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Evaluation of estimation algorithms. Part 1: Incomprehensive measures of performance

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2006年第4期42卷 1340-1358页

作者： Li, X. Rong Zhao, Zhanlue Univ New Orleans Dept Elect Engn New Orleans LA 70148 USA

Practical metrics for performance evaluation of estimation algorithms are discussed. A variety of metrics useful for evaluating various aspects of the performance of an estimation algorithm is introduced and justified. They can be classified in two different ways: 1) absolute error measures (without a reference), relative error measures (with a reference), or frequency counts (of some events), and 2) optimistic (i.e., how good the performance is), pessimistic (i.e., how bad the performance is), or balanced (neither optimistic nor pessimistic). Pros and cons of these metrics and the widely-used RMS error are explained. The paper advocates replacing the RMS error in many cases by a measure called average Euclidean error.

关键词： error statistics estimation theory RMS error absolute error measures average Euclidean error estimation algorithms frequency counts incomprehensive performance measures optimistic performance pessimistic performance relative error measures Performance metrics algorithms ROOT-MEAN-SQUARE ERRORS Pessimism Error measure estimation theory

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State-space stochastic volatility models: A review of estimation algorithms

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APPLIED STOCHASTIC MODELS AND DATA ANALYSIS 1996年第4期12卷 265-279页

作者： Capobianco, E Department of Statistical Sciences University of Padua Italy

Stochastic volatility models (SVMs) represent an important framework for the analysis of financial time series data, together with ARCH-type models;but unlike the latter, the former, at least from the statistical point of view, cannot rely on the possibility of obtaining exact inference, in particular with regard to maximum likelihood estimates for the parameters of interest. For SVMs, usually only approximate results can be obtained, unless particularly sophisticated estimation strategies like exact non-gaussian filtering methods or simulation techniques are employed. In this paper we review SVM and present a new characterization for them, called 'generalized bilinear stochastic volatility'.

关键词： stochastic volatility linear and nonlinear state space representation simulation techniques generalized bilinear stochastic volatility processes estimation algorithms

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SENSITIVITY ANALYSIS OF DOA estimation algorithms TO SENSOR ERRORS

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 1992年第3期28卷 708-717页

作者： LI, F VACCARO, RJ UNIV RHODE ISL DEPT ELECT ENGN KINGSTON RI 02881 USA

A unified statistical performance analysis using subspace perturbation expansions is applied to subspace-based algorithms for direction-of-arrival (DOA) estimation in the presence of sensor errors. In particular, the multiple signal classification (MUSIC), min-norm, state-space realization (TAM and DDA) and estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithms are analyzed. This analysis assumes that only a finite amount of data is available. An analytical expression for the mean-squared error of the DOA estimates is developed for theoretical comparison in a simple and self-contained fashion. The tractable formulas provide insight into the algorithms. Simulation results verify the analysis.

关键词： .Sensitivity Analysis DOA estimates matrix-pencil ESPRIT estimation algorithms min-norm Sensor Errors presence of sensor estimation of signal

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Correct algebras over estimation algorithms in the set of regular recognition problems with nonoverlapping classes

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COMPUTATIONAL MATHEMATICS AND MATHEMATICAL PHYSICS 2009年第7期49卷 1264-1275页

作者： Maksimov, Yu. V. Moscow Inst Phys & Technol Dolgoprudnyi 141700 Moscow Oblast Russia

Algebras over estimation algorithms in the set of regular problems with nonoverlapping classes are considered. A correctness criterion for the arbitrary degree algebraic closure of the model of estimation algorithms in the classification problems of this type is proposed;this criterion can be efficiently verified. An estimate of the minimal degree of the algebraic closure that is sufficient for constructing a correct classifier in an arbitrary regular problem with nonoverlapping classes is found.

关键词： classification problems algebraic approach estimation algorithms correct algorithms

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A finite-difference method for linearization in nonlinear estimation algorithms

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AUTOMATICA 1997年第11期33卷 2053-2058页

作者： Schei, TS SINTEF Elect & Cybernet N-7034 Trondheim Norway

Linearizations of nonlinear functions that are based on Jacobian matrices often cannot be applied in practical applications of nonlinear estimation techniques. An alternative linearization method is presented in this paper. The method assumes that covariance matrices are determined on a square root factored form. A factorization of the output covariance from a nonlinear vector function is directly determined by "perturbing" the nonlinear function with the columns of the factored input covariance, without explicitly calculating the linearization and with no differentiations involved. The output covariance is more accurate than that obtained with the ordinary Jacobian linearization method. It also has an advantage that Jacobian matrices do not have to be derived symbolically. (C) 1997 Elsevier Science Ltd.

关键词： covariance matrices estimation algorithms extended Kalman filters factorization methods nonlinear filters Jacobian matrices linearization parameter estimation recursive estimation state estimation

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Quasi coherent overlapping procedure to improve harmonics suppression using single tone estimation algorithms

Quasi coherent overlapping procedure to improve harmonics su...

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Conference on Precision Electromagnetic Measurements (CPEM)

作者： Lapuh, Rado Voljc, Bostjan Kokalj, Miha Lindic, Matjaz Svetik, Zoran Slovenian Inst Qual & Metrol Ljubljana Slovenia Metrol Inst Republ Slovenia Celje Slovenia

ISBN: (纸本)9781467391344

This paper describes the procedure to reduce an estimation bias of interpolated DFT and single-model sine-fit algorithms. estimation bias reduction of more than an order of magnitude is attainable. The procedure does not modify the estimation algorithm itself and additional knowledge of the measurement system or additional sampled points are not required.

关键词： Measurement sampling estimation algorithms harmonic distortion estimation error uncertainty

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Comparative Study of estimation algorithms for Predistorter Coefficients of GaN Power Amplifier 4th

Comparative Study of Estimation Algorithms for Predistorter ...

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4th International Symposium on Ubiquitous Networking (UNet)

作者： Rezgui, Haithem Rouissi, Fatma Ghazel, Adel Univ Carthage GRESCOM Lab SUP COM Cite Technol Commun Ariana Tunisia

ISBN: (纸本)9783030028497;9783030028480

The purpose of this paper is to compare two estimation methods when identifying the coefficients of the Simplified Volterra Series (SVS) model, in order to linearize a class AB GaN Power Amplifier (PA) driven by a 20-MHz LTE-A signal. First, a Digital Predistorter (DPD) design using the cholesky decomposition based inversion method and the Least Square QR (LSQR) algorithm is carried out, and next the performances of each method are analyzed in terms of computational complexity and suppressing distortions capability. The co-simulation test results show that the LSQR performs better than Cholesky decomposition in terms of Adjacent Channel Power Ratio (ACPR) and Normalized Mean Square Error (NMSE) by a margin of 3 dB and 4 dB, receptively.

关键词： RF power amplifier Digital predistortion Volterra series estimation algorithms Look-up table (LUT)

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A versatile sonar simulation platform for testing seabed estimation algorithms

A versatile sonar simulation platform for testing seabed est...

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8th Middle Eastern Simulation Multiconference

作者： Swadi, Ghedhban Rafik, Tahseen Jordanov, Ivan Univ Wales Inst Sch Prod & Engn Design Cardiff Western Ave Llandaff CF5 2YB Wales

ISBN: (纸本)9789077381281

This paper describes a simulation model of a sonar seabed mapping system based on echo sounder. The purpose of this simulation is to study the performance of linear predictors of different orders in estimating the future values of seabed depths. The simulated system consists of random seabed generator, echo sounder simulated signal generator and a predictor. The beam width of the echo sounder and the order of the estimator can be selected by the user. Labview and Matlab were used to build the simulation model. Results showed that a second order predictor gives the best results.

关键词： seabed mapping high resolution sonar estimation algorithms

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Developing Inferential estimation algorithms using Genetic Programming

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IFAC Proceedings Volumes 1997年第9期30卷 209-214页

作者： M.J. Willis H.G. Hiden G.A. Montague Dept. Chemical & Process Engineering Newcastle University NEI 7RU United Kingdom

In this contribution, Genetic Programming (GP) is used to develop inferential estimation models using experimental data. GP performs symbolic optimisation, automatically determining both the structure and the complexity of an empirical model. After a tutorial example, the usefulness of the technique is demonstrated by the development of an inferential estimation model of a plasticating extruder. A statistical analysis procedure is used as a guide in the selection of the final model structure. For the industrial case study, the inferential models obtained using the GP algorithm are compared to those obtained using a linear, finite impulse response model and a feedforward artificial neural network (FANN). For this application, the GP technique produces models with a significantly lower Root Mean Square (RMS) error than the other techniques.

关键词： estimation algorithms Genetic algorithms Modelling Extrusion Neural Networks

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Evaluating the Performance of Joint Angle estimation algorithms on an Exoskeleton Mock-Up via a Modular Testing Approach

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SENSORS 2024年第17期24卷 5673页

作者： Pollard, Ryan S. Bass, Sarah M. Schall Jr, Mark C. Zabala, Michael E. Auburn Univ Dept Mech Engn Auburn AL 36849 USA Auburn Univ Dept Ind & Syst Engn Auburn AL 36849 USA

A common challenge for exoskeleton control is discerning operator intent to provide seamless actuation of the device with the operator. One way to accomplish this is with joint angle estimation algorithms and multiple sensors on the human-machine system. However, the question remains of what can be accomplished with just one sensor. The objective of this study was to deploy a modular testing approach to test the performance of two joint angle estimation models-a kinematic extrapolation algorithm and a Random Forest machine learning algorithm-when each was informed solely with kinematic gait data from a single potentiometer on an ankle exoskeleton mock-up. This study demonstrates (i) the feasibility of implementing a modular approach to exoskeleton mock-up evaluation to promote continuity between testing configurations and (ii) that a Random Forest algorithm yielded lower realized errors of estimated joint angles and a decreased actuation time than the kinematic model when deployed on the physical device.

关键词： exoskeleton mock-up estimation algorithms random forest kinematics single sensor joint angles

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