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2nd Mini-Symposium on High Performance Computing (HPC) Applied to Computational Problems in Science and Engineering/10th International Conference on Computational and Mathematical Methods in Science and Engineering

作者： Migallon, Hector Migallon, Violeta Penades, Jose Univ Miguel Hernandez Dept Fis & Arquitectura Comp Alicante 03202 Spain Univ Alicante Dept Ciencia Comp & Inteligencia Artificial Alicante 03071 Spain

In this paper, we present PyPANCG, a Python library-interface that implements both the conjugate gradient method and the preconditioned conjugate gradient method for solving nonlinear systems. We describe the use of the library and its advantages in order to get fast development. The aim of this library is to develop high performance scientific codes for high-end computers hiding many of the underlying low-level programming complexities from users with the use of a high-level Python interface. The library has been designed for adapting to different stages of the design process, depending on whether the purpose is computational performance or fast development. Experimental results report the performance of our approach on different parallel computers.

关键词： Parallel libraries nonlinear algorithms Python high-level interfaces

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From linear to nonlinear unfolded Condat-Vũ algorithm for spectro-polarimetric hight-constrast image recovery 32

From linear to nonlinear unfolded Condat-Vũ algorithm for s...

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32nd European Signal Processing Conference, EUSIPCO 2024

作者： Chappon, E. Pustelnik, N. Tachella, J. Denneulin, L. Ferrari, A. Langlois, M. Laboratoire de Physique ENSL CNRS UMR 5672 LyonF-69342 France Laboratoire de Recherche de l’EPITA EPITA Le Kremlin-Bicêtre94270 France Université Côte d’Azur Observatoire de la Côte d’Azur CNRS Lab. J.-L. Lagrange France Univ Lyon Univ. Lyon 1 ENS de Lyon CNRS Centre de Recherche Astrophysique de Lyon UMR5574 Saint-Genis-Laval69230 France

ISBN: (纸本)9789464593617

Studying circumstellar environments is crucial for understanding exoplanets and stellar systems. Instruments like SPHERE can extract information about these environments by leveraging advanced image reconstruction methods, possibly based on deep learning. This work focuses on unfolded proximal neural networks based on Condat-Vũ iterations and proposes a new nonlinear formulation. To evaluate and compare the performance of the proposed reconstruction strategies, two datasets dedicated to circumstellar environments analysis in the context of high-contrast imagery have been created offering different level of complexity in the evaluation of the performance. © 2024 European Signal Processing Conference, EUSIPCO. All rights reserved.

关键词： deep learning High constrast image recovery nonlinear algorithms proximal algorithms unfolded algorithms

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SEPARABLE CONCAVE MINIMIZATION VIA PARTIAL OUTER APPROXIMATION AND BRANCH AND BOUND

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OPERATIONS RESEARCH LETTERS 1990年第6期9卷 389-394页

作者： BENSON, HP UNIV FLORIDA 351 BUSINESS BLDGGAINESVILLEFL 32611 USA

This paper presents a new algorithm for globally minimizing a separable, concave function over a compact convex set. The algorithm uses partial outer approximation and branch and bound. The major computational effort required is solving linear programming problems at some nodes of the branch and bound tree, and solving simple univariate minimizations in some iterations. The algorithm partially mitigates the rapid growth in the number of constraints of the linear programs that would frequently occur if traditional outer approximation were used. Furthermore, unlike outer approximation, the algorithm does not explicitly construct polyhedra which contain the feasible region.

关键词： programming nonlinear algorithms concave minimization

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A primal method for the solution of the groundwater quality management problem

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OPERATIONS RESEARCH 1998年第4期46卷 463-473页

作者： Tucciarelli, T Karatzas, GP Pinder, GF Univ Palermo Palermo Italy Univ Vermont Burlington VT USA

A new algorithm for the solution of the groundwater quality management problem is presented. The method assumes that most of the computational effort in such problems involves evaluation of the concentrations and their derivatives with respect to the pumping rates at the control points. The methodology proposed herein is a combination of the cutting plane method and the primal method. In this approach each line search moves from a feasible point towards the solution of a subproblem with linear constraints and the same objective function as the original problem. Sensitivity analysis is used to compute the derivative of a single concentration with respect to all the pumping rates by solving only one linear system at each time step. The method has been tested with analytical convex problems and a model example. A comparison of the algorithm's performance was conducted using MINOS 5.1. For the case of a linear cost function the method shows a computational growth rate almost linearly proportional to the number of decision variables.

关键词： Water resources groundwater quality management problem nonlinear algorithms primal method

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On the equivalence of linear complementarity problems

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OPERATIONS RESEARCH LETTERS 2002年第4期30卷 211-222页

作者： De Schutter, B Heemels, WPMH Bemporad, A Delft Univ Technol Fac ITS NL-2600 GA Delft Netherlands Eindhoven Univ Technol Dept Elect Engn NL-5600 MB Eindhoven Netherlands Univ Siena Dip Ingn Informaz I-53100 Siena Italy

We show that the Extended Linear Complementarity Problem (ELCP) can be recast as a standard Linear Complementarity Problem (LCP) provided that the surplus variables or the feasible set of the ELCP are bounded. Since many extensions of the LCP are special cases of the ELCP, this implies that these extensions can be rewritten as an LCP as well. Our equivalence proof is constructive and leads to three possible numerical solution methods for a given ELCP: regular ELCP algorithms, mixed integer linear programming algorithms, and regular LCP algorithms. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： complementarity problems nonlinear algorithms integer programming optimization linear complementarity problem

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A scalable fuzzy interference canceler for DS-CDMA systems

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INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS 2005年第2期20卷 253-274页

作者： Bas, J Neira, AP Univ Politecn Cataluna Signal Theory Dept Barcelona 08034 Spain

The spread spectrum modulation presents a more robust interference rejection capability than non-code-based modulations. However, the increase of the communication services has augmented the power of the interference signals. One example is unlicensed bands such as the 2.4-2.5 GHz one, where the DS-CDMA communications of the IEEE 802.1 lb standard are interfered with by other Industrial Scientific and Medical (ISM) services. One way of improving the interference robustness of the DS-CDMA receivers is introducing an interference canceler (IC) before the despreading stage. The optimum criterion to estimate or detect the interference is the maximum-a-posteriori (MAP) one. However, it requires a high computational burden and a complete knowledge of the statistical model, which reduce its feasibility. To overcome these drawbacks this article proposes an interference canceler based on Fuzzy Logic that allows (1) suppressing both analog and digital interferences, and (2) easily controlling the complexity versus performance trade-off. In other words, the design of the fuzzy canceler follows a down/ top strategy;that is, a first low complex design is possible just departing from linguistic information and, in a second stage, we refine it, incorporating the available statistical information into its structure. Finally, to assess the proposed fuzzy canceler we have derived asymptotic performance bounds. (C) 2005 Wiley Periodicals, Inc.

关键词： NARROW-BAND INTERFERENCE SPREAD-SPECTRUM SYSTEMS DS/CDMA COMMUNICATIONS nonlinear algorithms SUPPRESSION SETS

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Kernel-Based Learning for Statistical Signal Processing in Cognitive Radio Networks

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IEEE SIGNAL PROCESSING MAGAZINE 2013年第4期30卷 126-136页

作者： Ding, Guoru Wu, Qihui Yao, Yu-Dong Wang, Jinlong Chen, Yingying PLA Univ Sci & Technol Coll Commun Engn Nanjing Jiangsu Peoples R China Southeast Univ Nanjing Jiangsu Peoples R China PLA Univ Sci & Technol Nanjing Jiangsu Peoples R China Stevens Inst Technol Hoboken NJ 07030 USA Carleton Univ Ottawa ON K1S 5B6 Canada Spar Aerosp Ltd Montreal PQ Canada Qualcomm Inc San Diego CA USA IEEE Nanjing Sect Nanjing Jiangsu Peoples R China Stevens Inst Technol Dept Elect & Comp Engn Hoboken NJ USA Alcatel Lucent Holmdel NJ USA

Kernel-based learning (KBL) methods have recently become prevalent in many engineering applications, notably in signal processing and communications. The increased interest is mainly driven by the practical need of being able to develop efficient nonlinear algorithms, which can obtain significant performance improvements over their linear counterparts at the price of generally higher computational complexity. In this article, an overview of applying various KBL methods to statistical signal processing-related open issues in cognitive radio networks (CRNs) is presented. It is demonstrated that KBL methods provide a powerful set of tools for CRNs and enable rigorous formulation and effective solutions to both long-standing and emerging design problems.

关键词： Machine learning Learning systems Kernel Cognitive radio Signal processing algorithms nonlinear algorithms

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VECTOR MEDIAN FILTERS

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PROCEEDINGS OF THE IEEE 1990年第4期78卷 678-689页

作者： ASTOLA, J HAAVISTO, P NEUVO, Y Tampere Univ. of Technol.

Two nonlinear algorithms for processing vector-valued signals are introduced. The algorithms, called vector median operations, are derived from two multidimensional probability density functions using the maximum-likelihood-estimate approach. The underlying probability densities are exponential, and the resulting operations have properties very similar to those of the median filter. In the vector median approach, the samples of the vector-valued input signal are processed as vectors. The operation inherently utilizes the correlation between the signal components, giving the filters some desirable properties. General properties as well as the root signals of the vector median filters are studied. The vector median operation is combined with linear filtering, resulting in filters with improved noise attenuation and filters with very good edge response. An efficient algorithm for implementing long vector median filters is presented. The noise attenuation of the filters is discussed, and an application to velocity filtering is shown

关键词： correlation correlation theory edge response filtering and prediction theory linear filtering maximum-likelihood-estimate approach multidimensional probability density functions noise attenuation nonlinear algorithms probability probability densities root signals signal processing vector median operations vector-valued signals velocity filtering

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A DUAL APPROACH FOR THE CONTINUOUS COLLAPSING KNAPSACK-PROBLEM

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MATHEMATICAL PROGRAMMING 1987年第2期39卷 207-214页

作者： POSNER, ME SUZUKI, H TOKYO INST TECHNOL TOKYO 152JAPAN

We formulate and solve a dual version of the Continuous Collapsing Knapsack Problem using a geometric approach. Optimality conditions are found and an algorithm is presented. Computational experience shows that this p... 详细信息

关键词： nonlinear algorithms duality knapsack problem

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Friction State Classification Based on Vehicle Inertial Measurements 9th

Friction State Classification Based on Vehicle Inertial Meas...

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9th IFAC International Symposium on Advances in Automotive Control (AAC)

作者： Selmanaj, Donald Corno, Matteo Savaresi, Sergio M. Polytech Univ Tirana Dept Automat Sheshi Nene Tereza 4 Tirana Albania Politecn Milan Dipartimento Elettron Informaz & Bioingn Piazza L da Vinci 32 I-20133 Milan Italy

Tire-road friction is the most important characteristic defining the planar dynamics of wheeled vehicles. It has consequences on the drivability, stability and tuning of the active vehicle dynamics control systems. This paper proposes two online friction estimation methods designed for the adaptation of vehicle dynamics control algorithms. The problem is framed as a classification problem where inertial measurements are used to discriminate between high and low friction regimes. The first method merges a recursive least-squares (RLS) algorithm with a heuristic bistable logic to classify the friction condition and promptly react to its changes. The second method runs a classification algorithm on the slip-acceleration characteristic. Both methods simultaneously account for the longitudinal and lateral dynamics and are tested on experimental data. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Friction Vehicles dynamics Classification Recursive algorithms nonlinear algorithms

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