Results 231 to 240 of about 98,696 (254)

XOR-Satisfiability Set Membership Filters

2018
Set membership filters are used as a primary test for whether large sets contain given elements. The most common such filter is the Bloom filter [6]. Most pertinent to this article is the recently introduced Satisfiability (SAT) filter [31]. This article proposes the XOR-Satisfiability filter, a variant of the SAT filter based on random k-XORSAT ...
Sean A. Weaver, Hannah J. Roberts, Michael J. Smith   +2 more
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Noisy Bloom Filters for Multi-Set Membership Testing

ACM SIGMETRICS Performance Evaluation Review, 2016
This paper is on designing a compact data structure for multi-set membership testing allowing fast set querying. Multi-set membership testing is a fundamental operation for computing systems and networking applications. Most existing schemes for multi-set membership testing are built upon Bloom filter, and fall short in either storage space cost or ...
Haipeng Dai, Yuankun Zhong, Alex X. Liu, Wei Wang, Meng Li   +4 more
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Set-membership recursive least-squares adaptive filtering algorithm

2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012
A new set-membership adaptive filtering algorithm is developed based on the exponentially-weighted RLS algorithm with a time-varying forgetting factor that is optimized at each iteration by imposing a bounded-magnitude constraint on the a posteriori filter output error.
Reza Arablouei, Kutluyil Dogancay
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Robust set-membership filtering algorithms against impulsive noise

2014 22nd Signal Processing and Communications Applications Conference (SIU), 2014
In this paper, we propose robust set-membership filtering algorithms against impulsive noise. Firstly, we introduce set-membership normalized least absolute difference algorithm (SM-NLAD). This algorithm provides robustness against impulsive noise through pricing the absolute error instead of the square. Then, in order to achieve comparable convergence
Muhammed O. Sayin, N. Denizcan Vanli, Suleyman S. Kozat   +2 more
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Pipelined set-membership approach to adaptive Volterra filtering

Signal Processing, 2016
Due to the high computational complexity required by Volterra filter, some of its practical implementations consider pipelined adaptive Volterra filter architecture with two layers structure. However, its main challenges are the poor robustness against impulsive noise, slow convergence and high computational complexity for long memory high order ...
Sheng Zhang, Jiashu Zhang, Yanjie Pang
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Kernelized Set-Membership Approach to Nonlinear Adaptive Filtering

Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005., 2006
In linear filtering, the set-membership normalized least mean squares (SM-NLMS) algorithm has been shown to exhibit desirable features of selective update and optimized variable step size. In this paper, a kernel approach to the SM-NLMS algorithm is presented that makes it feasible to address nonlinear problems. An online greedy approximation technique
null Amaresh Malipatil, null Yih-Fang Huang, null Srinivas Andra, null Kristin Bennett   +3 more
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Particle Filters for Set-membership State Estimation

2006 SICE-ICASE International Joint Conference, 2006
This paper proposes a new way of using particle filters for set-membership state estimation problems. For nonlinear state estimation problems, stochastic particle filters have been proposed which maintain a large number of solution candidates by using Monte-Carlo simulation. Set-membership approach for state estimation is an alternative method that is,
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Frequency-domain adaptive filtering -a set-membership approach

The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003, 2004
Frequency-domain adaptive filtering has been shown to have the advantage of low complexity compared to its time-domain counterpart In this paper, a frequency-domain Set-Membership Normalized Least-Mean-Square (F-SM-NLMS) algorithm is derived, and shown to have better performance (in terms of convergence and bit error rate (BER)) and less updates than ...
null Li Guo, A. Ekpenyong, null Yih-Fang Huang   +2 more
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Set-Membership Adaptive Filtering

2003
Based on a bounded-error assumption, set-membership adaptive filtering (SMAF) offers a viable alternative to traditional adaptive filtering techniques that are aimed to minimize an ensemble (or a time) average of the errors. This chapter presents an overview of the principles of SMAF, its features, and some applications. Highlighting the novel features
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Set-Membership Adaptive Filtering

2019
The families of adaptive filtering algorithms introduced so far present a trade-off between the speed of convergence and the misadjustment after the transient. These characteristics are easily observable in stationary environments. In general fast-converging algorithms tend to be very dynamic, a feature not necessarily advantageous after convergence in
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