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Mathematical Problems in Engineering
Volume 2014, Article ID 728201, 8 pages
Research Article

New Strategy for Analog Circuit Performance Evaluation under Disturbance and Fault Value

1College of Engineering, Bohai University, Jinzhou 121013, China
2Department of Engineering, Faculty of Engineering and Science, The University of Agder, Grimstad 4898, Norway

Received 23 December 2013; Accepted 6 January 2014; Published 13 February 2014

Academic Editor: Xudong Zhao

Copyright © 2014 Aihua Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Focus on this issue of disturbance and fault value is inevitable in data collection about analog circuit. A novel strategy is developed for analog circuit online performance evaluation based on fuzzy learning and double weighted support vector machine (DWMK-FSVM). First, the double weighted support vector regression machine is employed to be the indirect evaluation means, relied on the college analog electronic technology experiment to evaluate analog circuit. Second, the superiority of fuzzy learning also is addressed to realize active suppression to the fault values and disturbance parameters. Moreover, the multikernel RBF is employed by support vector regression machine to realize more flexibility online such as the bandwidths tuning. Numerical results, supported by the college analog circuit experiments, adopted OTL performance eight indexes, which were obtained via precision instrument evaluation in two years to construct training set and are then to be evaluated online based on DWMK-FSVM. Simulation results presented not only highlight precision of the evaluation strategy derived here but also illustrate its great robustness.