Wavelet Neural Network Approach for Testing of Switched-Current Circuits

Authors:
Guo Jierong;He Yigang;Liu Meirong
Affiliations:
Institute of Information Technology, Hunan university of Arts and Science, Changde, China 415000 and College of Electrical and Information Engineering, Hunan University, Changsha, China 410082;College of Electrical and Information Engineering, Hunan University, Changsha, China 410082;College of Electrical and Information Engineering, Hunan University, Changsha, China 410082
Venue:
Journal of Electronic Testing: Theory and Applications
Year:
2011

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Abstract

Combining the time and frequency location and multiple-scale analysis of wavelet transform with the nonlinear mapping and generalizing of neural network, an efficient defect-oriented parametric test method using Wavelet Neural Network (WNN) for switched-current integrated circuits is proposed. Contraposing to the fully compatible digital CMOS technology and current scaling calculation of SI circuits, parameter cohort of switched current elements is used to compute the sensitivity and gain tolerance and is applied for selecting the test models. The selecting of the appropriate wavelet function based on particular switched current fault signal is discussed, and the number of network input and output nodes are determined by the circuit status and dimension of eigenvector which is the energy of wavelet decomposition coefficient. To simplify configuration of the neural network, the sampled data was preprocessed by wavelet transform. Illustrative examples show that the proposed wavelet neural network method for testing of switched current circuits is effective.