Paper
31 December 2008 A new detection method for crosstalk delay faults in VLSI circuits using chaotic ant colony algorithms
Zhongliang Pan, Ling Chen, Guangzhao Zhang
Author Affiliations +
Proceedings Volume 7130, Fourth International Symposium on Precision Mechanical Measurements; 71305Y (2008) https://doi.org/10.1117/12.819774
Event: Fourth International Symposium on Precision Mechanical Measurements, 2008, Anhui, China
Abstract
In the current circuit design technology, due to increasing device density and operation speed, crosstalk effects are induced between circuit elements. A new method for the detection of crosstalk faults in digital circuits is presented in this paper, the method is based on both the energy function model of digital circuits and the chaotic ant colony algorithms. First of all, the energy function models of basic gate circuits are constructed, then the energy function corresponding to a digital circuit is built. The energy function of a circuit is the summation of all energy functions of the gates in the circuit. The test vectors of crosstalk delay faults in the circuit are produced by computing the minimal energy states of energy functions. Secondly, a chaotic ant colony algorithm is designed to compute the minimal energy states. Experimental results show the method proposed in this paper is able to produce the test vectors of crosstalk delay faults if there are the test vectors for the faults, therefore the high fault coverage can be obtained by the proposed method.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhongliang Pan, Ling Chen, and Guangzhao Zhang "A new detection method for crosstalk delay faults in VLSI circuits using chaotic ant colony algorithms", Proc. SPIE 7130, Fourth International Symposium on Precision Mechanical Measurements, 71305Y (31 December 2008); https://doi.org/10.1117/12.819774
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KEYWORDS
Neural networks

Digital electronics

Neurons

Detection and tracking algorithms

Complex systems

Binary data

Logic

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