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Adaptive sign algorithm for graph signal processing

signAL PROCESSING 2022年 200卷

作者： Yan, Yi Kuruoglu, Ercan E. Altinkaya, Mustafa A. Tsinghua Univ Tsinghua Berkeley Shenzhen Inst Shenzhen Peoples R China Izmir Inst Technol Izmir Turkey

Efficient and robust online processing techniques for irregularly structured data are crucial in the current era of data abundance. In this paper, we propose a graph/network version of the classical adaptive sign algorithm for online graph signal estimation under impulsive noise. The recently introduced graph adaptive least mean squares algorithm is unstable under non-Gaussian impulsive noise and has high computational complexity. The Graph-sign algorithm proposed in this work is based on the minimum dispersion criterion and therefore impulsive noise does not hinder its estimation quality. Unlike the recently proposed graph adaptive least mean pth power algorithm, our Graph-sign algorithm can operate without prior knowledge of the noise distribution. The proposed Graph-sign algorithm has a faster run time because of its low computational complexity compared to the existing adaptive graph signal processing algorithms. Experimenting on steady-state and time-varying graph signals estimation utilizing spectral properties of bandlimitedness and sampling, the Graph-sign algorithm demonstrates fast, stable, and robust graph signal estimation performance under impulsive noise modeled by alpha stable, Cauchy, Student's t, or Laplace distributions. Keywords: Graph signal processing sign algorithm Adaptive filter Impulsive noise Non-Gaussian noise (C) 2022 Elsevier B.V. All rights reserved.

关键词： Graph signal processing sign algorithm Adaptive filter Impulsive noise Non-Gaussian noise

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A VARIABLE STEP-SIZE NORMALIZED sign algorithm FOR ACOUSTIC ECHO CANCELATION

A VARIABLE STEP-SIZE NORMALIZED SIGN ALGORITHM FOR ACOUSTIC ...

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IEEE International Conference on Acoustics, Speech, and signal Processing

作者： Tiange Shao Yahong Rosa Zheng Jacob Benesty Department of Electrical & Computer Engineering Missouri University of Science and Technology Rolla MO USA INRS-EMT University of Quebec Montreal QC H5A 1K6 Canada

ISBN: (纸本)9781424442959;9781424442966

A variable step size normalized sign algorithm (VSS-NSA) is proposed, for acoustic echo cancelation, which adjusts its step size automatically by matching the L_(1) norm of the a posteriori error to that of the background noise plus near-end signal. Simulation results show that the new algorithm combined with double-talk detection outperforms the dual sign algorithm (DSA) and the normalized triple-state sign algorithm (NTSSA) in terms of convergence rate and stability.

关键词： echo canceler double talk robust adaptive filter variable step size sign algorithm step size Echo cancellers signature algorithm ECHO algorithms BACKGROUND NOISE WWOX gene

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Modified sign-algorithm for Adaptive Laguerre Equalizer in DS-CDMA Communication Systems

Modified Sign-Algorithm for Adaptive Laguerre Equalizer in D...

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IEEE Region 10 Conference (TENCON)

作者： Benjangkaprasert, C. Sirithummachak, P. Lertwatechakul, M. King Mongkuts Inst Technol Ladkrabang Fac Engn Bangkok 10520 Thailand

ISBN: (纸本)9781479940752

This paper aims to improve the performance of DS-CDMA receiver by using a new adaptive equalizer with a modified sign-algorithm based on Laguerre filter structure. The proposed algorithm is modified version of the conventional sign-regressor algorithm for a Laguerre filter. By the simulation result, the BER performance of the proposed algorithm is shown to be better than the classical sign-regressor (SR) algorithm and the recursive least square (RLS) algorithm in multipath channel. This equalizer not only reduce the effected of ISI, MAI and the implementation cost, but also minimizes the computational complexity and supports the long impulse response system.

关键词： DS-CDMA system Laguerre equalizer RLS algorithm sign algorithm

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Steady-state performance for the sign normalized algorithm based on Hammerstein spline adaptive filtering 8

Steady-state performance for the sign normalized algorithm b...

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8th International Conference on Control, Automation and Information Sciences (ICCAIS)

作者： Liu, Chang Zhang, Zhi Tang, Xiao Dongguan Univ Technol Sch Elect Engn & Intelligence Dongguan Peoples R China

ISBN: (纸本)9781728123110

In this paper, by combining the Hammerstein spline adaptive filtering model with the L-1 norm minimization criterion, we present a new sign adaptive normalized least mean square algorithm based on Hammerstein spline adaptive filter (HSAF-SNLMS). Meanwhile, the steady-state performance of the proposed algorithm is extensively investigated by application of the energy conservation relation and Price theorem in the case of non-Gaussian noise. Simulation results under the background of the identification of the Hammerstein spline nonlinear system are in good agreement with the theoretical calculations.

关键词： Hammerstein spline adaptive filter sign algorithm mean square error steady-state

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Bias mitigating in a sign-algorithm for a constrainted adaptive IIR notch filter 7

Bias mitigating in a sign-algorithm for a constrainted adapt...

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7th International Electrical Engineering Congress (iEECON)

作者： Punchalard, Rachu Mahanakorn Univ Technol Fac Engn Dept Telecommun Engn Bangkok 10530 Thailand

ISBN: (纸本)9781728107295

sign-algorithm (SA) for a constrainted adaptive IIR notch filter (ANF) is very attractive because it is simple to implement. Although the slow convergence speed and biased estimate are two main drawbacks of SA, in some applications, it provides satisfactory results. In this work we propose the bias removal technique to mitigate the biased estimate of SA. Computer simulation has been drawn to show the performance of the proposed technique.

关键词： sign algorithm adaptive iir notch filter

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Performance Analysis of Adaptive Step-Size sign-Newton algorithm 8

Performance Analysis of Adaptive Step-Size Sign-Newton Algor...

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International Conference on Advanced Technologies for communications (ATC)

作者： Koike, Shin'ichi Tokyo Japan

ISBN: (纸本)9781467383745

This paper first proposes to combine the sign algorithm (SA) with an estimate of the inverse covariance matrix of the filter input calculated using the Newton's method. We further propose a new adaptive step-size (ASS) control algorithm to improve the filter convergence speed, yielding an adaptation algorithm named Adaptive Step-Size sign-Newton (ASS-sign-Newton) algorithm. A performance analysis of the ASS-sign-Newton algorithm is developed for calculating theoretical convergence behavior. In experiments with some examples, we demonstrate effectiveness of the proposed ASS-sign-Newton algorithm in realizing faster convergence, while preserving the robustness against impulsive observation noise. The calculated theoretical convergence curves are generally in good agreement with the simulated ones which shows that the analysis is valid.

关键词： adaptive filter sign algorithm Newton's method impulse noise fast convergence robust filtering

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Improving sign-algorithm convergence rate using natural gradient for lossless audio compression

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EURASIP JOURNAL ON AUDIO SPEECH AND MUSIC PROCESSING 2022年第1期2022卷 12-12页

作者： Mineo, Taiyo Shouno, Hayaru Univ Electrocommun Grad Sch Informat & Engn 1-5-1 Chofugaoka Chofu Tokyo 1828585 Japan

In lossless audio compression, the predictive residuals must remain sparse when entropy coding is applied. The sign algorithm (SA) is a conventional method for minimizing the magnitudes of residuals;however, this approach yields poor convergence performance compared with the least mean square algorithm. To overcome this convergence performance degradation, we propose novel adaptive algorithms based on a natural gradient: the natural-gradient sign algorithm (NGSA) and normalized NGSA. We also propose an efficient natural-gradient update method based on the AR(p) model, which requires O(p) multiply-add operations at every adaptation step. In experiments conducted using toy and real music data, the proposed algorithms achieve superior convergence performance to the SA. Furthermore, we propose a novel lossless audio codec based on the NGSA, called the natural-gradient autoregressive unlossy audio compressor (NARU), which is open-source and implemented in C. In a comparative experiment with existing, well-known codecs, NARU exhibits superior compression performance. These results suggest that the proposed methods are appropriate for practical applications.

关键词： Adaptive algorithm Autoregressive model Lossless audio codec Natural gradient method sign algorithm

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Adaptive centre-frequency bandpass state-space digital filters and their l2-sensitivity analysis

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SICE JOURNAL OF CONTROL MEASUREMENT AND SYSTEM INTEGRATION 2025年第1期18卷

作者： Hinamoto, Yoichi Doi, Akimitsu Natl Inst Technol Kagawa Coll Dept Elect & Comp Engn Takamatsu Japan Hiroshima Inst Technol Dept Comp Sci 2-1-1 MiyakeSaeki Ku Hiroshima 7315193 Japan

This paper explores an adaptive centre-frequency bandpass state-space digital filter by expanding a sign algorithm into the gradient-based method. To this end, a simple method for deriving a bandpass state-space digital filter with tuneable centre-frequency from a prototype low-pass filter and low-pass/bandpass transformation is presented. An adaptive iterative algorithm is then developed by expanding a sign algorithm into the gradient-based method. Also, l(2)-sensitivities for the bandpass state-space digital filter with tuneable centre-frequency are analysed where an l(2)-sensitivity measure for evaluating the whole l(2)-sensitivities is deduced. Numerical experiments are included to demonstrate the validity and effectiveness of the adaptive centre-frequency bandpass state-space digital filter and the l(2)-sensitivity analysis.

关键词： Adaptive centre-frequency bandpass digital filter gradient-based method l(2)-sensitivity analysis sign algorithm state-space approach

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Diffusion sign Subband Adaptive Filtering algorithm with Enlarged Cooperation and Its Variant

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CIRCUITS SYSTEMS AND signAL PROCESSING 2017年第4期36卷 1714-1724页

作者： Shi, Juan Ni, Jingen Soochow Univ Sch Elect & Informat Engn Suzhou 215006 Peoples R China

The recently proposed diffusion sign subband adaptive filtering (DSSAF) algorithm is more robust than most of mean-square error minimization criterion-based diffusion distributed estimation algorithms in an impulsive interference environment. To enhance its convergence rate and steady-state misalignment, this paper proposes a DSSAF algorithm with enlarged cooperation (DSSAF-EC). The DSSAF-EC algorithm exchanges not only the weight information but also measurements within individual neighborhoods. Moreover, a variant of the DSSAF-EC algorithm, called the proportionate DSSAF-EC (PDSSAF-EC) algorithm, is presented. It incorporates an adaptive gain matrix into the DSSAF-EC algorithm to proportionately adapt the weight vectors of agents. Simulation results verify that both the DSSAF-EC and PDSSAF-EC algorithms are robust against impulsive interference and that the PDSSAF-EC algorithm can obtain faster convergence rate than the DSSAF-EC algorithm in estimating a sparse unknown weight vector.

关键词： Distributed estimation Enlarged cooperation Proportionate adaption sign algorithm

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Variable step-size sign natural gradient algorithm for sequential blind source separation

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IEEE signAL PROCESSING LETTERS 2005年第8期12卷 589-592页

作者： Yuan, LX Wang, WW Chambers, JA Cradiff Univ Ctr Digital Signal Proc Cardiff Sch Engn Cardiff CF24 0YF Wales

A novel variable step-size sign natural gradient algorithm (VS-S-NGA) for online blind separation of independent sources is presented. A sign operator for the adaptation of the separation model is obtained from the derivation of a generalized dynamic separation model. A variable step size is also derived to better match the dynamics of the input signals and unmixing matrix. The proposed sign algorithm is appealing in practice due to its computational simplicity. Experimental results verify the superior convergence performance over conventional NGA in both stationary and nonstationary environments.

关键词： adaptive step size natural gradient sequential blind source separation (BSS) sign algorithm

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