Willsky, Alan S.Overview
Publication Timeline
Most widely held works by
Alan S Willsky
Signals and systems
by Alan V Oppenheim
(
Book
)
61 editions published between 1983 and 2014 in 4 languages and held by 1,184 WorldCat member libraries worldwide "More than half of the 600+ problems in the second edition of Signals & Systems are new, while the remainder are the same as in the first edition. This manual contains solutions to the new problems, as well as updated solutions for the problems from the first edition."Pref
Digital signal processing and control and estimation theory : points of tangency, areas of intersection, and parallel directions
by Alan S Willsky
(
Book
)
11 editions published between 1977 and 1979 in English and held by 343 WorldCat member libraries worldwide
Detection of abrupt changes in dynamic systems
by Alan S Willsky
(
Book
)
2 editions published in 1984 in English and held by 80 WorldCat member libraries worldwide This paper presents some of the basic ideas associated with the detection of abrupt changes in dynamic systems. The author's presentation focuses on two classes of methods  multiple filterbased techniques and residualbased methods  and in far more detail on the multiple model and generalized likelihood ratio methods. Issues such as the effect of unknown onset time on algorithm complexity and structure and robustness to model uncertainty are discussed. (Author)
Xin hao yu xi tong
by Alan V Oppenheim
(
Book
)
7 editions published between 1995 and 2013 in Chinese and held by 39 WorldCat member libraries worldwide
Signale und Systeme
by Alan V Oppenheim
(
Book
)
2 editions published between 1989 and 1992 in German and held by 25 WorldCat member libraries worldwide
Signale und Systeme
by Alan V Oppenheim
(
Book
)
1 edition published in 1989 in German and held by 20 WorldCat member libraries worldwide
Kalman filtering and Riccati equations for descriptor systems
by Ramine Nikoukhah
(
Book
)
9 editions published between 1990 and 1991 in English and held by 15 WorldCat member libraries worldwide In this paper we consider a general formulation of a discretetime filtering problem for descriptor systems. It is shown that the nature of descriptor systems leads directly to the need to examine singular estimation problems. Using a "dual approach" to estimation we derive a socalled "3block" form for the optimal filter and a corresponding 3block Riccati equation for a general class of timevarying descriptor models which need not represent a wellposed system in that the dynamics may be either over or underconstrained. Specializing to the timeinvariant case we examine the asymptotic properties of the 3block filter, and in particular analyze in detail the resulting 3block algebraic Riccati equation, generalizing significantly the results in [23, 28, 33]. Finally, the noncausal nature of discretetime descriptor dynamics implies that future dynamics may provide some information about the present state. We present a modified form for the descriptor Kalman filter that takes this information into account
Aggregation and multilevel control in discrete event dynamic systems
by Cüneyt M Özveren
(
Book
)
7 editions published between 1989 and 1990 in English and held by 11 WorldCat member libraries worldwide In this paper we consider the problem of higherlevel aggregate modelling and control of discreteevent dynamic systems (DEDS) modelled as finite state automata in which some events are controllable, some are observed, and some represent events to be tracked. The higherlevel models considered correspond to associating specified sequences of events in the original system to single macroscopic events in the higher level model. We also consider the problem of designing a compensator that can be used to restrict microscopic behavior so that the system will only produce strings of these primitive sequences or tasks. With this lower level control in place we can construct higherlevel models which typically have many fewer states and events than the original system. Also, motivated by applications such as flexible manufacturing, we address the problem of constructing and controlling higherlevel models of interconnections of DEDS. This allows us to "slow down" the combinatorial explosion typically present in computations involving interacting automata
Multiscale system theory
by Albert Benveniste
(
Book
)
8 editions published between 1990 and 1991 in English and held by 11 WorldCat member libraries worldwide In many applications, it is of interest to analyze and recognize phenomena occurring at different scales. The recently introduced wavelet transforms provide a timeandscale decomposition of signals that offers the possibility of such an analysis. Until recently, however, there has been no corresponding statistical framework to support the development of optimal, multiscale statistical signal processing algorithms. A recent work of some of the present authors and coauthors proposed such a framework via models of "stochastic fractals" on the dyadic tree. In this paper we investigate some of the fundamental issues that are relevant to system theories on the dyadic tree, both for systems and signals
Multiscale autoregressive processes
by M Basseville
(
Book
)
6 editions published between 1989 and 1990 in English and held by 9 WorldCat member libraries worldwide In many applications (e.g. recognition of geophysical and biomedical signals and multiscale analysis of images), it is of interest to analyze and recognize phenomena occuring at different scales The recently introduced wavelet trans forms provide a timeandscale decomposition of signals that offers the possibil ity of such analysis. At present, however, there is no corresponding statistical framework to support the development of optimal, multiscale statistical sig nal processing algorithms. In this paper we describe such a framework. The theory of multiscale signal representations leads naturally to models of signals on trees, and this provides the framework for our investigation. In particular, in this paper we describe the class of isotropic processes on homogenous trees and develop a theory of autoregressive models in this context. This leads to generalizations of Schur and Levinson recursions, associated properties of the resulting reflection coefficients, and the initial pieces in a system theory for multiscale modeling
Output stabilizability of discrete event dynamic systems
by Cüneyt M Özveren
(
Book
)
5 editions published in 1989 in English and held by 9 WorldCat member libraries worldwide In this paper, we investigate the problem of designing stabilizing feedback compensators for Discrete Event Dynamic Systems (DEDS). The DEDS model used is a finitestate automaton in which some transition events are controllable and some events are observed. The problem of output stabilization is defined as the construction of a compensator such that the closed loop system is stable, in the sense that all state trajectories go through a given set E infinitely often. We define a stronger notion of output stabilizability which requires that we also have perfect knowledge of the state in E through which the trajectory passes on each of its visits to E. Necessary and sufficient conditions are presented for both notions. The complexity of these tests is polynomial in the cardinality of the state space of the observer. A number of sufficient conditions for the weaker notion are also presented. Corresponding tests for these sufficient conditions are shown to be polynomial in the cardinality of the state space of the system. Finally, a problem of resilient output stabilizability is addressed
Estimationbased approach to the reconstruction of optical flow
by Anne Rougee
(
Book
)
4 editions published in 1987 in English and held by 9 WorldCat member libraries worldwide
Asymptotic Orders of Reachability in Perturbed Linear Systems
by Cüneyt M Özveren
(
Book
)
7 editions published between 1987 and 1988 in English and held by 8 WorldCat member libraries worldwide A framework for studying asymptotic orders of reachability in perturbed linear, timeinvariant systems is developed. The systems of interest are defined by matrices that have Taylor or Laurent expansions in the perturbation parameter e about the point 0. The reachability structure is exposed via the Smith form of the reachability matrix. This approach is used to provide insight into the kinds of inputs needed to reach weakly reachable target states, into the structure of highgain feedback for pole placement, and into the types of inputs that steer trajectories arbitrarily close to almost (A, B)invariant subspaces and almost (A, B)controllability subspaces
Optical flow computation via multiscale regularization
by M. R Luettgen
(
Book
)
4 editions published in 1992 in English and held by 7 WorldCat member libraries worldwide The apparent motion of brightness patterns in an image is referred to as the optical flow. In computational vision, optical flow is an important input into higher level vision algorithms performing tasks such as segmentation, tracking, object detection, robot guidance and recovery of shape information. In addition, methods for computing optical flow are an essential part of motion compensated coding schemes. In this paper, we present a new approach to the problem of computing optical flow. Standard formulations of this problem require the computationally intensive solution of an elliptic partial differential equation which arises from the often used "smoothness constraint" regularization term. We utilize the interpretation of the smoothness constraint as a "fractal prior" to motivate regularization based on a recently introduced class of multiscale stochastic models. These models are associated with efficient multiscale smoothing algorithms, and experiments on several image sequences demonstrate the substantial computational savings that can be achieved through their use
A geometric projectionspace reconstruction algorithm
by Jerry L Prince
(
Book
)
4 editions published in 1988 in English and held by 6 WorldCat member libraries worldwide We present a method to reconstruct images from finite sets of noisy projections that may be available only over limited or sparse angles. The algorithm calculates the maximum a posteriori (MAP) estimate of the full sinogram (which is an image of the 2D Radon transform of the object) from the available data. It is implemented using a primaldual constrained optimization procedure that solves a partial differential equation in the primal phase with an efficient local relaxation algorithm and uses a simple Lagrange multiplier update in the dual phase. The sinogram prior probability is given by a Markov random field (MRF) that includes information about the mass, center of mass, and convex hull of the object, and about the smoothness, fundamental constraints, and periodicity of the 2D Radon transform. The object is reconstructed using convolution back projection applied to the estimated sinogram. We show several reconstructed objects which are obtained from simulated limitedangle and sparse angle data using the described algorithm, and compare these results to images obtained using convolution back projection directly
Stability, stochastic stationarity and generalized Lyapunov equations for twopoint boundaryvalue descriptor systems
by Ramine Nikoukhah
(
Book
)
5 editions published in 1988 in English and held by 6 WorldCat member libraries worldwide This paper introduces the concept of internal stability for twopoint boundaryvalue descriptor systems (TPBVDSs). Since TPBVDSs are defined only over a finite interval, the concept of stability is not easy to formulate for these systems. The definition which is used here consists in requiring that as the length of the interval of definition increases, the effect of boundary conditions on states located close to the center of the interval should go to zero. Stochastic TPBVDSs are studied, and the property of stochastic stationarity is characterized in terms of a generalized Lyapunov equation satisfied by the variance of the boundary vector. A second generalized Lyapunov equation satisfied by state variance of a stochastically stationary TPBVDS is also introduced, and the existence and uniqueness of positive definite solutions to this equation is then used to characterize the property of internal stability. Keywords: Stability, Twopoint boundary value problems. (hde)
A wavelet packet approach to transient signal classification
by Rachel E Learned
(
Book
)
4 editions published in 1993 in English and held by 6 WorldCat member libraries worldwide Timefrequency transforms, including wavelet and wavelet packet transforms, are generally acknowledged to be useful for studying nonstationary phenomena and, in particular, have been shown or claimed to be of value in the detection and characterization of transient signals. In many applications timefrequency transforms are simply employed as a visual aid to be used for signal display. Although there have been several studies reported in the literature, there is still considerable work to be done investigating the utility of wavelet and wavelet packet timefrequency transforms for automatic transient signal classification. In this paper, we contribute to this ongoing investigation by exploring the feasibility of applying the wavelet packet transform to automatic detection and classification of a specific set of transient signals in background noise. In particular, a noncoherent waveletpacketbased algorithm specific to the detection and classification of underwater acoustic signals generated by snapping shrimp and sperm whale clicks is proposed. We develop a systematic feature extraction process which exploits signal class differences in the wavelet packet transform coefficients. The waveletpacketbased features obtained by our method for the biologically generated underwater acoustic signals yield excellent classification results when used as input for a neural network and a nearest neighbor rule
A distributed and iterative method for square root filtering in spacetime estimation
by Toshio M Chin
(
Book
)
4 editions published in 1994 in English and held by 6 WorldCat member libraries worldwide We describe a distribute, and iterative approach to perform the unitary transformations in the square root information filter imple nentation of the Kalman filter, providing an alternative to the common QR factorizationbased approaches. The new approach is useful in approximate computation of filtered estimates for temporallyevolving random fields defined by local interactions and observations. Using several examples motivated by computer vision applications, we demonstrate that nearoptimal estimates can be computed for problems of practical importance using only a small number of iterations, which can be performed in a finely parallel manner over the spatial domain of the random field
Likelihood calculation for a class of multiscale stochastic models, with application to texture discrimination
by Mark R Luettgen
(
Book
)
4 editions published in 1993 in English and held by 6 WorldCat member libraries worldwide A class of multiscale stochastic models based on scalerecursive dynamics on trees has recently been introduced. Theoretical and experimental results have shown that these models provide an extremely rich framework for representing both processes which are intrinsically multiscale, e.g., 1/f processes, as well as 1D Markov processes and 2D Markov random fields. Moreover, efficient optimal estimation algorithms have been developed for these models by exploiting their scalerecursive structure. In this paper, we exploit this structure in order to develop a computationally efficient and parallelizable algorithm for likelihood calculation. We illustrate one possible application to texture discrimination and demonstrate that likelihoodbased methods using our algorithm have substantially better probability of error characteristics than wellknown leastsquares methods, and achieve performance comparable to that of Gaussian Markov random field based techniques, which in general are prohibitively complex computationally
Efficient multiscale regularization with applications to the computation of optical flow
by Mark R Luettgen
(
Book
)
4 editions published in 1993 in English and held by 6 WorldCat member libraries worldwide A new approach to regularization methods for image processing is introduced and developed using as a vehicle the problem of computing dense optical flow fields in an image sequence. Standard formulations of this problem require the computationally intensive solution of an elliptic partial differential equation which arises from the often used "smoothness constraint" type regularization. We utilize the interpretation of the smoothness constraint as a "fractal prior" to motivate regularization based on a recently introduced class of multiscale stochastic models. The solution of the new problem formulation is computed with an efficient multiscale algorithm more
fewer
Audience Level
Related Identities
Associated Subjects
Algorithms Boundary value problems Computer vision Control theory Digital control systems Electric filters Estimation theory Image processing Kalman filtering Linear programming MATLAB Matrices Multigrid methods (Numerical analysis) Riccati equation Signal detection Signal generators Signal processing Signal processingData processing Signal processingDigital techniques Signal theory (Telecommunication) System analysis System theory

Alternative Names
Willsky, A. S. (Alan S.)
Languages
Covers
