing for VLSI cellular neural network implementations

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3 Author(s)
M. R. Grimaila ; Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA ; J. P. de Gyvez ; Gunhee Han

A robust testing method for detecting circuit faults within two-dimensional Cellular Neural Network (CNN) arrays is presented. The functional tests consist of a sequence of input vectors that toggle all internal nodes of the conceptual CNN model and propagate the result to the output pins. The resultant output vectors reveal nodes that exhibit opened, shorted, or stuck-at faults. The generated test vectors are universal, detect faults independent of the size or topology of the CNN array, and can be applied to any particular CNN implementation with little effort

Published in:

IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications  (Volume:44 ,  Issue: 2 )