Results 1  10
of
33
Determinant maximization with linear matrix inequality constraints
 SIAM Journal on Matrix Analysis and Applications
, 1998
"... constraints ..."
The bhattacharyya metric as an absolute similarity measure for frequency coded data
 Kybernetika
, 1997
"... A recurring problem that arises throughout the sciences is that of deciding whether two statistical distributions differ or are consistent currently the chisquared statistic is the most commonly used technique for addressing this problem. This paper explains the drawbacks of the chisquared statis ..."
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Cited by 52 (4 self)
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A recurring problem that arises throughout the sciences is that of deciding whether two statistical distributions differ or are consistent currently the chisquared statistic is the most commonly used technique for addressing this problem. This paper explains the drawbacks of the chisquared statistic for comparing measurements over large distances in pattern space and suggests that the Bhattacharyya measure can avoid such difficulties. The original interpretation of the Bhattacharyya metric as a geometric similarity measure is reviewed and it is pointed out that this derivation is independent of the use of the Bhattacharyya measure as an upper bound on misclassification in a twoclass problem. The affinity between the Bhattacharyya and Matusita measures is described and we show that the measure is applicable to any distribution of data. We explain that the Bhattacharyya measure is consistent with an assumption of a Poisson generation mechanism for individual measurements in a distribution which is applicable to a frequency (histogram) or probabilistic data set and suggest application of the Bhattacharyya measure to the field of system identification.
Digital Audio Restoration
 Applications of Digital Signal Processing to Audio and Acoustics
, 1997
"... This chapter is concerned with the application of modern signal processing techniques to the restoration of degraded audio signals. Although attention is focussed on gramophone recordings, film sound tracks and tape recordings, many of the techniques discussed have applications in other areas where ..."
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Cited by 28 (10 self)
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This chapter is concerned with the application of modern signal processing techniques to the restoration of degraded audio signals. Although attention is focussed on gramophone recordings, film sound tracks and tape recordings, many of the techniques discussed have applications in other areas where degraded audio signals occur, such as speech transmission, telephony and hearing aids. We aim to provide a wide coverage of existing methodology while giving insight into current areas of research and future trends. 1 Introduction The introduction of high quality digital audio media such as Compact Disk (CD) and Digital Audio Tape (DAT) has dramatically raised general awareness and expectations about sound quality in all types of recordings. This, combined with an upsurge in interest in historical and nostalgic material, has led to a growing requirement for restoration of degraded sources ranging from the earliest recordings made on wax cylinders in the nineteenth century, through disc reco...
Crestfactor minimization using nonlinear Chebyshev approximation methods
 IEEE Trans. on Inst. and Meas
, 1991
"... AbstractLow crestfactor of excitation and response signals is desirable in transfer function measurements, since this allows the maximization of the signaltonoise ratios (SNR’s) for given allowable amplitude ranges of the signals. The paper presents a new crestfactor minimization algorithm for ..."
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Cited by 15 (2 self)
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AbstractLow crestfactor of excitation and response signals is desirable in transfer function measurements, since this allows the maximization of the signaltonoise ratios (SNR’s) for given allowable amplitude ranges of the signals. The paper presents a new crestfactor minimization algorithm for periodic signals with prescribed power spectrum. The algorithm is based on approximation of the nondifferentiable Chebyshev (minimax) norm by Z,,norms with increasing values of p, and the calculations are accelerated by using FFT’s. Several signals related by linear systems can also be compressed simultaneously. The resulting crestfactors are significantly better than those provided by earlier methods. Moreover, it is shown that the peak value of a signal can be further decreased by allowing some extra energy at additional frequencies. KeywordsCrestfactor, multisine, optimal excitation. I.
Numerical Algorithms For Subspace State Space System Identification (n4sid)
 in Applied and Computational Control, Signals and Circuits
, 1997
"... We present the basic notions on subspace identification algorithms for linear systems. These methods estimate state sequences or extended observability matrices directly from the given data, through an orthogonal or oblique projection of the row spaces of certain block Hankel matrices into the row s ..."
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Cited by 14 (7 self)
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We present the basic notions on subspace identification algorithms for linear systems. These methods estimate state sequences or extended observability matrices directly from the given data, through an orthogonal or oblique projection of the row spaces of certain block Hankel matrices into the row spaces of others. The extraction of the state space model is then achieved through the solution of a least squares problem. These algorithms can be elegantly implemented using wellknown numerical linear algebra algorithms such as the LQ and singular value decomposition. The paper aims at giving an overview of the methodologies used in time domain subspace identification. A short overview of frequency domain subspace identification results is also presented. 1 INTRODUCTION While at first sight, the class of linear timeinvariant systems with lumped parameters, seems to be rather restricted, it turns out that the inputoutput behavior of many reallife industrial processes, for most practica...
Databased mechanistic modelling of environmental,ecological,economic and engineering systems, Environmental Modelling and
 Software
, 1998
"... Abstract: The paper discusses the problems associated with environmental modelling and the need to consider uncertainty in the formulation, identification, estimation and validation of environmental models. It introduces the concept of DataBased Mechanistic (DBM) modelling and contrasts its inducti ..."
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Cited by 11 (5 self)
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Abstract: The paper discusses the problems associated with environmental modelling and the need to consider uncertainty in the formulation, identification, estimation and validation of environmental models. It introduces the concept of DataBased Mechanistic (DBM) modelling and contrasts its inductive approach with the hypotheticodeductive approaches that dominate most environmental modelling research at the present time. The major methodological procedures utilized in DBM modelling are outlined and two practical examples illustrate how it has been applied in a hydrological and water quality context. Keynote paper presented at the International Federation on Automatic Control (IFAC) Workshop on Environmental Systems, Tokyo, Japan, August 21st, 2001. 1.
Model Based Recognition using Pruned Correspondence Search
 IEEE Conf. on Computer Vision and Pattern Recognition
, 1990
"... This paper presents a polynomial time algorithm (pruned correspondence search, PCS) for solving a wide class of geometric maximal matching problems, including the problem of recognizing 3D objects from a single 2D image. The PCS algorithm is connected with the geometry of the underlying recognit ..."
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Cited by 10 (0 self)
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This paper presents a polynomial time algorithm (pruned correspondence search, PCS) for solving a wide class of geometric maximal matching problems, including the problem of recognizing 3D objects from a single 2D image. The PCS algorithm is connected with the geometry of the underlying recognition problem only through calls to a verification algorithm.
Stochastic, dynamic modelling and signal processing: time variable and state dependent parameter estimation
 Cambridge University Press: Cambridge
, 2000
"... 1999) have discussed an approach to nonstationary and nonlinear signal processing ..."
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Cited by 6 (3 self)
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1999) have discussed an approach to nonstationary and nonlinear signal processing
Guaranteed nonlinear parameter estimation in knowledgebased models
 J. Comput. Appl. Math
"... Knowledgebased models are ubiquitous in pure and applied sciences. They often involve unknown parameters to be estimated from experimental data. This is usually much more difficult than for blackbox models, only intended to mimic a given inputoutput behavior. The output of knowledgebased models ..."
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Cited by 6 (1 self)
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Knowledgebased models are ubiquitous in pure and applied sciences. They often involve unknown parameters to be estimated from experimental data. This is usually much more difficult than for blackbox models, only intended to mimic a given inputoutput behavior. The output of knowledgebased models is almost always nonlinear in their parameters, so that linear least squares cannot be used, and analytical solutions for the model equations are seldom available. Moreover, since the parameters have some physical meaning, it is not enough to find some numerical values of these quantities that are such that the model fits the data reasonably well. One would like, for instance, to make sure that the parameters to be estimated are identifiable. If this is not the case, all equivalent solutions should be provided. The uncertainty in the parameters resulting from the measurement noise and approximate nature of the model should also be characterized. This paper describes how guaranteed methods based on interval analysis may contribute to these tasks. Examples in linear and nonlinear compartmental modeling, widely used in biology, are provided.
An Efficient Correspondence Based Algorithm for 2D and 3D Model Based Recognition
 A.I. Memo 1259, MIT, MIT AI Lab
, 1990
"... This paper presents a polynomial time aJgorithm (pruned correspondence sem'ch, PCS) with good average case performance for solving a wide class of geometric maximal matching problems, including the problem of recognizing 3D objects from a single 2D image. Given two finite sets of geometric features ..."
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Cited by 5 (3 self)
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This paper presents a polynomial time aJgorithm (pruned correspondence sem'ch, PCS) with good average case performance for solving a wide class of geometric maximal matching problems, including the problem of recognizing 3D objects from a single 2D image. Given two finite sets of geometric features with error bounds and a polynomiai time algorithm that determines the feasibility of individuai matchings, it finds a maximaJ matching. The algorithm is based on a pruned depthfirst search for correspondences. Pruning is accomplished by representing regions of search space that have aiready been explored using an "adjoint list" of correspondences between image and model points.