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Localization of a Coherent Acoustic Source in a Shallow-Water Channel Using the Partially Calibrated Adaptive Antenna Array

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RADIOPHYSICS AND QUANTUM ELECTRONICS 2016年第2期59卷 88-96页

作者： Sazontov, A. G. Smirnov, I. P. Chashchin, A. S. Russian Acad Sci Inst Appl Phys Moscow 117901 Russia NI Lobachevsky State Univ Nizhny Novgorod Nizhnii Novgorod Russia

We consider the problem of determining the location of a coherent acoustic source in a shallowwater channel using a partially calibrated antenna array. To solve this problem, we develop a reduced-rank stable projection algorithm, which is the generalization of the RARE method to the case of signal reception under the conditions of incomplete information on the propagation medium. The results of experimental validation of the proposed approach, which show its efficiency under the conditions of an actual shallow-water area, are presented.

关键词： Calibration signal reception acoustic radiators propagation medium Generalization Antenna arrays adaptive antenna arrays projection algorithms

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The successive projections algorithm for interval selection in partial least squares discriminant analysis

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ANALYTICAL METHODS 2016年第41期8卷 7522-7530页

作者： de Sousa Fernandes, David Douglas Almeida, Valber Elias Pinto, Licarion Veras, Germano Harrop Galvao, Roberto Kawakami Gomes, Adriano Araujo Ugulino Araujo, Mario Cesar Univ Fed Paraiba Dept Quim Lab Automacao & Instrumentacao Quim Anal Quimiome Caixa Postal 5093 BR-58051970 Joao Pessoa Paraiba Brazil Univ Estadual Paraiba Ctr Ciencia & Tecnol Lab Quim Anal & Quimiometria BR-58429500 Campina Grande Paraiba Brazil Inst Tecnol Aeronaut Div Engn Elect BR-12228900 Sao Jose Dos Campos SP Brazil Univ Fed Sul & Sudoeste Para Fac Quim Inst Ciencia Exatas Folha 17Quadra 04 BR-68505080 Maraba Para Brazil

This paper proposes a new interval selection approach for PLS-DA modelling, which is developed as an extension of the recently introduced iSPA-PLS method for multivariate calibration. The proposed iSPA-PLS-DA algorithm is tested in two case studies concerning the classification of five types of vegetable oils employing square-wave voltammetry and the classification of five species of bacteria (Escherichia coli, Enterococcus faecalis, Streptococcus salivarius, Streptococcus oralis, and Staphylococcus aureus) using digital images. For comparison, the iPLS-DA algorithm for interval selection is also employed, in standard and backward modes. In both case studies, iSPA-PLS-DA provided correct classification rates larger than or equal to those obtained by PLS-DA using all variables and iPLS-DA with single or multiple intervals.

关键词： Streptococcus oralis Streptococcus salivarius projection algorithms Vegetable Oils algorithms discriminant analysis Case studies Digital images Partial least squares

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Norm-constrained adaptive algorithms for sparse system identification based on projections onto intersections of hyperplanes

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SIGNAL PROCESSING 2016年 118卷 259-271页

作者： Beck, Eduardo Ortiz Batista, Eduardo Luiz Seara, Rui Univ Fed Santa Catarina Dept Elect & Elect Engn LINSE Circuits & Signal Proc Lab BR-88040900 Florianopolis SC Brazil

This paper introduces a novel approach to derive norm-constrained adaptive algorithms for sparse system identification. In contrast to other similar approaches found in the literature, the proposed approach is focused primarily on keeping the a posteriori error equal to zero (which is a characteristic of the normalized least-mean-square algorithm) while seeking to satisfy a norm constraint. To this end, the proposed algorithms look directly for a vector belonging to the intersection of a zero-error hyperplane and a hyperplane resulting from a relaxed norm constraint. This somewhat simpler strategy leads to effective sparsity-promoting adaptive algorithms that exhibit low computational complexity and use parameters that are easy to adjust. In this context, a general framework that allows obtaining adaptive algorithms using different norm functions is devised. From this framework, two norm-constrained algorithms based on the l(1) and l(0) norms are obtained. Moreover, enhanced versions of these algorithms are developed aiming to make them independent of user-defined norm-bound parameters. Numerical simulation results corroborate the effectiveness of the proposed framework as well as the very good performance of the obtained algorithms. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Adaptive filtering Norm-constrained optimization projection algorithms Sparse impulse response System identification

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Adaptive Fault-tolerant Control for Cooperative Spacecraft Rendezvous and Docking

Adaptive Fault-tolerant Control for Cooperative Spacecraft R...

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American Control Conference

作者： Kewei Xia Wei Huo The Seventh Research Division Science and Technology on Aircraft Control Laboratory Beihang University Beijing 100191 P.R. China

ISBN: (纸本)9781509045839

An adaptive fault-tolerant controller is investigated for a pursuer spacecraft approaching a cooperative target spacecraft and docking with it. The six degree-of-freedom (6-DOF) relative dynamics system with actuator faults is formulated. An adaptive controller is developed, where adaptive algorithm is introduced to estimate and compensate system uncertainties, and projection algorithm is introduced to guarantee that the estimation of multiplicative fault matrix is invertible. It is proved that the closed-loop dynamics system is globally uniformly ultimately bounded. Numerical simulations are given to show effectiveness of the proposed controller.

关键词： Spacecraft Rendezvous Docking Berthing rendezvous Spacecraft SPACE RENDEZVOUS system uncertainties fault-tolerant control projection algorithms Reversibility Self tuning adaptive controller

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Bi-Orthonormal Polynomial Basis Function Framework With Applications in System Identification

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2016年第11期61卷 3285-3300页

作者： van Herpen, Robbert Bosgra, Okko Oomen, Tom Eindhoven Univ Technol Dept Mech Engn Control Syst Technol Grp NL-5612 AZ Eindhoven Netherlands

Numerical aspects are of central importance in identification and control. Many computations in these fields involve approximations using polynomial or rational functions that are obtained using orthogonal or oblique projections. The aim of this paper is to develop a new and general theoretical framework to solve a large class of relevant problems. The proposed method is built on the introduction of bi-orthonormal polynomials with respect to a data-dependent bi-linear form. This bi-linear form generalises the conventional inner product and allows for asymmetric and indefinite problems. The proposed approach is shown to lead to optimal numerical conditioning (kappa = 1) in a recent frequency-domain instrumental variable system identification algorithm. In comparison, it is shown that these recent algorithms exhibit extremely poor numerical properties when solved using traditional approaches.

关键词： Least-squares approximations numerical analysis polynomials projection algorithms system identification

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Two-microphone acoustic feedback cancellation using NLMS based algorithms

Two-microphone acoustic feedback cancellation using NLMS bas...

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International Conference on Electronics, Computers and Artificial Intelligence (ECAI)

作者： Felix Albu Linh T. T. Tran Sven Nordholm Department of Electronics Telecommunications and Electrical Engineering Valahia University of Targoviste Targoviste Romania Faculty of Science and Engineering Curtin University Perth Australia

In this paper a sign NLMS algorithm variant is proposed to adapt the second microphone on the two microphone approach in hearing aids. for closed-loop feedback cancellation. The simulation results show improved conver... 详细信息

关键词： Signal processing algorithms Microphones Acoustics Hearing aids Probes projection algorithms Adaptive filters

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Projecting "better than randomly": How to reduce the dimensionality of very large datasets in a way that outperforms random projections 3

Projecting "better than randomly": How to reduce the dimensi...

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3rd IEEE/ACM International Conference on Data Science and Advanced Analytics (DSAA)

作者： Wojnowicz, Michael Zhang, Di Chisholm, Glenn Zhao, Xuan Wolff, Matt Cylance Inc Dept Res & Intelligence Irvine CA 92612 USA

ISBN: (纸本)9781509052066

For very large datasets, random projections (RP) have become the tool of choice for dimensionality reduction. This is due to the computational complexity of principal component analysis. However, the recent development of randomized principal component analysis (RPCA) has opened up the possibility of obtaining approximate principal components on very large datasets. In this paper, we compare the performance of RPCA and RP in dimensionality reduction for supervised learning. In Experiment 1, study a malware classification task on a dataset with over 10 million samples, almost 100,000 features, and over 25 billion non-zero values, with the goal of reducing the dimensionality to a compressed representation of 5,000 features. In order to apply RPCA to this dataset, we develop a new algorithm called large sample RPCA (LS-RPCA), which extends the RPCA algorithm to work on datasets with arbitrarily many samples. We find that classification performance is much higher when using LS-RPCA for dimensionality reduction than when using random projections. In particular, across a range of target dimensionalities, we find that using LS-RPCA reduces classification error by between 37% and 54%. Experiment 2 generalizes the phenomenon to multiple datasets, feature representations, and classifiers. These findings have implications for a large number of research projects in which random projections were used as a preprocessing step for dimensionality reduction. As long as accuracy is at a premium and the target dimensionality is sufficiently less than the numeric rank of the dataset, randomized PCA may be a superior choice. Moreover, if the dataset has a large number of samples, then LS-RPCA will provide a method for obtaining the approximate principal components.

关键词： Machine learning Predictive models projection algorithms

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Improved set-membership partial-update affine projection algorithm

Improved set-membership partial-update affine projection alg...

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

作者： Paulo S. R. Diniz Hamed Yazdanpanah Universidade Federal do Rio de Janeiro DEL/Poli & PEE/COPPE/UFRJ Rio de Janeiro RJ Brazil

ISBN: (纸本)9781479999897

In this paper, we present an improved set-membership partial-update affine projection (I-SM-PUAP) algorithm, aiming at accelerating the convergence, and decreasing the update rates and the computational complexity of the set-membership partial-update affine projection (SM-PUAP) algorithm. To meet these targets, we constrain the weight vector perturbation to be bounded by a hypersphere instead of the threshold hyperplanes as in the standard algorithm. We use the distance between the present weight vector and the expected update in the standard set-membership affine projection (SM-AP) algorithm to construct the hypersphere. With this strategy, the new algorithm shows better behavior in the early iterations. Simulation results verify the excellent performance of the proposed algorithm related to the convergence rate and the required number of updates.

关键词： Convergence Computational complexity Acceleration Standards Estimation error projection algorithms Mathematical model

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Runway extraction method based on rotating projection for UAV

Runway extraction method based on rotating projection for UA...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Yu-jie Sun Yang Li Huan Yang Beijing Institute of Technology Beijing China

ISBN: (纸本)9781467386456

We bring out a runway extraction method based on rotating projection in this paper, which is consisted of three steps, locating the Region of interest (ROI), edge extraction and line detection. Firstly we employed template matching to locate the ROI which contains the runway area. Then we use Sobel operator to extract edges. The rotating projection algorithm is proposed to seek the potential straights in ROI, which will be integrated into the real straights by means of improved K-means clustering method. Simulations are carried out in the end, and results show that the algorithm proposed in this paper can extract the four boundaries of the runway effectively, while it can reduce 50% of computing time compared with Hough transform.

关键词： Image edge detection Transforms Clustering algorithms projection algorithms Clustering methods Mathematical model Correlation

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Adaptive Decision Feedback Equalizer with Set-membership Affine projection Algorithm

Adaptive Decision Feedback Equalizer with Set-membership Aff...

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IEEE International Conference on Industrial and Information Systems

作者： Ramesh Chandra Mishra Ratnajit Bhattacharjee Indian Institute of Technology Guwahati Assam India

In this paper, a data-reusing algorithm with non-zero decision boundaries for data-selective updating of the coefficients of a decision feedback equalizer (DFE) is investigated for time-varying frequency selective wireless channels. Here, the coefficients of both the feed-forward filter (FFF) and the feedback filter (FBF) are adaptively updated using set-membership affine projection algorithm. It's performance is analyzed through simulations using ITU-R recommended wireless channel models. It is shown that, this scheme offers substantial computational savings while keeping the bit error rate (BER) and convergence performance almost similar to channel equalization with the data reusing affine projection algorithms. It is also demonstrated that, this channel equalization method yields faster convergence and better BER than the existing set-membership normalized least mean square (NLMS) algorithm based scheme.

关键词： Decision feedback equalizers Convergence Wireless communication Adaptation models Mathematical model Complexity theory decision feedback equalisers adaptive decision feedback equalizer Complexity theory CARRIER SYSTEM Converge projection algorithms Mathematical Model channel equalization Adaptation models Affine In-law Bit error rate wireless channels

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