Paper Details: Downloads: 485
Serial Number: P1120841394
Title: Performance Evaluation of ANN Models for the Analysis of Microstrip Low Pass Filters
Authors: Dr.K.Sri Rama Krishna, J.Lakshmi Narayana, Dr.L.Pratap Reddy
Abstract: Filters play an important role in many RF/microwave applications and are used to select or confine the RF/microwave signals within assigned spectral limits. Emerging applications such as wireless communications continue to challenge RF/microwave filters with ever more stringent requirements like higher performance, smaller size, lighter weight, and lower cost. Microstrip filters are always preferred over the lumped filters at higher frequencies. In this paper we present the design and analysis of Microstrip Lowpass Filter using stepped-impedance and open circuited stubs at 1GHz. Also a simple artificial neural network model to determine the Magnitude and Phase variations of scattering parameters (S-parameters) of these filters is proposed for various frequencies. Performance of the proposed model is evaluated in terms of average and maximum estimated errors using different neural network training algorithms. Comparison of the results of the neural models with EM simulated results is also presented.
Keywords: Microstrip Low Pass Filters, ANN models, S-parameters,Training Algorithms
Journal/Conference: International Journal of Artificial Intelligence and Machine Learning
Volume: 9
Issue: 1
Submission Date: 10/8/2008 12:00:00 AM
Review Date: 11/9/2008 12:00:00 AM
Publishing Date: 11/25/2008 12:00:00 AM
Article Downloads: 485
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