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1 Poznan University of Technology Academic Journals. Electrical Engineering

1 2010

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Correction of nominal point of circuit's parameters based on artificial dynamic (optimizing) neural network

Józefowicz K., Rybarczyk A.

Poznan University of Technology Academic Journals. Electrical Engineering

2010

No. 61

75-87

In this paper the authors propose using dynamic (optimizing) artificial neural networks as well as interactive environment MATLAB to correct nominal parameters of active filters of higher ranks with a simultaneous process of optimization of a circuit designed [8, 9]. The MATLAB's [3, 15] capabilities of fast constructing and testing algorithms of artificial neural networks as much as a verification of statistical properties of the project acquired were employed. In the paper it was shown how the Hopfield dynamic artificial neural networks aid in designing electronic circuits with a correction of the nominal point of the parameters. The analyses aimed at building neural optimizers in order to acquire such values of constructional parameters of the circuit examined which minimize the variance of selected output values, which means minimizing the dependences of the project parameters on the scatter of the values of technological parameters [10-18]. The most effective solutions of neural optimizers for a dedicated project task were presented. The authors also indicated advantages resulting from an application of optimizing networks in comparison with other methods of optimization.