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Laguerre based predictors in discrete-time recursive algorithms: A solution for open-loop identification under oversampling

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IFAC-PapersOnLine 2017年第1期50卷 12911-12918页

作者： Vau, Bernard Bourlès, Henri SATIE Ecole normale supérieure de Cachan Cachan94230 France

In this paper we propose a novel formulation of the predictor used in open-loop recursive identification algorithms. The predicted output is expressed by means of an orthogonal Laguerre transfer functions basis. This predictor representation presents many advantages: It makes it possible to identify robustly oversampled systems without any bias in low frequency, and to obtain relevant reduced order models. The Laguerre pole plays the role of a tuning parameter enabling the selection of the best approximation frequency area. The proposed schemes address both output error and ARMAX systems. Simulation and experimental results show all the practical benefits provided by these algorithms. © 2017

关键词： Transfer functions Orthogonal functions Adaptive Control ARMAX model identification algorithms Laguerre Output error models Recursive algorithms Recursive estimation

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Laguerre based predictors in discrete-time recursive algorithms: A solution for open-loop identification under oversampling

Laguerre based predictors in discrete-time recursive algorit...

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20th World Congress of the International-Federation-of-Automatic-Control (IFAC)

作者： Vau, Bernard Bourles, Henri SATIE Ecole Normale Super Cachan F-94230 Cachan France

In this paper we propose a novel formulation of the predictor used in open-loop recursive identification algorithms The predicted output is expressed by means of an orthogonal Laguerre transfer functions basis. This predictor representation presents many advantages: It makes it possible to identify robustly oversampled systems without any bias in low frequency, and to obtain relevant reduced order models. The Laguerre pole plays the role of a tuning parameter enabling the selection of the best approximation frequency area. The proposed schemes address both output error and ARMAX systems. Simulation and experimental results show all the practical benefits provided by these algorithms (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： identification algorithms recursive algorithms recursive estimation output error model identification ARMAX model identification Laguerre transfer functions adaptive control

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Evaluation of the algorithms of Face identification 2

Evaluation of the Algorithms of Face Identification

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2nd International Conference on Knowledge Based Engineering and Innovation (KBEI)

作者： Hashemi, Seyyed Mohammad Reza Faridpour, Maryam Islamic Azad Univ Qazvin Branch Young Researchers & Elite Club Qazvin Iran Comp & Stat Expert Semnan Municipal Semnan Iran

ISBN: (纸本)9781467365062

The need to identify and discern identities gradually rises in social and economic interactions along with following the rules and other fields. Accordingly, biometric data as basic information of an individual's physical and behavioral features play an important role. This article reviews the duties of face recognition, thence to make a comparison among the function of five face-recognition algorithm, called PCA, ICA, FLDA, Eigen features, and Eigen face, in which the basis for comparing these algorithms was the rate of face identification accuracy. The mentioned algorithms have been analyzed in the databases of ORL, AR, FERET, and YALE. This article shows that ICA Algorithm give better results than the other algorithms in the introduced databases.

关键词： Face ICA ORL identification algorithms Evaluation Introduction

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Utilization of advanced clutter suppression algorithms for improved standoff detection and identification of radionuclide threats

Utilization of advanced clutter suppression algorithms for i...

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SPIE Defense, Security + Sensing Symposium / 15th Annual Meeting on Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing

作者： Cosofret, Bogdan R. Shokhirev, Kirill Mulhall, Phil Payne, David Harris, Bernard Phys Sci Inc 20 New England Business Ctr Andover MA 01810 USA BRaytheon Integrated Def Syst Tewksbury MA USA

ISBN: (纸本)9781628410105

Technology development efforts seek to increase the capability of detection systems in low Signal-to-Noise regimes encountered in both portal and urban detection applications. We have recently demonstrated significant performance enhancement in existing Advanced Spectroscopic Portals (ASP), Standoff Radiation Detection Systems (SORDS) and handheld isotope identifiers through the use of new advanced detection and identification algorithms. The Poisson Clutter Split (PCS) algorithm is a novel approach for radiological background estimation that improves the detection and discrimination capability of medium resolution detectors. The algorithm processes energy spectra and performs clutter suppression, yielding de-noised gamma-ray spectra that enable significant enhancements in detection and identification of low activity threats with spectral target recognition algorithms. The performance is achievable at the short integration times (0.5 - 1 second) necessary for operation in a high throughput and dynamic environment. PCS has been integrated with ASP, SORDS and RIID units and evaluated in field trials. We present a quantitative analysis of algorithm performance against data collected by a range of systems in several cluttered environments (urban and containerized) with embedded check sources. We show that the algorithm achieves a high probability of detection/identification with low false alarm rates under low SNR regimes. For example, utilizing only 4 out of 12 Nal detectors currently available within an ASP unit, PCS processing demonstrated P-d,P-ID > 90% at a CFAR (Constant False Alarm Rate) of 1 in 1000 occupancies against weak activity (7 - 8 mu Ci) and shielded sources traveling through the portal at 30 mph. This vehicle speed is a factor of 6 higher than was previously possible and results in significant increase in system throughput and overall performance.

关键词： radionuclide identification algorithms standoff detection clutter suppression

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Multivariable identification of an Activated Sludge Process with Subspace-Based algorithms

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IFAC Proceedings Volumes 2001年第25期34卷 317-322页

作者： Oscar A.Z. Sotomayor Song Won Park Claudio Garcia LSCP - Dept. of Chemical Engineering Polytechnic School of the University of São Paulo LAC - Dept. of Telecommunications and Control Engineering Polytechnic School of the University of São Paulo Phone: +55-11-3818.2246 Fax: +55-11-3813.2380

This paper deals with the use of subspace-based identification methods, to obtain multi variable linear dynamic models in state-space form of an activated sludge process around an operating point. Different subspace algorithms (such as CVA, N4SID, MOESP, DSR) are used and compared, based on performance quality criteria. The selected model is validated with a data set not used in the identification process and it describes well the complex dynamics of the process. This model is asymptotically stable and it can be used for control and monitoring purposes.

关键词： Subspace methods identification algorithms State-space models Waterpollution Environment engineering

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Efficient algorithms for the Bee-identification Problem

IEEE JOURNAL ON SELECTED AREAS IN INFORMATION THEORY

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IEEE JOURNAL ON SELECTED AREAS IN INFORMATION THEORY 2023年 4卷 205-218页

作者： Kiah, Han Mao Vardy, Alexander Yao, Hanwen Nanyang Technol Univ Sch Phys & Math Sci Singapore Singapore Univ Calif San Diego Dept Elect & Comp Engn La Jolla CA 92093 USA Duke Univ Dept Elect & Comp Engn Durham NC 27705 USA

The bee-identification problem, formally defined by Tandon, Tan, and Varshney (2019), requires the receiver to identify "bees" using a set of unordered noisy measurements. In this previous work, Tandon, Tan, and Varshney studied error exponents and showed that decoding the measurements jointly results in a significantly larger error exponent. In this work, we study algorithms related to this joint decoder. First, we demonstrate how to perform joint decoding efficiently. By reducing to the problem of finding perfect matching and minimum-cost matchings, we obtain joint decoders that run in time quadratic and cubic in the number of "bees" for the binary erasure (BEC) and binary symmetric channels (BSC), respectively. Next, by studying the matching algorithms in the context of channel coding, we further reduce the running times by using classical tools like peeling decoders and list-decoders. In particular, we show that our identifier algorithms when used with Reed-Muller codes terminate in almost linear and quadratic time for BEC and BSC, respectively. Finally, for explicit codebooks, we study when these joint decoders fail to identify the "bees" correctly. Specifically, we provide practical methods of estimating the probability of erroneous identification for given codebooks.

关键词： Bee identification problem joint decoding identification algorithms

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Non-Linear System identification with Multiobjective Genetic algorithms

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IFAC Proceedings Volumes 1996年第1期29卷 1169-1174页

作者： Carlos M. Fonseca Peter J. Fleming Department of Automatic Control and Systems Engineering University of Sheffield Mappin Street Sheffield S1 3JD UK.

In this work, a multiobjective genetic algorithm is applied in the identification of polynomial models for a real non-linear system. The approach is shown to allow multiple performance, complexity, and validity criteria to influence the selection of candidate model structures, leading to the production of various preferable alternatives. The various models produced by the algorithm enable a better informed selection of the final identified model.

关键词： Genetic algorithms multiobjective optimisations identification algorithms polynomial models structural optimization

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identification of Unstructured Mechatronics System Using Genetic algorithms

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IFAC Proceedings Volumes 2000年第26期33卷 487-492页

作者： Makoto Iwasaki Hiromu Hirai Nobuyuki Matsui Dept. of Electrical and Computer Engineering Nagoya Institute of Technology Gokiso Showa Nagoya 4668555 Japan phone: +81-52-735-5455 fax: +81-52-735-5442

Soft computing techniques, e.g., Neural Networks, Fuzzy inference, evolutionary computation, and chaos theory, have been applying to a wide variety of control systems in industry because of their control capability and flexibility. They are also powerful to handle the complicated mechatronics systems with various nonlinearities which are difficult to be modeled as mathematical formulas. This paper presents a novel autonomous algorithm for the identification of unknown structured mechatronics systems using Genetic algorithms (GA), where the optimal order of a system polynomial expression and the optimal set of coefficients for the polynomial can be determined by means of the optimization ability of GA. The effectiveness of the proposed identification can be verified by experiments using the typical mechanical systems with velocity controller.

关键词： identification algorithms Genetic algorithms Optimization Mechanical systems Structural optimization

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A Class of Linear Convergent algorithms for H ∞ identification

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IFAC Proceedings Volumes 1996年第1期29卷 4333-4338页

作者： Shuning Wang Institute of Systems Engineering Huazhong University of Science and Technology Wuhan 430074 P.R.China

In this paper a traditional approach in system identification is adopted to design linear algorithms for H ∞ identification. That is to get the required algorithm by minimizing a tractable cost function which is carefully constructed to measure the performance of all alternatives. By means of this approach, desirable linear convergent algorithms for H ∞ identification with observations in both frequency domain and time domain are presented. The new algorithms are not only very simple in computation, but can also deliver a tight upper bound on the worst-case identification error.

关键词： identification algorithms H ∞ identification worst-case/deterministic approach robust estimation linear algorithms

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Comparison of subspace and ARX models of a waveguide's terahertz transient response after optimal wavelet filtering

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IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES 2004年第10期52卷 2409-2419页

作者： Hadjiloucas, S Galvao, RKH Becerra, VM Bowen, JW Martini, R Brucherseifer, M Pellemans, HPM Bolívar, PH Kurz, H Chamberlain, JM Univ Reading Dept Cybernet Reading RG6 6AY Berks England Inst Tecnol Aeronaut Div Engn Eletron Sao Jose Dos Campos SP Brazil Stevens Inst Technol Dept Phys & Engn Phys Hoboken NJ 07030 USA Georgia Inst Technol Sch Chem & Biochem Appl Sensors Lab Atlanta GA 30332 USA ASML Holding NV NL-5504 DR Veldhoven Netherlands Westfal Tech Hsch Inst Halbleitertech D-52056 Aachen Germany Univ Durham Grey Coll Durham DH1 3LG England

A quasi-optical deembedding technique for characterizing waveguides is demonstrated using wide-band time-resolved terahertz spectroscopy. A transfer function representation is adopted for the description of the signal in the input and output port of the waveguides. The time-domain responses were discretized and the waveguide transfer function was obtained through a parametric approach in the z-domain after describing the system with an AutoRegressive with eXogenous input (ARX), as well as with a state-space model. Prior to the identification procedure, filtering was performed in the wavelet domain to minimize both signal distortion, as well as the noise propagating in the ARX and subspace models. The optimal filtering procedure used in the wavelet domain for the recorded time-domain signatures is described in detail. The effect of filtering prior to the identification procedures is elucidated with the aid of pole-zero diagrams. Models derived from measurements of terahertz transients in a precision WR-8 waveguide adjustable short are presented.

关键词： identification algorithms multimode waveguide characterization signal processing terahertz spectroscopy

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