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检索条件"主题词=Projection Algorithms"

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Adaptive projected subgradient method and its applications to set theoretic adaptive filtering

Adaptive projected subgradient method and its applications t...

引用

Asilomar Conference on Signals, Systems & Computers

作者： I. Yamada N. Ogura Department of Comm. and Integrated Systems Tokyo Institute of Technology Tokyo Japan Precision and Intelligence Laboratory Tokyo Institute of Technology Yokohama Japan

This paper presents an algorithm, named adaptive projected subgradient method that can minimize asymptotically certain sequence of nonnegative convex functions over a closed convex set in a real Hubert space. The proposed algorithm is a natural extension of the Polyak's subgradient algorithm, for unsmooth convex optimization problem with a fixed target value, to the case where the convex objective itself keeps changing in the whole process. The main theorem, showing the strong convergence of the algorithm as well as the asymptotic optimality of the sequence generated by the algorithm, can serve as a unified guiding principle of a wide range of set theoretic adaptive filtering schemes for nonstationary random processes. These include not only the existing adaptive filtering techniques, e.g.. NLMS, projected NLMS, constrained NLMS, APA, and adaptive parallel outer projection algorithm etc, but also new techniques, e.g., adaptive parallel min-max projection algorithm, and their embedded constraint versions. Numerical examples show that the proposed techniques are well-suited for robust adaptive signal processing problems.

关键词： Adaptive filters Signal processing algorithms Filtering algorithms Hilbert space Space technology Convergence projection algorithms Adaptive signal processing Programmable control Adaptive control

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Robust training algorithm for a perceptron neuron

Robust training algorithm for a perceptron neuron

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International Conference on Neural Networks

作者： Q. Song School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore

Our interest in this paper is to study the behavior of the perceptron neuron in the presence of disturbance which is always important for practical applications. A robust classifier is required to be insensitive to disturbances and to classify noisy input patterns into the correct class, to which the respective desired input pattern belongs. The projection algorithm with a dead zone is well known in system identification and adaptive control systems to guarantee the convergence. In this paper, the dead zone scheme is used to train the nonlinear perceptron neuron. The trained perceptron neuron is capable of classifying the noisy input pattern sequence into the correct class in the presence of disturbance.

关键词： Neurons projection algorithms Convergence System identification Adaptive control Noise robustness Pattern classification Robust control Differential equations

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A Global Stability Result in Utility-Based Congestion Control

A Global Stability Result in Utility-Based Congestion Contro...

引用

IEEE Conference on Decision and Control

作者： O.C. Imer T. Basar Coordinated Science Laboratory University of illinois Urbana-Champaign USA GE Global Research Niskayuna NY USA Coordinated Science Laboratory University of Illinois Urbana-Champaign Urbana IL USA

In this paper, we introduce a new utility-based congestion control algorithm, M-REM (modified-REM), and show its convergence. The algorithm is a slight modification of the so-called REM (random exponential marking) gradient projection algorithm, in which all buffers in the network are cleared when equilibrium source rates are reached. By defining the "price" of a particular link as a weighted sum of the Lagrange multiplier and buffer length associated with that link, we show that M-REM is globally asymptotically stable, while preserving the decentralized nature of REM.

关键词： Convergence Quality of service Intelligent networks projection algorithms Lagrangian functions Cost accounting Aggregates Internet Stability analysis Routing

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Image coding with iterated contourlet and wavelet transforms

Image coding with iterated contourlet and wavelet transforms

引用

IEEE International Conference on Image Processing

作者： V. Chappelier C. Guillemot S. Marinkovic IRISA Universite de Rennes 1 Rennes France

This paper presents a new coding technique based on a mixed contourlet and wavelet transform. The redundancy of the transform is controlled by using the contourlet at fine scales and by switching to a separable wavelet transform at coarse scales. The transform is then optimized through an iterative projection process in the transform domain in order to minimize the quantization error in the image domain. A gain of respectively up to 0.5 dB and to 1 dB over respectively contourlet and wavelet based coding has been observed for images with directional features.

关键词： Image coding Wavelet transforms Discrete wavelet transforms Matching pursuit algorithms Frequency Quantization Signal processing algorithms Discrete transforms Iterative algorithms projection algorithms

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Construction of equiangular signatures for synchronous CDMA systems

Construction of equiangular signatures for synchronous CDMA ...

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IEEE International Symposium on Spread Spectrum Techniques and Applications

作者： R.W. Heath J.A. Tropp I. Dhillon T. Strohmer Department of Electrical and Computer Engineering University of Texas Austin Austin TX USA Institute for Computer Engineering and Science (ICES) University of Texas Austin Austin TX USA Department of ComputerSci University of Texas Austin Austin TX USA Department of Mathematics University of California슠Davis Davis CA USA

Welch bound equality (WBE) signature sequences maximize the uplink sum capacity in direct-spread synchronous code division multiple access (CDMA) systems. WBE sequences have a nice interference invariance property that typically holds only when the system is fully loaded, and, to maintain this property, the signature set must be redesigned and reassigned as the number of active users changes. An additional equiangular constraint on the signature set, however, maintains interference invariance. Finding such signatures requires equiangular side constraints to be imposed on an inverse eigenvalue problem. The paper presents an alternating projection algorithm that can design WBE sequences that satisfy equiangular side constraints. The proposed algorithm can be used to find Grassmannian frames as well as equiangular tight frames. Though one projection is onto a closed, but non-convex, set, it is shown that this algorithm converges to a fixed point, and these fixed points are partially characterized.

关键词： Code division multiplexing Multiaccess communication Interference constraints Iterative algorithms Eigenvalues and eigenfunctions Ice Mathematics projection algorithms Algorithm design and analysis Gaussian noise

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A FAST COMPRESSIVE SENSING METHOD WITH APPLICATION TO NETWORK ECHO CANCELLATION

A FAST COMPRESSIVE SENSING METHOD WITH APPLICATION TO NETWOR...

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European Signal Processing Conference

作者： Pratik Shah Steven L. Grant Jacob Benesty Missouri University of Science and Technology Rolla Missouri INRS-EMT University of Quebec Montreal Canada

ISBN: (纸本)9781479936878

Compressive sensing methods have been effectively used for sparse system identification. Many methods have been proposed to exploit this sparsity to reduce the amount of data required for identification. Most though, have high computational complexity. Recently, an iterative method based on the proportionate affine projection algorithm with row action projections (iPAPA-RAP) has been shown to have good convergence properties with relatively low complexity. Here, we present extensions of that algorithm that significantly speed convergence and as a result lower overall computational complexity. The main improvement is the addition of a zero attractor step with a variable scale factor. Significantly, this scale factor is made to be a function of the sparsity of the estimated system parameters. This greatly improves the convergence behavior of the resulting algorithm. It is compared with iteratively reweighted least-squares (IRLS) and l_0 - zero attracting projections (l_0-ZAP). Results show that the proposed algorithm converges faster with lower overall complexity.

关键词： PAPA sparse IRLS compressed sensing adaptive filter ZiPR Compressed sensing adaptive filters IRL Scale factor PSTPIP1 gene CANCELLATIONS Converge ECHO projection algorithms

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Incorporated robustness in narrow-band signal subspace spatial spectral estimators

Incorporated robustness in narrow-band signal subspace spati...

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

作者： K. Buckley Department of Electrical Engineering University of Minnesota Minneapolis MN USA

Signal subspace spectral estimation algorithms are, by design, highly sensitive to differences between assumed source observation models and actual source observations. In spatial spectral estimation, where observations are derived from different array elements and are a function of various source propagation and observation parameters, accurate source modeling is often not possible. As a result, when incorrect values of model parameters are assumed, signal subspace algorithm performance is degraded. In this paper, an approach for incorporating robustness to assumed model parameter values is investigated. The approach is based on: 1) a representation of rank-1 sources in an low-rank subspace; and 2) a signal subspace projection algorithm suggested by Schmidt. In addition to providing robustness to certain types of parameter variations, the approach provides a computationally efficient way of searching through some multidimensional parameter spaces.

关键词： Robustness Narrowband Sensor arrays Frequency projection algorithms Sensor systems Position measurement Propagation delay Signal design Algorithm design and analysis

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Learning sparse deep neural networks using efficient structured projections on convex constraints for green AI

Learning sparse deep neural networks using efficient structu...

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International Conference on Pattern Recognition

作者： Michel Barlaud Frédéric Guyard Laboratoire I3S CNRS Cote d’ Azur University Sophia Antipolis France Orange Labs Sophia Antipolis France

Deep neural networks (DNN) have been applied recently to different domains and perform better than classical state-of-the-art methods. However the high level of performances of DNNs is most often obtained with networks containing millions of parameters and for which training requires substantial computational power. To deal with this computational issue proximal regularization methods have been proposed in the literature but they are time consuming. In this paper, we propose instead a constrained approach. We provide the general framework for this new projection gradient method. Our algorithm iterates a gradient step and a projection on convex constraints. We studied algorithms for different constraints: the classical ℓ₁unstructured constraint and structured constraints such as the £2,1 constraint (Group LASSO). We propose a new ℓ_1,1structured constraint for which we provide a new projection algorithm. Finally, we used the recent “Lottery optimizer” replacing the threshold by our ℓ_1,1projection. We demonstrate the effectiveness of this method with three popular datasets (MNIST, Fashion MNIST and CIFAR). Experiments with these datasets show that our projection method using this new ℓ_1,1structured constraint provides the best decrease in memory and computational power.

关键词： Training Gradient methods Neural networks Pattern recognition Computational efficiency projection algorithms Artificial intelligence

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A computationally optimal randomized proper orthogonal decomposition technique

A computationally optimal randomized proper orthogonal decom...

引用

American Control Conference

作者： Dan Yu Suman Chakravorty Department of Aerospace Engineering Texas A&M University College Station USA Aerospace Engineering Texas A&M University College Station USA

ISBN: (纸本)9781467386838

In this paper, we consider the model reduction problem of large-scale systems, such as systems obtained through the discretization of partial differential equations. We propose a computationally optimal randomized proper orthogonal decomposition (RPOD*) technique to obtain the reduced order model by perturbing the primal and adjoint system using Gaussian white noise. We show that the computations required by the RPOD* algorithm is orders of magnitude cheaper when compared to the balanced proper orthogonal decomposition (BPOD) algorithm while the performance of the RPOD* algorithm is better than BPOD. It is optimal in the sense that a minimal number of snapshots is needed. We also relate the RPOD* algorithm to random projection algorithms. One numerical example is given to illustrate the procedure.

关键词： Read only memory Reduced order systems Algorithm design and analysis Markov processes Large-scale systems White noise projection algorithms

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Adaptive generation of desired velocity field for cooperative mobile robots with decentralized PVFC

Adaptive generation of desired velocity field for cooperativ...

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Proceedings. 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2000) (Cat. No.00CH37113)

作者： M. Yamakita J.H. Suh Department of Control and Systems Engineering Tokyo Institute of Technology Meguro Tokyo Japan

We have proposed a decentralized control method based on passive velocity field control (PVFC) in previous works (1997, 1998). However, the feedback was localized and the desired velocity field was given by a central controller. The geometry cooperative multiple mobile robot system whose subsystem is under nonholonomic constraints and which conveys a common rigid object in a horizontal plain was proposed. In this paper, we propose a method to generate the desired velocity field for cooperative mobile robots with decentralized PVFC. The proposed control method for cooperative mobile robots is constructed by extending the PVFC and ensures the stability and boundedness using projection algorithm. Finally, the efficiency of the proposed method is examined by computer simulations for cooperative tasks with two manipulators.

关键词： Mobile robots Velocity control Distributed control Feedback Centralized control Computational geometry Stability projection algorithms Computer simulation Manipulators

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