Abstract:
To improve precision of the signal conditioning circuit in
an automatic test system, an error compensation approach was proposed based
on the Loose Type of Wavelet Neural Network (L-WNN), combining wavelet transform
with BP neural network. It was applied to get the error curve which stands for
the relationship of input voltage and the error of conditioning circuit. To
evaluate the performance of the L-WNN model, the error curve was also compared
to it got by BP neural network and regression analysis which applied Least Squares
Estimate (LSE). The effect of testing on the compensation result shows that
significant improvements can be made and that is an efficient method to compensate
the error of the signal conditioning circuit.
Hui Lu and Ruibo Liu, 2014. An Error Compensation Integrated Approach for Signal Conditioning Circuit Based on Wavelet Transform and BP Neural Network. Information Technology Journal, 13: 839-845.
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