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IEEE Workshop on Signal Processing Systems (SIPS 02)

作者： Albu, F Kadlec, J Coleman, N Fagan, A UCD DSP Grp Dublin 4 Ireland

ISBN: (纸本)0780375874

In this paper we propose a new stable Fast Affine projection algorithm based on Gauss-Seidel iterations (GSFAP). We investigate its implementation using the logarithmic number system (LNS) and compare it with two other fast affine projection (FAP) algorithms. Simplified and multi-input GSFAP versions are also proposed. We show that the algorithm is only marginally more complex than NLMS and simpler than other FAP algorithms. Its application for acoustic echo cancellation is also investigated.

关键词： Adaptive filters Convergence Digital signal processing Echo cancellers Financial advantage program Gaussian processes Iterative algorithms Noise cancellation projection algorithms Resonance light scattering

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A Modified Adaptive Step-size Affine projection Algorithm based on QR-decomposition

A Modified Adaptive Step-size Affine Projection Algorithm ba...

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International Electrical Engineering Congress (iEECON)

作者： Sitjongsataporn, Suchada Nurarak, Piyaporn Mahanakorn Univ Technol Fac Engn Ctr Elect Syst Design & Signal Proc CESdSP 140 Cheumsamphan Rd Bangkok 10530 Thailand Sukhothai Thammathirat Open Univ Sch Sci & Technol 9-9 Chaengwattana Rd Nonthaburi 11120 Thailand

ISBN: (纸本)9781509046669

In this paper, we present an adaptive step-size affine projection algorithm with QR-decomposition for single-carrier frequency-domain equalisation systems. The QR-decomposition mechanism is introduced how to derive the modified inverse autocorrelation matrix based on inverse square-root approach to reduce the complexity. The adaptive step-size mechanism is presented with the increasing prediction estimate error vector to improve the fast convergence. Simulation results depict that the proposed algorithm can indicate clearly the superior performance compared with the conventional affine projection algorithm.

关键词： projection algorithms Correlation Frequency-domain analysis Steady-state Prediction algorithms Signal processing algorithms Time-domain analysis

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A Variable Step Size Affine projection Algorithm Based on the Principle of Orthogonality 59

A Variable Step Size Affine Projection Algorithm Based on th...

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59th IEEE International Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Naveed, Khuram Ali, Bakhtiar Akhtar, Muhammad Tahir COMSATS Inst Informat Technol Dept Elect Engn Pk Rd Islamabad 44000 Pakistan

ISBN: (纸本)9781509009169

The orthogonality principle states that as an adaptive filter approaches to the Weiner solution and error approaches to its minimum value, the correlation between error and input signal approaches to zero. This fact has been exploited in the proposed scheme for the minimizing mean square deviation (MSD) for the tap weights and its estimated value at each iteration. Essentially, this paper proposes a variable step-size (VSS) affine projection algorithm (APA) where step-size is varied on the basis of instantaneous cross correlation of error and input signal along with the error power and estimated noise variance. The main advantage of the proposed method is that it does not need an initial tuning parameter of fixed step-size to kick-off VSS calculations unlike most VSS APAs. The simulation results show that the proposed algorithm has fast convergence and small steady state error than the existing VSS APAs.

关键词： orthogonality step size input signal Volatile suspended solids projection algorithms Cross correlation adaptive filters Affine In-law minimum value

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SQP-based projection SPSA Algorithm for Stochastic Optimization with Inequality Constraints

SQP-based Projection SPSA Algorithm for Stochastic Optimizat...

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American Control Conference (ACC)

作者： Shi, Jiahao Spall, James C. Johns Hopkins Univ Dept Appl Math & Stat Baltimore MD 21218 USA Johns Hopkins Univ Appl Phys Lab Baltimore MD 21218 USA JHU Dept Appl Math & Stat Baltimore MD USA

ISBN: (纸本)9781665441971

projection and penalty function simultaneous perturbation stochastic approximation (SPSA) algorithms are two commonly used methods in stochastic optimization problems under inequality constraints where no direct gradient of the loss function is available. However, both methods have potential shortcomings. We propose an algorithm that uses sequential quadratic programming (SQP) to estimate the projection operator under potentially complex explicit inequality constraints. This algorithm has some advantages over the penalty function method in practice. We prove the convergence of the proposed SQP-based projection SPSA algorithm and make a comparison with the penalty function method in a numerical example to show its superiority.

关键词： Perturbation methods Approximation algorithms Robustness Quadratic programming Noise measurement projection algorithms Optimization

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DOUBLE PSEUDO AFFINE projection ALGORITHM FOR SPEECH ENHANCEMENT AND ACOUSTIC NOISE REDUCTION

DOUBLE PSEUDO AFFINE PROJECTION ALGORITHM FOR SPEECH ENHANCE...

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20th European Signal Processing Conference (EUSIPCO)

作者： Djendi, Mohamed Scalart, Pascal Univ Saad Dahlab Signal Proc & Image Lab LATSI Route SoumaaBP 270 Blida 09000 Algeria ENSSAT IRISA CAIRN Lannion France

ISBN: (纸本)9781467310680

In this paper, we consider the speech enhancement problem in a moving car through a blind source separation scheme involving two closely spaced microphones. We propose the use of a new double pseudo affine projection DPAP algorithm to estimate and suppress coherent noise components from speech. The proposed DPAP algorithm is applied to the forward blind source separation FBSS structure and combined with a new whitening scheme of its two inputs. In order to avoid the use of a manual voice activity detector in the new DPAP algorithm, we have adapted then applied the technique proposed in [1] to the FBSS structure and for the new proposed algorithm. The simulation results show that the DPAP algorithm, when controlled by the proposed technique is able to fully cancel the correlated noise components from speech.

关键词： Speech enhancement Noise reduction projection algorithms Voice activity detectors Pseudo Affine In-law Acoustic noise Blind source separation Speech

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A Proportionate Affine projection Algorithm Using Dichotomous Coordinate Descent Iterations

A Proportionate Affine Projection Algorithm Using Dichotomou...

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10th International Symposium on Signals, Circuits and Systems (ISSCS)

作者： Stanciu, Cristian Anghel, Cristian Paleologu, Constantin Benesty, Jacob Albu, Felix Ciochina, Silviu Univ Politehn Bucuresti Telecommun Dept Bucharest Romania Univ Quebec INRS EMT Montreal PQ Canada

ISBN: (纸本)9781457702013

This paper proposes a low-complexity proportionate affine projection algorithm (PAPA) suitable for echo cancellation. It is known that proportionate-type algorithms exploit the sparseness character of the echo path in order to achieve faster convergence and tracking as compared to the conventional algorithms. The proposed algorithm results as a combination between a recently proposed "memory"-PAPA (MPAPA) and an iterative technique for solving the matrix inversion problem, i.e., the dichotomous coordinate descent (DCD) with a leading element. Simulations performed in the context of network echo cancellation indicate the good performance of the proposed algorithm.

关键词： Complexity theory Context Convergence Echo cancellers History projection algorithms Speech convergence dichotomous coordinate descent Iterations echo path echo suppression iterative methods low-complexity proportionate affine projection algorithm matrix inversion matrix inversion problem memory proportionate affine projection algorithm network echo cancellation tracking

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A Tensorial Affine projection Algorithm 15

A Tensorial Affine Projection Algorithm

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15th International Symposium on Signals, Circuits and Systems, ISSCS 2021

作者： Dogariu, Laura-Maria Elisei-Iliescu, Camelia Paleologu, Constantin Benesty, Jacob Ciochina, Silviu University Politehnica of Bucharest Department of Telecommunications Romania University of Quebec INRS-EMT Montreal Canada

ISBN: (纸本)9781665449427

The affine projection algorithm (APA) represents a popular choice in system identification scenarios, especially with correlated input signals. In this paper, we address the multilinear identification problem, in the framework of multiple-input single-output systems. The main challenge consists of a large parameter space, which can be efficiently reshaped into a tensorial form. The proposed tensor-based APA is tailored for the identification of such multilinear forms, since it combines the solutions provided by the individual (shorter) filters. Simulation results indicate the appealing performance of this algorithm. © 2021 IEEE.

关键词： Circuits and systems Simulation MISO communication Filtering algorithms Benchmark testing System identification projection algorithms

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Asymptotically Efficient Recursive Identification of FIR Systems With Binary-Valued Observations

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2021年第5期51卷 2687-2700页

作者： Zhang, Hang Wang, Ting Zhao, Yanlong Chinese Acad Sci Acad Math & Syst Sci Key Lab Syst & Control Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Math Sci Beijing 100049 Peoples R China

This paper considers the identification problem of finite impulse response (FIR) systems with binary-valued observations under the assumption of fixed threshold and bounded persistently excitations. A recursive projection algorithm is constructed to estimate the unknown parameter. For first-order FIR systems, the convergence properties of the algorithm are analyzed theoretically. With mild conditions on the weight coefficients in the parameter update, the algorithm is proved to be convergent in mean square and the convergence rate can be the reciprocal of the number of observations, which has the same order as the optimal estimation when the system output is exactly known. Furthermore, it is also shown that the Cramer-Rao (CR) lower bound is achieved asymptotically with proper weight coefficients, which indicates that the algorithm is optimal in the sense of asymptotic efficiency. Some numerical examples are simulated to demonstrate the effectiveness of the proposed algorithm in both first-order and high-order FIR systems.

关键词： Finite impulse response filters Convergence Approximation algorithms Adaptive control projection algorithms Estimation Control systems Asymptotic efficiency binary-valued observations convergence Cramé r– Rao (CR) lower bound identification

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Imaging for a Forward Scanning Automotive Synthetic Aperture Radar

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2019年第3期55卷 1420-1434页

作者： Gishkori, Shahzad Daniel, Liam Gashinova, Marina Mulgrew, Bernard Univ Edinburgh Sch Engn Inst Digital Commun Edinburgh EH8 9YL Midlothian Scotland Univ Birmingham Microwave Integrated Syst Lab Sch Elect Elect & Syst Engn Birmingham B15 2TT W Midlands England

In this paper, we propose a forward scanning synthetic aperture radar methodology for a forward-looking automotive (low-terahertz) radar, which combines scene scanning with synthetic aperture processing, resulting in enhanced angular resolution and improved imaging. We propose two algorithms, first, a modified back-projection (BP) algorithm and, second, a compressed sensing-based BP algorithm. We suggest techniques to reduce computational complexity of the proposed algorithms. Results of simulation and real-data experiments corroborate the validity of our proposed methodology and algorithms.

关键词： Radar imaging Synthetic aperture radar Apertures Imaging Radar antennas projection algorithms

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Adaptive Vector Control of an Induction Motor on the Basis of the Method of Recurrent Objective Inequalities

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AUTOMATION AND REMOTE CONTROL 2010年第9期71卷 1849-1863页

作者： Bondarko, V. A. St Petersburg State Univ St Petersburg Russia

The problem is considered for control of an electromagnetic moment of the induction motor with a squirrel-cage rotor without the measurement of its rotational speed. By means of the principle of vector control, this problem reduces to developing an adaptive observer of values of the vector of the rotor magnetic-flux linkage. The method of recurrent objective inequalities (ROIs) is used, which enables one to reduce adaptation problems to counting systems of inequalities relative to the vector of the parameters estimated. For the control problem under consideration, these inequalities prove to be nonconvex, which makes it impossible to use directly the projection algorithms developed in the framework of the method of ROIs. In this connection, the common method for the stepwise reduction of the dimension of the nonlinear portion of inequalities is suggested in this work. On condition that the processes of a closed system display a certain natural property of nondegeneracy, this method permits reducing nonconvex inequalities to convex ones and ensures the achievement of the control aim on completion of the transient processes.

关键词： Basis rotational speed induction motors squirrel-cage rotor projection algorithms inequalities transient processes

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