The authors present a general approach to determining the number of sinusoids present in measurements corrupted by additive white Gaussian and nonGaussian noise. The approach involves the simultaneous application of m...
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The authors present a general approach to determining the number of sinusoids present in measurements corrupted by additive white Gaussian and nonGaussian noise. The approach involves the simultaneous application of maximum a posteriori detection and nonlinear estimation using either the extended Kalman filter when the noise is Gaussian, or the extended high order filter when the noise is nonGaussian. The problem is formulated as a multiple hypothesis testing problem with assumed known a priori probabilities for each hypothesis. The advantage of the approach lies in the potential to accommodate time-varying as well as time-invariant parameters in the measurement model. Experimental evaluation of the approach demonstrates excellent performance in selecting the correct model order and estimating the system parameters even for signal-to-noise ratios as low as -5 dB.< >
A nonlinear adaptive detector/estimator is introduced for single and multiple radar data processing. The problem of target detection from returns of monostatic radar(s) is formulated as a nonlinear joint detection/est...
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A nonlinear adaptive detector/estimator is introduced for single and multiple radar data processing. The problem of target detection from returns of monostatic radar(s) is formulated as a nonlinear joint detection/estimation problem on the unknown parameters in the signal return. The problems of detecting the target and estimating its parameters are considered jointly. A bank of spatially and temporally localized nonlinear filters is used to estimate the a posteriori likelihood of the existence of the target in a given space-time resolution cell. Within a given cell, the localized filters are used to produce refined spatial estimates of the target parameters. A decision logic is used to decide on the existence of a target within any given resolution cell based on the a posteriori estimates obtained from the likelihood functions. Simulation results show excellent detection capabilities and excellent resolution in target parameter estimation for both single and multiple sensor data.< >
The authors address the problem of high-resolution parameter estimation of superimposed sinusoids using nonlinear filtering techniques. Six separate nonlinear filters are evaluated for the estimation of the parameters...
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The authors address the problem of high-resolution parameter estimation of superimposed sinusoids using nonlinear filtering techniques. Six separate nonlinear filters are evaluated for the estimation of the parameters of sinusoids in white and colored Gaussian noise. Experimental evaluation demonstrates that the nonlinear filters perform very satisfactorily (close to the Cramer-Rao bound) for reasonable values of the initial estimation error. A major advantage of using nonlinear filtering methods for harmonic retrieval is that the filters can be applied to time-varying process models as well.< >
A number of robust stability problems take the following form: A polynomial has real coefficients wvhich are multiaffine in real parameters that are confined to a box in parameter space. An efficient method is require...
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A number of robust stability problems take the following form: A polynomial has real coefficients wvhich are multiaffine in real parameters that are confined to a box in parameter space. An efficient method is required for checking the stability of this set of polynomials. We present two sufficient conditions in this paper. They involve: checking certain properties at the corners and edges of the parameter space box.
An effective method for visual pattern recognition using morphological techniques is presented. It is shown that it can be successfully used for the recognition of deformed letters. The method extracts morphological i...
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An effective method for visual pattern recognition using morphological techniques is presented. It is shown that it can be successfully used for the recognition of deformed letters. The method extracts morphological information by the successive dilation of an idealized letter set. At each stage a properly defined similarity index is computed. The maximum values of the similarity index for each stored letter are compared and are used for the classification decision. Classification results are presented for a set of deformed capital English letters with a realistic level of deformation. Skeletonization of the deformed pattern is shown to improve the performance of the classification method. The described method can be easily implemented using a parallel architecture.< >
作者:
Theocharis, J.Petridis, V.Dr.-Ing. John Theocharis (1956) graduated as an Electrical Engineer from Aristotelian University of Thessaloniki.Greece
in 1980. From 1980 to 1985 he has been with the scientific staff of the Department of Electrical Engineering at the Aristotelian University where he received the Ph.D. degree in 1985. Since 1986 he is working as a lecturer and in 1990 he became assistant professor at the Department of Electronics and Computer Engineering in the m e university. His research activities include control power electronics and electrical motor drives. Recently he is working with the Neural Network Systems with applications to field oriented control problems. Aristotelian University of Thessaloniki School of Engineering Faculty of Electrical Engineering Dept. of Electronics & Computer Engineering P.O. Box 438 GR-Thessalonikil/Greece.T+3131/219784Fax + 3031/274868) Prof. Dr.-Ing. Vasilis Petridis (1946) graduated from National Technical University of Athens
Greece in 1969.He obtained the M.Sc. and the Ph.D. in electronics and systems from the University of London in 1970 and 1974. respectively. H i s interests include applied automatic control neural networks drives dynamic systems robotics etc. He is currently professor in the Department of Electronics and Computer Engineering of the University of Thessaloniki. (Aristotelian University of Thessaloniki. School of EngineeringFaculty of Electrical Engineering Dept. of Electronics & Computer Engineering P.O. Box 438. GR-ThessaloniW Greece T+3031/219784.Fax+3031/274868)
The procedure of harmonic insertion is generalized in this paper. Analytical expressions of the voltage spectra are derived. The insertion of the 3rd harmonic to the modulating signal, which is of particular interest,...
Application of the certainty equivalence principle in the dynamic control problem of an unstable random access (RA) channel results in a nonlinear separation control rule which can be implemented in a decentralized fa...
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Application of the certainty equivalence principle in the dynamic control problem of an unstable random access (RA) channel results in a nonlinear separation control rule which can be implemented in a decentralized fashion and yields maximum stable throughout e-1. Stability of the controlled RA channel is proven by showing that the channel backlog and its least squares estimate from an ergodic double Markov chain. Tight upper and lower bounds on the invariant probability distribution are also derived when the backlog is precisely known. The bounds are loglinear functions of the channel backlog and can be readily used to compute bounds on the average backlog and delay in the RA channel. An adaptive realization of the control is introduced for an RA channel with unknown traffic rates. Extensive simulation results are provided and the performance of our control is compared with other existing distributed controls.
A method of reference model decomposition, an extension of model reference adaptive control, is presented. The decomposition method can be regarded as a way of including knowledge about the structure and parameters of...
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A method of reference model decomposition, an extension of model reference adaptive control, is presented. The decomposition method can be regarded as a way of including knowledge about the structure and parameters of unmodeled dynamics in the adaptive system, making it possible to choose a lower order controller which is only equipped for the nominal process part. To illustrate the decomposition method, an adaptive controller for a scale model of a gantry crane is presented. Simplifying and linearizing the mathematical equations describing the crane yields a fourth-order model, of which the dynamics of the load swing take two. A standard adaptive control algorithm needs eight parameters, which in practice yields unacceptable behavior. The decomposition method allows the use of only two adjustable parameters, and real-time experiments showing practical results obtained with the method are described.< >
This survey discusses current approaches to the robust control of the motion of rigid robots and summarizes the available literature on the subject. The five major designs discussed are the “Linear-Multivariable” ap...
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