Application of adaptive neuro-fuzzy inference systems for analyzing non-Gaussian signal

Author

Chabaa, S. ; Zeroual, A. ; Antari, J.

Author_Institution

Dept. of Phys., Cadi Ayyad Univ., Marrakesh, Morocco

fYear

2009

fDate

2-4 April 2009

Firstpage

377

Lastpage

380

Abstract

In this paper, we developed a model based on the adaptive neuro-fuzzy inference systems (ANFIS) for analyzing a real non Gaussian process. The obtained results show that the generated values using ANFIS techniques have similar statistical characteristics as real data. Additionally, the developed model fits well real data and can be used for predicting purpose. Compared with existing model obtained by third order moment (TOM) method, our model has better prediction accuracy.

Keywords

fuzzy neural nets; fuzzy reasoning; fuzzy set theory; fuzzy systems; mean square error methods; signal processing; statistical analysis; ANFIS; RMSE; adaptive neuro-fuzzy inference system; fuzzy set theory; nonGaussian signal analysis; statistical characteristics; third order moment method; Adaptive systems; Automatic control; Fuzzy logic; Fuzzy neural networks; Fuzzy reasoning; Fuzzy systems; Neural networks; Predictive models; Signal analysis; Signal processing; Adaptive neuro-fuzzy inference systems (ANFIS); Prediction; Tank noise; modeling;

fLanguage

English

Publisher

ieee

Conference_Titel

Multimedia Computing and Systems, 2009. ICMCS '09. International Conference on

Conference_Location

Ouarzazate

Print_ISBN

978-1-4244-3756-6

Electronic_ISBN

978-1-4244-3757-3

Type

conf

DOI

10.1109/MMCS.2009.5256668

Filename

5256668