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DETERMINANT MAXIMIZATION WITH LINEAR MATRIX INEQUALITY CONSTRAINTS
"... The problem of maximizing the determinant of a matrix subject to linear matrix inequalities arises in many fields, including computational geometry, statistics, system identification, experiment design, and information and communication theory. It can also be considered as a generalization of the s ..."
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Cited by 183 (18 self)
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The problem of maximizing the determinant of a matrix subject to linear matrix inequalities arises in many fields, including computational geometry, statistics, system identification, experiment design, and information and communication theory. It can also be considered as a generalization of the semidefinite programming problem. We give an overview of the applications of the determinant maximization problem, pointing out simple cases where specialized algorithms or analytical solutions are known. We then describe an interiorpoint method, with a simplified analysis of the worstcase complexity and numerical results that indicate that the method is very efficient, both in theory and in practice. Compared to existing specialized algorithms (where they are available), the interiorpoint method will generally be slower; the advantage is that it handles a much wider variety of problems.
Estimation of Model Quality
 Automatica
, 1994
"... This paper gives an introduction to recent work on the problem of quantifying errors in the estimation of models for dynamic systems. This is a very large field. We therefore concentrate on approaches that have been motivated by the need for reliable models for control system design. This will invol ..."
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Cited by 29 (7 self)
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This paper gives an introduction to recent work on the problem of quantifying errors in the estimation of models for dynamic systems. This is a very large field. We therefore concentrate on approaches that have been motivated by the need for reliable models for control system design. This will involve a discussion of efforts which go under the titles of `Estimation in H1 ', `Worst Case Estimation', `Estimation in ` 1 ', `Information Based Complexity', and `Stochastic Embedding of Undermodelling'. A central theme of this survey is to examine these new methods with reference to the classic bias/variance tradeoff in model structure selection. Technical Report EE9437 Centre for Industrial Control Science and Department of Electrical and Computer Engineering, University of Newcastle, Callaghan 2308, AUSTRALIA 1 Introduction Our aim in this paper is to survey an area of research which has flourished in recent years. The common denominator of this work is that of finding system identificat...
The Role of Model Validation for Assessing the Size of the Unmodeled Dynamics
 IEEE TRANSACTIONS ON AUTOMATIC CONTROL
, 1997
"... The problem of assessing the quality of a given, or estimated model is a central issue in system identification. Various new techniques for estimating bias and variance contributions to the model error have been suggested in the recent literature. In this contribution, classical model validation pro ..."
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Cited by 28 (6 self)
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The problem of assessing the quality of a given, or estimated model is a central issue in system identification. Various new techniques for estimating bias and variance contributions to the model error have been suggested in the recent literature. In this contribution, classical model validation procedures are placed at the focus of our attention. We discuss the principles by which we reach confidence in a model through such validation techniques, and also how the distance to a "true" description can be estimated this way. In particular, we stress how the typical model validation procedure gives a direct measure of the model error of the model test, without referring to its ensemble properties. Several model error bounds are developed for various assumptions about the disturbances entering the system.
Setmembership adaptive equalization and an updatorshared implementation for multiple channel communication systems
 IEEE Trans. Signal Processing
, 1998
"... Abstract — This paper considers the problems of channel estimation and adaptive equalization in the novel framework of setmembership parameter estimation. Channel estimation using a class of setmembership identification algorithms known as optimal bounding ellipsoid (OBE) algorithms and their exte ..."
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Cited by 16 (9 self)
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Abstract — This paper considers the problems of channel estimation and adaptive equalization in the novel framework of setmembership parameter estimation. Channel estimation using a class of setmembership identification algorithms known as optimal bounding ellipsoid (OBE) algorithms and their extension to track timevarying channels are described. Simulation results show that the OBE channel estimators outperform the leastmeansquare (LMS) algorithm and perform comparably with the RLS and the Kalman filter. The concept of setmembership equalization is introduced along with the notion of a feasible equalizer. Necessary and sufficient conditions are derived for the existence of feasible equalizers in the case of linear equalization for a linear FIR additive noise channel. An adaptive OBE algorithm is shown to provide a set of estimated feasible equalizers. The selective update feature of the OBE algorithms is exploited to devise an updatorshared scheme in a multiple channel environment, referred to as updatorshared parallel adaptive equalization (USHAPE). USHAPE is shown to reduce hardware complexity significantly. Procedures to compute the minimum number of updating processors required for a specified quality of service are presented. I.
Security of latticebased data hiding against the Known Message Attack
 IEEE Transactions on Information Forensics and Security
, 2006
"... Abstract—Security of quantization index modulation (QIM) watermarking methods is usually sought through a pseudorandom dither signal which randomizes the codebook. This dither plays the role of the secret key (i.e., a parameter only shared by the watermarking embedder and decoder), which prevents un ..."
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Cited by 13 (8 self)
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Abstract—Security of quantization index modulation (QIM) watermarking methods is usually sought through a pseudorandom dither signal which randomizes the codebook. This dither plays the role of the secret key (i.e., a parameter only shared by the watermarking embedder and decoder), which prevents unauthorized embedding and/or decoding. However, if the same dither signal is reused, the observation of several watermarked signals can provide sufficient information for an attacker to estimate the dither signal. This paper focuses on the cases when the embedded messages are either known or constant. In the first part of this paper, a theoretical security analysis of QIM data hiding measures the information leakage about the secret dither as the mutual information between the dither and the watermarked signals. In the second part, we show how setmembership estimation techniques successfully provide accurate estimates of the dither from observed watermarked signals. The conclusion of this twofold study is that current QIM watermarking schemes have a relative low security level against this scenario because a small number of observed watermarked signals yields a sufficiently accurate estimate of the secret dither. The analysis presented in this paper also serves as the basis for more involved scenarios. Index Terms—Equivocation, lattice data hiding, mutual information, quantization index modulation, setmembership estimation, watermarking security. I.
Hybrid System Modeling and Event Identification
, 1993
"... Hybrid control systems contain two distinct types of systems, continuous state and discretestate, that interact with each other. Their study is essential in designing sequential supervisory controllers for continuousstate systems, and it is central in designing control systems with high degree of ..."
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Cited by 10 (2 self)
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Hybrid control systems contain two distinct types of systems, continuous state and discretestate, that interact with each other. Their study is essential in designing sequential supervisory controllers for continuousstate systems, and it is central in designing control systems with high degree of autonomy. After an introduction to intelligent autonomous control and its relation to hybrid control, models for the plant, controller, and interface are introduced. The important role of the interface is discussed at length. System theoretic issues are addressed and the concepts of determinism and quasideterminism are introduced and studied. The relation to the theory of logical discrete event systems is shown and discussed. When the system changes, online identification supervisory control is desirable. To meet the demanding computing requirements, event identification is performed using inductive inference algorithms.
Learning to be Autonomous: Intelligent Supervisory Control
 Intelligent Control Systems: Theory and Applications
, 1993
"... . A brief introduction to the main ideas in Autonomous Control Systems is first given and certain important issues in modeling, analysis and design are discussed. Control systems with high degree of autonomy should perform well under significant uncertainties in the system and environment for extend ..."
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Cited by 6 (4 self)
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. A brief introduction to the main ideas in Autonomous Control Systems is first given and certain important issues in modeling, analysis and design are discussed. Control systems with high degree of autonomy should perform well under significant uncertainties in the system and environment for extended periods of time, and they must be able to compensate for certain system failures without external intervention. Highly autonomous control systems evolve from conventional control systems by adding intelligent components, and their development requires interdisciplinary research. A working characterization of intelligent controllers is introduced and it is argued that the supervisory controller discussed here, which can learn events, is indeed intelligent. There are problems in Autonomous Control Hybrid control systems are of great importance in the development of autonomous control and they are discussed extensively. An appropriate hybrid system model is first introduced and it is used to...
Smart: A Toolbox For SetMembership Filtering
 Proc. 1997 European Conf. Circuit Theory and Design
, 1997
"... This paper presents the concept of SetMembership Filtering (SMF), an extension of SetMembership Identification (SMI) theory to the general filtering problem. A toolbox of adaptive solutions called SMART (SetMembership Adaptive Recursive Techniques) is presented. We show that the class of Optimal Bo ..."
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Cited by 4 (0 self)
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This paper presents the concept of SetMembership Filtering (SMF), an extension of SetMembership Identification (SMI) theory to the general filtering problem. A toolbox of adaptive solutions called SMART (SetMembership Adaptive Recursive Techniques) is presented. We show that the class of Optimal Bounding Ellipsoid (OBE) algorithms belong to SMART. An NLMSlike algorithm that features linear complexity and an adaptive stepsize is also derived as a member of SMART. I. INTRODUCTION Conventional filtering involves determining, or estimating, the filter parameters by optimizing a cost function defined on the parameter space. The choice of the cost function is usually made to facilitate analytical and computational simplicity, rather than to reflect desired performance and a priori knowledge. Examples include the stochastic least meansquare criterion and the deterministic leastsquares criterion. In many applications, however, the designer has a priori knowledge about the physical syste...
WorstCase InputOutput Identification
 INT. J. CONTROL
, 1992
"... We consider worstcase l¹ identification of causal linear shiftinvariant systems from time series. Many results are given on general aspects of identification algorithm performance, existence of optimal algorithms, robust convergence, and input (experiment) design. The identification methodology st ..."
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Cited by 4 (0 self)
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We consider worstcase l¹ identification of causal linear shiftinvariant systems from time series. Many results are given on general aspects of identification algorithm performance, existence of optimal algorithms, robust convergence, and input (experiment) design. The identification methodology studied here is compatible with the modelling requirements of modern robust control design.
UpdatorShared Adaptive Parallel Equalization (UShAPE) Using SetMembership Identification
 Proc. IEEE Intl. Symp. Circuits and Systems, Atlanta, GA
, 1996
"... Earlier research has shown that the use of setmembership identification (SMI) in adaptive equalization of multipath fading channels results in bit error rate performance comparable to that obtained using the recursive least squares (RLS) algorithm while not requiring to update the equalizer paramet ..."
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Cited by 3 (3 self)
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Earlier research has shown that the use of setmembership identification (SMI) in adaptive equalization of multipath fading channels results in bit error rate performance comparable to that obtained using the recursive least squares (RLS) algorithm while not requiring to update the equalizer parameters at every instant of time. The discerning update strategy of the SMI methodology is exploited in this paper to develop a scheme, referred to here as USHAPE, which shares the processors that update equalizer tap coefficients, resulting in a significant reduction in the hardware requirements of a multiaccess channel equalizer. 1. INTRODUCTION The everincreasing demand for high quality wireless communication services to a large number of users has created a need for novel signal processing techniques to combat distortion in wireless digital communication systems. Adaptive equalization is a common approach to mitigate the effect of multipath fading and the resulting intersymbol interferenc...