Artificial neural network design of stub microstrip band-pass filters
by Geetam Singh Tomar; Vivek Singh Kushwah; Sarita Singh Bhadauria
International Journal of Ultra Wideband Communications and Systems (IJUWBCS), Vol. 3, No. 1, 2014

Abstract: In this paper, an artificial neural network (ANN) design technique for a stub microstrip band-pass filter is presented. Essential dimensions of the microstrip filter layout are used to get the relationship of the input-outputs for ANN model. This paper presents the design and analysis of stub microstrip band-pass filter at mid-band frequency 1.8 GHz, which produced improved bandwidth and minimum insertion loss of -0.5899 dB and return loss of -36.67 dB. Artificial neural network architecture has been proposed to determine the magnitude variation of scattering parameters (S-parameters) of the microstrip band-pass filters for various dimensions. The ANN model produced has been exposed to be as exact and veracious as an EM simulator and it is computationally more effective in the design. The simulation is performed using the commercial software IE3D 14.1 and ANN training of S-parameters are performed in MATLAB 7.1.

Online publication date: Mon, 30-Jun-2014

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