Robust functional testing for vlsi cellular neural network implementations

Michael Russell Grimaila, Jose Pineda De Gyvez, Gunhee Han

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


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. Index Terms-Cellular Neural Networks, Testing, C-Testability.

Original languageEnglish
Pages (from-to)161-166
Number of pages6
JournalIEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications
Issue number2
Publication statusPublished - 1997

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering


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