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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.

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...

Abstract — This paper considers the problems of channel estimation and adaptive equalization in the novel framework of set-membership parameter estimation. Channel estimation using a class of set-membership identification algorithms known as optimal bounding ellipsoid (OBE) algorithms and their extension to track time-varying channels are described. Simulation results show that the OBE channel estimators outperform the leastmean-square (LMS) algorithm and perform comparably with the RLS and the Kalman filter. The concept of set-membership 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 updator-shared scheme in a multiple channel environment, referred to as updator-shared parallel adaptive equalization (U-SHAPE). U-SHAPE 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.

. Hybrid control systems contain two distinct types of systems, continuous state and discrete-state, 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. ? The partial financial support of the National Science Foundation (...

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 set-membership 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, set-membership estimation, watermarking security. I.

. 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...

Earlier research has shown that the use of set-membership 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 U-SHAPE, 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 ever-increasing 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...

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 (Set-Membership Adaptive Recursive Techniques) is presented. We show that the class of Optimal Bounding Ellipsoid (OBE) algorithms belong to SMART. An NLMS-like algorithm that features linear complexity and an adaptive step-size 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 mean-square criterion and the deterministic least-squares criterion. In many applications, however, the designer has a priori knowledge about the physical syste...

We consider worst-case l 1 identification of causal linear shift-invariant 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. Notation R; R+ the reals, and the nonnegative reals, respectively. Z+ the set of positive integers. R n the set of all n-tuples of real numbers. l 1 the normed space of sequences x = fx k 2 Rg k0 with the norm kxk1 = sup k0 jx k j ! 1. l 1 the normed space of sequences x = fx k 2 Rg k0 with the norm kxk 1 = P k0 jx k j ! 1. We shall use the notation l 1 also for bounded sequence spaces for which the integer-valued indexing set can be put into one-to-one correspondence with the set of natural numbers f0g [ Z+ . 1 Introduction This paper is concerned with worst-case l 1 identifica...