Results 201 to 210 of about 10,305 (253)
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Proceedings of 36th Midwest Symposium on Circuits and Systems, 2002
In this paper a methodology for the design of FIR and IIR fuzzy filters is presented. The choice to implement fuzzy filters rises from the obvious advantages in terms of low computational costs and easy implementation. The validation of the proposed methodology has been performed through the analysis of several examples of fuzzy filters.
BAGLIO, Salvatore +3 more
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In this paper a methodology for the design of FIR and IIR fuzzy filters is presented. The choice to implement fuzzy filters rises from the obvious advantages in terms of low computational costs and easy implementation. The validation of the proposed methodology has been performed through the analysis of several examples of fuzzy filters.
BAGLIO, Salvatore +3 more
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Deadbeat Dissipative FIR Filtering
IEEE Transactions on Circuits and Systems I: Regular Papers, 2016In this paper, we propose a new deadbeat dissipative filter with a finite impulse response (FIR) structure for linear discrete-time systems with external disturbance; this filter is called a deadbeat dissipative FIR filter (DDFF). The new filter ensures $(Q,S,R)\text{--}\alpha$ -dissipativity and the deadbeat property based on three slack matrix ...
Choon Ki Ahn +2 more
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Circuits Systems and Signal Processing, 1994
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Pang, D., Ferrari, L. A., Sankar, P. V.
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Pang, D., Ferrari, L. A., Sankar, P. V.
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Asymptotic behaviour of FIR filters
2000 IEEE International Symposium on Circuits and Systems (ISCAS), 2000The recursive algorithm for the impulse response coefficients of FIR filters with maximally flat specifications was recently developed. Based on a differential equation for the almost equiripple specifications, a similar recursion is derived and presented in this paper.
Miroslav Vlcek +2 more
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Signal Processing, 1997
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José I. Acha, Rubén Martín-Clemente
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José I. Acha, Rubén Martín-Clemente
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Two-Band Hybrid FIR–IIR Filters for Image Compression
IEEE Transactions on Image Processing, 2011 Two-band analysis–synthesis filters or wavelet filters are used pervasively for compressing natural images. Both FIR and IIR filters have been studied in this context, the former being the most popular.
Jianyu Lin, M J T Smith
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IEEE Transactions on Acoustics, Speech, and Signal Processing, 1988
An optimum finite impulse response (FIR) filter bank is derived that recovers a desired signal from an array of sensors in the presence of random sensor noise and one or more coherent interfering noise sources. The required filter order is determined by the relative delays between the signal and coherent noise at each sensor, and is independent of the ...
Darrell Williamson +2 more
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An optimum finite impulse response (FIR) filter bank is derived that recovers a desired signal from an array of sensors in the presence of random sensor noise and one or more coherent interfering noise sources. The required filter order is determined by the relative delays between the signal and coherent noise at each sensor, and is independent of the ...
Darrell Williamson +2 more
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Neural filters: a class of filters unifying FIR and median filters
[Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, 1992A new class of nonlinear filters called neural filters based on the threshold decomposition and neural networks is introduced. Neural filters can approximate both linear finite impulse response (FIR) filters and weighted order statistic (WOS) filters which include median, rank order, and weighted median filters.
Lin Yin, Jaakko Astola, Yrjö Neuvo
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Universal Switching FIR Filtering
IEEE Transactions on Signal Processing, 2012We revisit recently considered universal finite-impulse-response (FIR) filtering problem and devise a scheme that asymptotically attains the expected mean-square error (MSE) of the best switching FIR filters for every underlying bounded, real-valued signal, provided that the switch rate of the best filters are sufficiently slow. As a performance metric,
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2007
IIR filters can give the same magnitude performance with fewer parameters than FIR filters. However, they cannot have exact linear phase. Their design is more complicated due to the difficulty in ensuring stability and to the non-convexity of the optimization problems.
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IIR filters can give the same magnitude performance with fewer parameters than FIR filters. However, they cannot have exact linear phase. Their design is more complicated due to the difficulty in ensuring stability and to the non-convexity of the optimization problems.
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