Neuro fuzzy model for adaptive filtering of oscillatory signals

dc.contributor.author	Mahapatra, Sakuntala
dc.contributor.author	Nayak, Santanu K.
dc.contributor.author	Sabat, Samrat L.
dc.date.accessioned	2022-03-27T06:44:19Z
dc.date.available	2022-03-27T06:44:19Z
dc.date.issued	2001-12-01
dc.description.abstract	In this paper we have developed a neuro fuzzy model for adaptive filtering of oscillatory signals embedded with white noise. Such type of fuzzy adaptive filters are constructed from a set of fuzzy IF-THEN rules, which change adaptively to minimise the cost function until a desired information is available. Here we have used a generalised cost function for better convergence of the error. This algorithm is simulated on a digital signal processor in order to track the signal and to filter out the disturbances present in the signal at a particular instant of time. The system presented here, can measure both types of information like numerical as well as linguistic. © 2001 Elsevier Science Ltd. All rights reserved.
dc.identifier.citation	Measurement: Journal of the International Measurement Confederation. v.30(4)
dc.identifier.issn	02632241
dc.identifier.uri	10.1016/S0263-2241(01)00007-0
dc.identifier.uri	https://www.sciencedirect.com/science/article/abs/pii/S0263224101000070
dc.identifier.uri	https://dspace.uohyd.ac.in/handle/1/9995
dc.subject	Neuro fuzzy model and intelligent instrument
dc.title	Neuro fuzzy model for adaptive filtering of oscillatory signals
dc.type	Journal. Article
dspace.entity.type

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