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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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Stability of adaptive FIR filters
ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing, 2003Svoboda's matrix inversion algorithm is used to analyze the adaptive FIR (finite-impulse response) filter. To get stable response, conditions of convergence and solvability have to be met. They determine the maximum correction step of the adaptive loop, the lower bound of the norm of output signal vector and the statistical properties of the reference ...
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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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Implementation of a frequency FIR filter as 2D-FIR filter based on FPGA
2015 AI & Robotics (IRANOPEN), 2015In this paper, it is tried to transfer one of the powerful tools for image processing from the frequency domain to spatial domain. In which the frequency concepts is used in the field of image processing based on FPGA. The process is as follows that first a low-pass FIR filter in frequency domain is designed and then it is transferred from frequency ...
Ahmad Fakharian, Saeed Badr, Mohsen Abdi
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2020
In this chapter, we discuss efficient realization of FIR filters. First, we focus on nonrecursive structures with linear-phase response and their realisation using direct form, transposed form, cascade form, and delay-complementary FIR filter pairs. Recursive structures like Lagrange and running-sum structures are also discussed.
Lars Wanhammar, Tapio Saramäki
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In this chapter, we discuss efficient realization of FIR filters. First, we focus on nonrecursive structures with linear-phase response and their realisation using direct form, transposed form, cascade form, and delay-complementary FIR filter pairs. Recursive structures like Lagrange and running-sum structures are also discussed.
Lars Wanhammar, Tapio Saramäki
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ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing, 1985
Given a tissue of suitable size one may program the tissues cells so that it implements any FIR filter. The parameters of such a tissue program are: the number of taps, the tap values, the word sizes (input, ou tput, and internal), and the type of arithmetic (twos complement, one's complement, or sign-magnitude). The FIR tissue thus is versatile.
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Given a tissue of suitable size one may program the tissues cells so that it implements any FIR filter. The parameters of such a tissue program are: the number of taps, the tap values, the word sizes (input, ou tput, and internal), and the type of arithmetic (twos complement, one's complement, or sign-magnitude). The FIR tissue thus is versatile.
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2021
In this chapter we learn about adaptive filters that change their weights during work, from sample to sample. The filters use different adaptation equations, resulting from choice of different cost functions that are minimized during signal processing.
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In this chapter we learn about adaptive filters that change their weights during work, from sample to sample. The filters use different adaptation equations, resulting from choice of different cost functions that are minimized during signal processing.
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Sharpened raised-cosine FIR filters
2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), 2018Shaping of transition bands in the ideal frequency response allows the analytic design of least-squares FIR filters with a direct control of the transition-band edges. The basic least-squares approximation is obtained by the Fourier series method. In this paper, we use it to develop a straightforward method for the design of steep roll-off FIR filters.
Molnar, Goran +2 more
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1992
High performance FIR filters have applications in several video processing [Privat86] and digital communications systems [Samueli90]. While compiler tools exist for low sample rate applications such as audio and telecommunication, techniques for automating the design of high sample rate FIR filters have only recently been emerging [Hartley89, Reutz89].
Paul Yang, Rajeev Jain
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High performance FIR filters have applications in several video processing [Privat86] and digital communications systems [Samueli90]. While compiler tools exist for low sample rate applications such as audio and telecommunication, techniques for automating the design of high sample rate FIR filters have only recently been emerging [Hartley89, Reutz89].
Paul Yang, Rajeev Jain
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