NDLI: Neural filtering method for stationary signal processes

Content Provider	Springer Nature Link
Author	Sugisaka, Masari
Copyright Year	1997
Abstract	In this paper a new method of neural filtering using artificial neural network systems is presented for the filtering problems of linear and nonlinear, stationary and nonstationary stochastic signals. The neural filter (denoted neurofilter) developed in this paper has either finite impulse response (FIR) structure or infinite impulse response (IIR) structure. The neurofilter differs from the conventional linear digital FIR and IIR filters because the artificial neural network system used in the neurofilter has a nonlinear structure due to the sigmoid function. Numerical studies for the estimation of a second-order Butterworth process are performed by changing the structures of the neurofilter in order to evaluate the performance indices under changes of the output noises or disturbances. The results obtained from these studies verified the capabilities which are essentially necessary for on-line filtering of various stochastic signals.
Starting Page	165
Ending Page	168
Page Count	4
File Format	PDF
ISSN	14335298
Journal	Artificial Life and Robotics
Volume Number	1
Issue Number	4
e-ISSN	16147456
Language	English
Publisher	Springer-Verlag
Publisher Date	1997-01-01
Publisher Place	Tokyo
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Neural filtering Stochastic signals FIR and IIR structures Computation by Abstract Devices Artificial Intelligence (incl. Robotics) Automation and Robotics
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Biochemistry, Genetics and Molecular Biology

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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