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filtering algorithms for global chance constraints

ARTIFICIAL INTELLIGENCE 2012年 189卷 69-94页

作者： Hnich, Brahim Rossi, Roberto Tarim, S. Armagan Prestwich, Steven Univ Edinburgh Sch Business Edinburgh EH8 9JS Midlothian Scotland Izmir Univ Econ Dept Comp Engn Izmir Turkey Hacettepe Univ Dept Management Ankara Turkey Natl Univ Ireland Univ Coll Cork Cork Constraint Computat Ctr Cork Ireland

Stochastic Constraint Satisfaction Problems (SCSPs) are a powerful modeling framework for problems under uncertainty. To solve them is a PSPACE task. The only complete solution approach to date - scenario-based stochastic constraint programming - compiles SCSPs clown into classical CSPs. This allows the reuse of classical constraint solvers to solve SCSPs, but at the cost of increased space requirements and weak constraint propagation. This paper tries to overcome these drawbacks by automatically synthesizing filtering algorithms for global chance constraints. These filtering algorithms are parameterized by propagators for the deterministic version of the chance constraints. This approach allows the reuse of existing propagators in current constraint solvers and it has the potential to enhance constraint propagation. Our results show that, for the test bed considered in this work, our approach is superior to scenario-based stochastic constraint programming. For these instances, our approach is more scalable, it produces more compact formulations, it is more efficient in terms of run time and more effective in terms of pruning for both stochastic constraint satisfaction and optimization problems. (C) 2012 Elsevier B.V. All rights reserved.

关键词： Stochastic constraint programming Stochastic constraint satisfaction Global chance constraints filtering algorithms Stochastic alldifferent

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ADAPTIVE IIR filtering algorithms FOR SYSTEM-IDENTIFICATION - A GENERAL FRAMEWORK

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IEEE TRANSACTIONS ON EDUCATION 1995年第1期38卷 54-66页

作者： NETTO, SL DINIZ, PSR AGATHOKLIS, P UNIV FED RIO DE JANEIRO COPPE DEPT ELECTR ENGN PROGRAMA ENGN ELETR BR-21945 RIO DE JANEIRO BRAZIL

Adaptive IIR (infinite impulse response) filters are particularly beneficial in modeling real systems because they require lower computational complexity and can model sharp resonances more efficiently as compared to the FIR (finite impulse response) counterparts. Unfortunately, a number of drawbacks are associated with adaptive IIR filtering algorithms that have prevented their widespread use, such as: Convergence to biased or local minimum solutions, requirement of stability monitoring, and slow convergence. Most of the recent research effort on this field is aimed at overcoming some of the above mentioned drawbacks. In this paper, a number of known adaptive IIR filtering algorithms are presented using a unifying framework that is useful to interrelate the algorithms and to derive their properties. Special attention is given to issues such as the motivation to derive each algorithm and the properties of the solution after convergence. Several computer simulations are included in order to verify the predicted performance of the algorithms.

关键词： filtering algorithms System identification IIR filters Finite impulse response filter Adaptive filters Computational complexity Resonance Stability Monitoring Computer simulation

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Optimum block adaptive filtering algorithms using the preconditioning technique

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 1997年第3期45卷 773-778页

作者： Jae, SL Chong, KU Communications Research Laboratory Department of Electrical Engineering Korea Advanced Institute of Science and Technology Taejon South Korea

We propose three block adaptive algorithms using the preconditioning technique, The Toeplitz-preconditioned optimum block adaptive (TOBA) algorithm employs a preconditioner assumed to be Toeplitz, the SSOR-preconditioned optimum block adaptive (SOBA) algorithm uses a product of triangular matrices as a preconditioner, and the circulant-preconditioned OBA (COBA) algorithm is based on a circulant preconditioner. It is also shown that their tracking properties and convergence rates are superior to those of the OBA algorithm, the self-orthogonalizing block adaptive filter (SOBAF), and the normalized frequency-domain OBA (NFOBA) algorithm.

关键词： Adaptive filters filtering algorithms Signal processing algorithms Convergence Signal to noise ratio Finite impulse response filter Adaptive algorithm Autocorrelation Signal processing System identification

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A STRUCTURAL VIEW OF ASYMPTOTIC CONVERGENCE SPEED OF ADAPTIVE IIR filtering algorithms .1. INFINITE PRECISION IMPLEMENTATION

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 1993年第4期41卷 1493-1517页

作者： FAN, H Department of Electrical and Computer Engineering University of Cincinnati Cincinnati OH USA

Recently, adaptive algorithms based on alternate structures such as parallel and lattice that are more traditional in digital filter design literature have been proposed for system identification and adaptive infinite impulse response (IIR) filtering with the objectives of ease of stability monitoring, improved convergence speed, better numerical property, and possible VLSI implementation due to their modular structural nature, as opposed to the direct form algorithms. While the issue of stability for adaptive algorithms has received much study, that of convergence speed has hardly been touched for these structures. Computer simulations show that many adaptive IIR filtering algorithms do not converge or converge extremely slowly for lightly damped low-frequency (LDLF) poles despite their theoretical convergence analysis under ideal conditions. In this paper such a problem is studied analytically under infinite precision implementation assumption. Asymptotic convergence speed of various structures and algorithms is investigated in terms of unknown system pole-zero locations which may often be roughly known a priori. The adverse effects of LDLF poles on convergence speed of various structures and algorithms are analyzed and compared. This is done by studying local eigenvalue spread of appropriate information matrices associated with each algorithm. It is shown, expectedly, that local convergence speed of the simple constant-gain type algorithms is very susceptible to unknown system pole locations, especially LDLF poles, whereas Newton type of algorithms are more immune to such effect. More surprising results in terms of convergence speed have also been obtained. For example, the transform-domain algorithms are shown to be inferior to the direct form ones;and, locally most lattice algorithms do not offer much improvement ever the direct form ones. With additional consideration in terms of global convergence and stability monitoring, it is concluded that the normalized

关键词： Convergence Lattices Differential equations Adaptive filters IIR filters System identification filtering algorithms Transforms Eigenvalues and eigenfunctions Adaptive algorithm

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IMPLEMENTATION OF KALMAN AND ADAPTIVE KALMAN filtering algorithms FOR DIGITAL DISTANCE PROTECTION ON A VECTOR SIGNAL PROCESSOR

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IEEE TRANSACTIONS ON POWER DELIVERY 1989年第1期4卷 141-156页

作者： GIRGIS, AA HART, DG Electrical & Computer Engineering Department Clemson University Clemson SC USA

Implementation of two Kalman filtering processes for use in digital distance protection schemes is discussed. The first method uses Kalman filtering to determine the type of fault and fault location, while the second method utilizes adaptive Kalman filtering and conditional probabilities. Both techniques can be divided into five major components: fault detection, postfault current and voltage estimation (filtering), fault classification, zone computation, and fault location. This research focuses on the implementation of the filtering algorithms on the Zoran ZR34161 vector signal processor. The algorithm was tested on the Zoran vector signal processor simulator. The results are presented and discussed.

关键词： distance protection Kalman filtering Fault location filtering algorithms adaptive Kalman filters ethynylestradiol mixture with norethindrone

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APPLICATION OF BENVENISTES CONVERGENCE RESULTS IN THE STUDY OF ADAPTIVE IIR filtering algorithms

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IEEE TRANSACTIONS ON INFORMATION THEORY 1988年第4期34卷 692-709页

作者： HONG, F Department of Electrical and Computer Engineering University of Cincinnati Cincinnati OH USA

It is shown that the weak convergence results of A. Benveniste et al. (IEEE Trans. Automat. Contr., ***-25, p.1042-58, Dec. 1980) can be used to prove convergence of some adaptive infinite impulse response (IIR) filtering algorithms. The association of the algorithms with some ordinary differential equations for constant gains, which parallels the theory of L. Ljung et al. (1983), is suitable for constant-gain adaptive filtering applications. Convergence proofs for a prefiltering algorithm, for a simple constant-gain version of the recursive maximum-likelihood algorithm, and for the well-known simple hyperstable adaptive recursive filter (SHARF) algorithm are given as examples

关键词： Convergence filtering algorithms Adaptive filters IIR filters Finite impulse response filter System identification Differential equations Stochastic processes Algorithm design and analysis Poles and zeros

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Linear-time filtering algorithms for the disjunctive constraint and a quadratic filtering algorithm for the cumulative not-first not-last

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CONSTRAINTS 2018年第3期23卷 272-293页

作者： Fahimi, Hamed Ouellet, Yanick Quimper, Claude-Guy Univ Laval Quebec City PQ Canada

We present new filtering algorithms for Disjunctive and Cumulative constraints, each of which improves the complexity of the state-of-the-art algorithms by a factor of log n. We show how to perform Time-Tabling and Detectable Precedences in linear time on the Disjunctive constraint. Furthermore, we present a linear-time Overload Checking for the Disjunctive and Cumulative constraints. Finally, we show how the rule of Not-first/Not-last can be enforced in quadratic time for the Cumulative constraint. These algorithms rely on the union find data structure, from which we take advantage to introduce a new data structure that we call it time line. This data structure provides constant time operations that were previously implemented in logarithmic time by the Iy-tree data structure. Experiments show that these new algorithms are competitive even for a small number of tasks and outperform existing algorithms as the number of tasks increases. We also show that the time line can be used to solve specific scheduling problems.

关键词： Scheduling Global constraint filtering algorithms Disjunctive Cumulative Data structure

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Evaluation of speckle noise MAP filtering algorithms applied to SAR images

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INTERNATIONAL JOURNAL OF REMOTE SENSING 2003年第24期24卷 5197-5218页

作者： Medeiros, FNS Mascarenhas, NDA Costa, LF Univ Fed Sao Carlos DC BR-13565905 Sao Carlos SP Brazil Univ Fed Ceara DETI BR-60455760 Fortaleza Ceara Brazil Univ Sao Paulo IFSC Cybernet Vis Grp BR-13560970 Sao Carlos SP Brazil

This work proposes new speckle reduction filters for multi-look, amplitude-detected Synthetic Aperture Radar (SAR) images based on the maximum a posteriori (MAP) approach and compares their performance. The new filters use an adaptive approach based on the one-dimensional k -means clustering algorithm over the variance ratio and also a region-growing procedure. The trade-off between the loss of radiometric resolution and edge preservation is evaluated in the filtered images. In order to obtain quantitative measures of the speckle reduction and of the edge blurring, we used some parameters such as the classical equivalent number of looks and the Hough transform. Experiments have been carried out with natural images corrupted with synthetic speckle noise following the Rayleigh and square root of gamma distributions and with real SAR images.

关键词： Gamma Distribution Synthetic aperture radar Square root Radar polarimetry filtering algorithms speckle noise Rayleigh Rescue radiometric resolution Specific absorption rate

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Efficient filtering algorithms for Location-Aware Publish/Subscribe

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2015年第4期27卷 950-963页

作者： Yu, Minghe Li, Guoliang Wang, Ting Feng, Jianhua Gong, Zhiguo Tsinghua Univ Tsinghua Natl Lab Informat Sci & Technol TNList Dept Comp Sci Beijing 100084 Peoples R China Univ Macau Dept Comp & Informat Sci Macau 3974465 Peoples R China

Location-based services have been widely adopted in many systems. Existing works employ a pull model or user-initiated model, where a user issues a query to a server which replies with location-aware answers. To provide users with instant replies, a push model or server-initiated model is becoming an inevitable computing model in the next-generation location-based services. In the push model, subscribers register spatio-textual subscriptions to capture their interests, and publishers post spatio-textual messages. This calls for a high-performance location-aware publish/subscribe system to deliver publishers' messages to relevant subscribers. In this paper, we address the research challenges that arise in designing a location-aware publish/subscribe system. We propose an R-tree based index by integrating textual descriptions into R-tree nodes. We devise efficient filtering algorithms and effective pruning techniques to achieve high performance. Our method can support both conjunctive queries and ranking queries. We discuss how to support dynamic updates efficiently. Experimental results show our method achieves high performance which can filter 500 messages in a second for 10 million subscriptions on a commodity computer

关键词： Location based services Messages Location awareness HIGH-PERFORMANCE filtering algorithms instant Servers tree nodes Publishers Subscriptions

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Optimal and efficient filtering algorithms for table constraints

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CONSTRAINTS 2014年第1期19卷 77-120页

作者： Mairy, Jean-Baptiste Van Hentenryck, Pascal Deville, Yves Catholic Univ Louvain Dept Comp Sci & Engn ICTEAM B-1348 Louvain Belgium NICTA Canberra ACT 2601 Australia Australian Natl Univ Canberra ACT 2601 Australia

filtering algorithms for table constraints can be classified in two categories: constraint-based and value-based. In the constraint-based approaches, the propagation queue only contains information on the constraints that must be reconsidered. For the value-based approaches, the propagation queue also contains information on the removed values. This paper proposes five efficient value-based algorithms for table constraints. Two of them (AC5TCOpt-Tr and AC5TCOpt-Sparse) are proved to have an optimal time complexity of O(r center dot t+r center dot d) per table constraint. Substantial experimental results are presented. An empirical analysis is conducted on the effect of the arity of the tables. The experiments show that our propagators are the best when the arity of the table is 3 or 4. Indeed, on instances containing only binary constraints, our algorithms are outperformed by classical AC algorithm AC3rm. AC3rm is dedicated to binary constraints. However, all our algorithms outperform existing state-of-the-art constraint based STR2+ and MDD (c) and the optimal value-based STR3 algorithms on those instances. On instances with small arity tables (up to arity 4), all our algorithms are generally faster than STR2+, MDD (c) and than STR3. AC5TCOpt-Sparse is globally the best propagator on those benchmarks. On benchmarks containing large arity tables (arity 5 or more), each of the three existing state-of-the-art algorithms is the winning strategy on one different benchmark.

关键词： Propagation Consistency filtering algorithms Table constraints

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