Complex-valued neural network using simultaneous perturbation with dynamic tunneling technique

Authors:
M. Sornam;P. Thangavel
Affiliations:
University of Madras, Chennai, Tamilnadu, India;University of Madras, Chennai, Tamilnadu, India
Venue:
Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology
Year:
2012

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Abstract

This paper proposes complex-valued neural network using simultaneous perturbation method with dynamic tunneling technique. A comparison is made between conventional complex-valued backpropagation algorithm, complex-valued network using simultaneous perturbation method, complex-valued network with dynamic tunneling technique with the proposed method. All these four methods have been compared and the results are shown. For simulation, we have tested with the benchmark problem namely complex XOR with binary inputs, two real valued problems namely geometric figure rotation and similarity transformation of scaling problem. Comparison shows conventional complex-valued backpropagation method performs much better than the other three methods.