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检索条件"主题词=Projection algorithms"

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Regularization of the improved proportionate affine projection algorithm

Regularization of the improved proportionate affine projecti...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Constantin Paleologu Jacob Benesty Felix Albu University Politehnica of Bucharest Romania INRS-EMT University of Quebec Montreal Canada

In sparse adaptive filters, the adaptation gain is “proportionately” redistributed among all the coefficients, emphasizing the large ones in order to speed up their convergence. The improved proportionate affine projection algorithm (IPAPA) is a very attractive choice for echo cancellation, since it combines the good convergence features of the affine projection algorithm (APA) and the gain factors of the improved proportionate normalized least-mean-square (IPNLMS) algorithm. Similar to the APA, a matrix inversion is required within the IPAPA. For practical reasons, the matrix needs to be regularized before inversion, i.e., a positive constant is added to the elements of its main diagonal. In this paper, we propose a formula for choosing the regularization parameter of the IPAPA, aiming at attenuating the effects of the noise in the adaptive filter estimate. Simulation results indicate the validity of this approach in both network and acoustic echo cancellation scenarios.

关键词： Echo cancellers Noise Vectors projection algorithms Convergence Adaptation models

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Proposed affine projection algorithm for adaptive equalization over shallow water acoustic channel

Proposed affine projection algorithm for adaptive equalizati...

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IEEE Symposium on Wireless Technology and Applications (ISWTA)

作者： Masoumeh Soflaei Paeiz Azmi Faculty of Electrical and Computer Engineering Tarbiat Moalem University Tehran Iran

Underwater acoustic communications especially over shallow water channels suffer from multipath spread that causes inter-symbol interference (ISI). One of the best ways for overcoming ISI is to use adaptive equalizers. In addition to convergence rate and steady-state error, computational complexity influences adaptive equalizers performance. In this paper, we apply least mean fourth-power of two quantizer (LMFPTQ) also we suggest proposed affine projection algorithm (Proposed APA) and proposed normalized least mean fourth (Proposed NLMF) as new algorithms with lower steady-state error and faster convergence rate in comparison with LMF-PTQ, for equalizing underwater acoustic communications. We apply experimental data from Persian Gulf for examining and showing that the proposed method provides a good trade-off between convergence rate and computational complexity over shallow water channels.

关键词： Computational complexity Convergence Underwater acoustics Noise Adaptive equalizers projection algorithms Steady-state

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AN EFFICIENT KERNEL ADAPTIVE FILTERING ALGORITHM USING HYPERPLANE projection ALONG AFFINE SUBSPACE

AN EFFICIENT KERNEL ADAPTIVE FILTERING ALGORITHM USING HYPER...

引用

European Signal Processing Conference

作者： Masahiro Yukawa Ryu-ichiro Ishii Department of Electrical and Electronic Engineering Niigata University

ISBN: (纸本)9781467310680

We propose a novel kernel adaptive filtering algorithm that selectively updates a few coefficients at each iteration by projecting the current filter onto the zero instantaneous-error hyper-plane along a certain time-dependent affine subspace. Coherence is exploited for selecting the coefficients to be updated as well as for measuring the novelty of new data. The proposed algorithm is a natural extension of the normalized kernel least mean squares algorithm operating iterative hyper-plane projections in a reproducing kernel Hilbert space. The proposed algorithm enjoys low computational complexity. Numerical examples indicate high potential of the proposed algorithm.

关键词： Kernel adaptive filter projection algorithms Reproducing kernel Hilbert space Normalized kernel least mean square algorithm Seeds Hilbert space Least mean square algorithm algorithms Filtration iterative methods high potential projection

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An affine projection algorithm based DFE with set-membership filtering

An affine projection algorithm based DFE with set-membership...

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International Conference on Computers and Devices for Communication (CODEC)

作者： Ramesh Chandra Mishra Ratnajit Bhattacharjee Abhijit Mitra Department of EEE Indian Institute of Technology Guwahati Assam India Department of ECE Sir J. C. Bose School of Engineering West Bengal India

ISBN: (纸本)9781467326193

A channel equalization technique based on the affine projection algorithms (APA) with set-membership (SM) filtering for updating filters of a decision feedback equalizer (DFE) is proposed for time-varying wireless channels. The performance of the proposed approach is analyzed through simulations. It is shown in the results that this scheme offers advantages of having substantial fewer number of weight updating operations at moderate SNR with almost similar convergence as normal APA based equalizer. The introduced equalizer converges faster with a marginal increase in complexity than the set-membership normalized least mean square (NLMS) algorithm based equalizer.

关键词： Affine projection algorithm Decision feedback equalizer Normalized least mean square algorithm Set-membership decision feedback equalisers projection algorithms Least mean square algorithm Equalizers HELIOS DEVICES Filtration ALASKA POWER ADMINISTRATION based

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MIMO channel equalization using set-membership affine projection algorithm

MIMO channel equalization using set-membership affine projec...

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IEEE Region 10 International Conference TENCON

作者： R. C. Mishra R. Bhattacharjee A. Mitra Department of EEE Indian Institute of Technology Guwahati Assam India Department of ECE Sir J. C. Bose School of Engg West Bengal India

ISBN: (纸本)9781467348232

A multiple-input multiple-output (MIMO) channel equalization scheme for time-varying wireless channels is proposed. The proposed equalization technique uses set-membership affine projection (SM-AP) algorithm for updating filter weights of a decision feedback equalizer (DFE). The performance of the proposed scheme is investigated through simulations using wireless channel models recommended by International Telecommunication Union for Radiocommunication Sector (ITU-R). The results show that the proposed scheme achieves a fast convergence speed. The convergence performance of this scheme has also been studied for different projection order and compared with the convergence performance of set-membership normalized least mean-square (SM-NLMS) algorithm based MIMO-DFE. The proposed equalizer has low complexity and works well even in frequency-selective channels.

关键词： MIMO Decision feedback equalizers Convergence Vectors projection algorithms Upper bound Delay

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Steady-state performance of multichannel affine projection algorithms for active noise control

Steady-state performance of multichannel affine projection a...

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European Signal Processing Conference (EUSIPCO)

作者： Miguel Ferrer Alberto Gonzalez Maria de Diego Gema Piñero Universitat Politecnica de Valencia Valencia Valenciana ES Institute of Telecommunications and Multimedia Applications (iTEAM) Universidad Politecnica de Valencia

ISBN: (纸本)9782839904506

In the field of adaptive filtering, it is well known that affine projection (AP) algorithms lead to a good tradeoff between convergence speed and computational load. For multichannel sound control, some computationally efficient AP (fast AP) algorithms have been recently proposed. This paper analyzes the steady-state mean square error of two efficient affine projection algorithms (representative of the different approaches) for multichannel active noise control (ANC) applications based on a different filtering-x scheme: the modified filtered-x affine projection (MFXAP) algorithm (with the modified filtered-x structure embedded) and the filtered-x affine projection (FXAP) algorithm (based on the conventional filtered-x structure). This study depends on energy conservation arguments and does not require a specific signal distribution. The theoretical models derived allow to accurately predict the steady-state performance of the algorithms considered. Simulation results obtained in practical single-channel and multichannel ANC systems validate the analysis and the derived expressions.

关键词： Vectors Prediction algorithms Steady-state projection algorithms Noise Adaptation models Convergence

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Class-dependent locality preserving projections for multimodal scenarios

Class-dependent locality preserving projections for multimod...

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International Conference on Tools with Artificial Intelligence

作者： Elias R. Silva, Jr. George D. C. Cavalcanti Tsang Ing Ren Center for Informatics Federal University of Pernambuco

ISBN: (纸本)9781479902279

This paper proposes a method for linear feature extraction called Class-dependent Locality Preserving projections. It is a supervised extension of the Locality Preserving projection algorithm and it aims to work in scenarios with within-class multimodality, which are those scenarios where the scattering of the patterns follows more than one modal distribution. Differently from the classical feature extraction techniques that build their solutions based on the whole dataset, the Class-dependent Locality Preserving projections looks at each class separately, building a specific projection for each class. The proposed technique analyses a query pattern based on the output of each class and chooses the class that better fit the pattern. The experimental study shows that the Class-dependent Locality Preserving projections is a feature extraction technique for general purposes, however, it is particularly well succeed when applied to within-class multimodal scenarios.

关键词： Feature extraction projection projection algorithms Scattering

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Distributed strongly convex optimization

Distributed strongly convex optimization

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Annual Allerton Conference on Communication, Control, and Computing

作者： Konstantinos I. Tsianos Michael G. Rabbat Department of Electrical and Computer Engineering McGill University Montreal Quebec Canada

A lot of effort has been invested into characterizing the convergence rates of gradient based algorithms for non-linear convex optimization. Recently, motivated by large datasets and problems in machine learning, the interest has shifted towards distributed optimization. In this work we present a distributed algorithm for strongly convex constrained optimization. Each node in a network of n computers converges to the optimum of a strongly convex, L-Lipchitz continuous, separable objective at a rate O(log (√n T)/T) where T is the number of iterations. This rate is achieved in the online setting where the data is revealed one at a time to the nodes, and in the batch setting where each node has access to its full local dataset from the start. The same convergence rate is achieved in expectation when the subgradients used at each node are corrupted with additive zero-mean noise.

关键词： Convex functions Convergence Cost function Program processors Loss measurement projection algorithms

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Electromyogram (EMG) Feature Reduction Using Mutual Components Analysis for Multifunction Prosthetic Fingers Control

Electromyogram (EMG) Feature Reduction Using Mutual Componen...

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International Conference on Control, Automation, Robotics and Vision

作者： Rami N. Khushaba Sarath Kodagoda School of Electrical Mechanical and Mechatronics Systems University of Technology Sydney (UTS)

ISBN: (纸本)9781467318716

Surface Electromyogram (EMG) signals are usually utilized as a control source for multifunction powered prostheses. A challenge that arises with the current demands of such prostheses is the ability to accurately control a large number of individual and combined fingers movements and to do so in a computationally efficient manner. As a response to such a challenge, we present a combined feature selection and projection algorithm, denoted as Mutual Components Analysis (MCA). The proposed MCA algorithm extends the well-known Principal Components Analysis (PCA) by pruning the noisy and redundant features before projecting the data. To implement the feature selection step, the mutual information concept is utilized to implement a new information gain evaluation function. The performance and significance of the proposed MCA is demonstrated on EMG datasets collected for the purpose of this research from eight subjects with eight electrodes attached on their forearm. Fifteen classes of fingers movements where considered in this paper with MCA achieving >95% accuracy on average across all subjects.

关键词： Electromyogram Feature extraction system buses compensatory amounts Maximum credible accidents controlled source Fingers component analysis Prosthesis projection algorithms

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Guaranteed Delay Margins for Adaptive Control of Scalar Plants

Guaranteed Delay Margins for Adaptive Control of Scalar Plan...

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IEEE Annual Conference on Decision and Control

作者： Megumi Matsutani Anuradha Annaswamy Eugene Lavretsky Department of Aeronautics and Astronautics Massachusetts Institute of Technology Department of Mechanical Engineering Massachusetts Institute of Technology Boeing company Huntington Beach

ISBN: (纸本)9781467320658

Robust adaptive control of scalar plants in the presence of time-delays is established in this paper. It is shown that a standard adaptive controller with a projection algorithm ensures global boundedness of the overall adaptive system for a range of non-zero delays. The upper bound of such delays, i.e. the delay margin, is explicitly computed.

关键词： adaptive control Adaptive robust control Adaptive systems Scalar adaptive controller Nonzero delay projection algorithms margins plants PLANTS

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