Adaptive noise cancellation using type-2 fuzzy logic and neural networks

Author

Castillo, Oscar ; Melin, Patricia

Author_Institution

Dept. of Comput. Sci., Tijuana Inst. of Technol., Mexico

Volume

2

fYear

2004

fDate

25-29 July 2004

Firstpage

1093

Abstract

We describe in this paper the use of type-2 fuzzy logic for achieving adaptive noise cancellation. The objective of adaptive noise cancellation is to filter out an interference component by identifying a model between a measurable noise source and the corresponding un-measurable interference. We propose the use of type-2 fuzzy logic to find this model. The use of type-2 fuzzy logic is justified due to the high level of uncertainty of the process, which makes difficult to find appropriate parameter values for the membership functions.

Keywords

adaptive filters; filtering theory; fuzzy logic; fuzzy neural nets; interference suppression; signal denoising; adaptive noise cancellation; filtering theory; measurable noise source; membership functions; neural networks; parameter values; type-2 fuzzy logic; uncertainty level; unmeasurable interference; Adaptive filters; Distortion measurement; Electrocardiography; Fuzzy logic; Interference; Neural networks; Noise cancellation; Noise measurement; Nonlinear distortion; Nonlinear filters;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 2004. Proceedings. 2004 IEEE International Conference on

ISSN

1098-7584

Print_ISBN

0-7803-8353-2

Type

conf

DOI

10.1109/FUZZY.2004.1375563

Filename

1375563