NDLI: Neural fuzzy digital filtering: Properties

Content Provider	IEEE Xplore Digital Library
Author	Infante, J.C.G. Garcia, J.C.S. Juarez, J.J.M.
Copyright Year	2009
Description	Author affiliation: Professional School of Mechanical and Electrical Engineering (IPN), Av. Santa Ana No. 1000, Col. San Francisco Culhuacan, Coyoacan, México D.F., Mexico (Infante, J.C.G.; Garcia, J.C.S.) \|\| Research Centre of Computing (IPN), Av. Juan de Dios Bátiz S/N, Adolfo López Mateos, México D. F., Mexico (Juarez, J.J.M.)
Abstract	The paper describes the structure of the neural fuzzy filtering; giving an approach of this kind of filters called NFDF. This filters have an adaptive fuzzy inference mechanism in order to deduce the filter answers to select the best parameter values into the knowledge base (KB), actualizing the filter weights to give a good enough answers in natural linguistic sense; this require that all of the states bound into NFDF error functional, also considering the Nyquist criterion. A conventional filter can't classifies and deduce its responses into levels, the difference with the NFDF is that it characterizes the variables of a reference system and the set of membership functions using levels of response into the KB describing the classification of the filter using its probabilistic properties with respect to the rules set decisions, performing the NFDF. The paper also describes illustratively the neural net architecture into the filter mechanism. The results expressed in formal sense by the definitions related in the papers included into the paper references. Finally, the paper shows schematically the NFDF operation applying the first order ARMA model as reference system using the Matlab© software.
Starting Page	893
Ending Page	896
File Size	603829
Page Count	4
File Format	PDF
ISBN	9781424444793
ISSN	15483746
DOI	10.1109/MWSCAS.2009.5235910
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-02
Publisher Place	Mexico
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Digital filters Filtering Adaptive filters Space technology Inference mechanisms Computer architecture Mathematical model Fuzzy systems Artificial intelligence Intelligent systems
Content Type	Text
Resource Type	Article
Subject	Electronic, Optical and Magnetic Materials Electrical and Electronic Engineering

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