International Journal of Applied Electronics in Physics & Robotics

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Complex Neuro-Fuzzy System for Function Approximation


Affiliations
1 Department of Electrical and Electronics, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia
 

Complex fuzzy sets have been developed recently and extends truth values to unit circle in complex plane. Complex fuzzy logic then developed by employing complex fuzzy sets. In this paper, a novel adaptive complex neuro fuzzy inference system based on complex fuzzy logic is proposed for function approximation. The underlying procedure of this network and its learning rule are described. Afterwards, the performance of this system is evaluated by two functions consisting of Sine wave and Sinc function.

Keywords

Complex Fuzzy Logic (CFL), Hybrid Learning, Complex Fuzzy Set (CFS), Complex Neural Networks (CNN).
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  • Complex Neuro-Fuzzy System for Function Approximation

Abstract Views: 204  |  PDF Views: 79

Authors

Reza Shoorangiz
Department of Electrical and Electronics, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia
Mohammad H. Marhaban
Department of Electrical and Electronics, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia

Abstract


Complex fuzzy sets have been developed recently and extends truth values to unit circle in complex plane. Complex fuzzy logic then developed by employing complex fuzzy sets. In this paper, a novel adaptive complex neuro fuzzy inference system based on complex fuzzy logic is proposed for function approximation. The underlying procedure of this network and its learning rule are described. Afterwards, the performance of this system is evaluated by two functions consisting of Sine wave and Sinc function.

Keywords


Complex Fuzzy Logic (CFL), Hybrid Learning, Complex Fuzzy Set (CFS), Complex Neural Networks (CNN).