Blind Identification and Separation of Complex-valued Signals

Blind Identification and Separation of Complex-valued Signals PDF Author: Eric Moreau
Publisher: John Wiley & Sons
ISBN: 1848214596
Category : Technology & Engineering
Languages : en
Pages : 112

Get Book

Book Description
Blind identification consists of estimating a multi-dimensional system only through the use of its output, and source separation, the blind estimation of the inverse of the system. Estimation is generally carried out using different statistics of the output. The authors of this book consider the blind identification and source separation problem in the complex-domain, where the available statistical properties are richer and include non-circularity of the sources – underlying components. They define identifiability conditions and present state-of-the-art algorithms that are based on algebraic methods as well as iterative algorithms based on maximum likelihood theory. Contents 1. Mathematical Preliminaries. 2. Estimation by Joint Diagonalization. 3. Maximum Likelihood ICA. About the Authors Eric Moreau is Professor of Electrical Engineering at the University of Toulon, France. His research interests concern statistical signal processing, high order statistics and matrix/tensor decompositions with applications to data analysis, telecommunications and radar. Tülay Adali is Professor of Electrical Engineering and Director of the Machine Learning for Signal Processing Laboratory at the University of Maryland, Baltimore County, USA. Her research interests concern statistical and adaptive signal processing, with an emphasis on nonlinear and complex-valued signal processing, and applications in biomedical data analysis and communications. Blind identification consists of estimating a multidimensional system through the use of only its output. Source separation is concerned with the blind estimation of the inverse of the system. The estimation is generally performed by using different statistics of the outputs. The authors consider the blind estimation of a multiple input/multiple output (MIMO) system that mixes a number of underlying signals of interest called sources. They also consider the case of direct estimation of the inverse system for the purpose of source separation. They then describe the estimation theory associated with the identifiability conditions and dedicated algebraic algorithms. The algorithms depend critically on (statistical and/or time frequency) properties of complex sources that will be precisely described.

Blind Identification and Separation of Complex-valued Signals

Blind Identification and Separation of Complex-valued Signals PDF Author: Eric Moreau
Publisher: John Wiley & Sons
ISBN: 1848214596
Category : Technology & Engineering
Languages : en
Pages : 112

Get Book

Book Description
Blind identification consists of estimating a multi-dimensional system only through the use of its output, and source separation, the blind estimation of the inverse of the system. Estimation is generally carried out using different statistics of the output. The authors of this book consider the blind identification and source separation problem in the complex-domain, where the available statistical properties are richer and include non-circularity of the sources – underlying components. They define identifiability conditions and present state-of-the-art algorithms that are based on algebraic methods as well as iterative algorithms based on maximum likelihood theory. Contents 1. Mathematical Preliminaries. 2. Estimation by Joint Diagonalization. 3. Maximum Likelihood ICA. About the Authors Eric Moreau is Professor of Electrical Engineering at the University of Toulon, France. His research interests concern statistical signal processing, high order statistics and matrix/tensor decompositions with applications to data analysis, telecommunications and radar. Tülay Adali is Professor of Electrical Engineering and Director of the Machine Learning for Signal Processing Laboratory at the University of Maryland, Baltimore County, USA. Her research interests concern statistical and adaptive signal processing, with an emphasis on nonlinear and complex-valued signal processing, and applications in biomedical data analysis and communications. Blind identification consists of estimating a multidimensional system through the use of only its output. Source separation is concerned with the blind estimation of the inverse of the system. The estimation is generally performed by using different statistics of the outputs. The authors consider the blind estimation of a multiple input/multiple output (MIMO) system that mixes a number of underlying signals of interest called sources. They also consider the case of direct estimation of the inverse system for the purpose of source separation. They then describe the estimation theory associated with the identifiability conditions and dedicated algebraic algorithms. The algorithms depend critically on (statistical and/or time frequency) properties of complex sources that will be precisely described.

Signals and Control Systems

Signals and Control Systems PDF Author: Smain Femmam
Publisher: John Wiley & Sons
ISBN: 1119384583
Category : Technology & Engineering
Languages : en
Pages : 340

Get Book

Book Description
The aim of this book is the study of signals and deterministic systems, linear, time-invariant, finite dimensions and causal. A set of useful tools is selected for the automatic and signal processing and methods of representation of dynamic linear systems are exposed, and analysis of their behavior. Finally we discuss the estimation, identification and synthesis of control laws for the purpose of stabilization and regulation.

Digital Signal Processing (DSP) with Python Programming

Digital Signal Processing (DSP) with Python Programming PDF Author: Maurice Charbit
Publisher: John Wiley & Sons
ISBN: 1119373050
Category : Technology & Engineering
Languages : en
Pages : 290

Get Book

Book Description
The parameter estimation and hypothesis testing are the basic tools in statistical inference. These techniques occur in many applications of data processing., and methods of Monte Carlo have become an essential tool to assess performance. For pedagogical purposes the book includes several computational problems and exercices. To prevent students from getting stuck on exercises, detailed corrections are provided.

Digital Signal and Image Processing using MATLAB, Volume 3

Digital Signal and Image Processing using MATLAB, Volume 3 PDF Author: Gérard Blanchet
Publisher: John Wiley & Sons
ISBN: 1119054109
Category : Technology & Engineering
Languages : en
Pages : 362

Get Book

Book Description
Volume 3 of the second edition of the fully revised and updated Digital Signal and Image Processing using MATLAB®, after first two volumes on the “Fundamentals” and “Advances and Applications: The Deterministic Case”, focuses on the stochastic case. It will be of particular benefit to readers who already possess a good knowledge of MATLAB®, a command of the fundamental elements of digital signal processing and who are familiar with both the fundamentals of continuous-spectrum spectral analysis and who have a certain mathematical knowledge concerning Hilbert spaces. This volume is focused on applications, but it also provides a good presentation of the principles. A number of elements closer in nature to statistics than to signal processing itself are widely discussed. This choice comes from a current tendency of signal processing to use techniques from this field. More than 200 programs and functions are provided in the MATLAB® language, with useful comments and guidance, to enable numerical experiments to be carried out, thus allowing readers to develop a deeper understanding of both the theoretical and practical aspects of this subject.

Matrix and Tensor Decompositions in Signal Processing, Volume 2

Matrix and Tensor Decompositions in Signal Processing, Volume 2 PDF Author: Gérard Favier
Publisher: John Wiley & Sons
ISBN: 1786301555
Category : Technology & Engineering
Languages : en
Pages : 386

Get Book

Book Description
The second volume will deal with a presentation of the main matrix and tensor decompositions and their properties of uniqueness, as well as very useful tensor networks for the analysis of massive data. Parametric estimation algorithms will be presented for the identification of the main tensor decompositions. After a brief historical review of the compressed sampling methods, an overview of the main methods of retrieving matrices and tensors with missing data will be performed under the low rank hypothesis. Illustrative examples will be provided.

Fundamentals of Signals and Control Systems

Fundamentals of Signals and Control Systems PDF Author: Smain Femmam
Publisher: John Wiley & Sons
ISBN: 1786300982
Category : Technology & Engineering
Languages : en
Pages : 308

Get Book

Book Description
The aim of this book is the study of signals and deterministic systems, linear, time-invariant, finite dimensions and causal. A set of useful tools is selected for the automatic and signal processing and methods of representation of dynamic linear systems are exposed, and analysis of their behavior. Finally we discuss the estimation, identification and synthesis of control laws for the purpose of stabilization and regulation. The study of signal characteristics and properties systems and knowledge of mathematical tools and treatment methods and analysis, are lately more and more importance and continue to evolve. The reason is that the current state of technology, particularly electronics and computing, enables the production of very advanced processing systems, effective and less expensive despite the complexity.

Digital Signal and Image Processing using MATLAB, Volume 2

Digital Signal and Image Processing using MATLAB, Volume 2 PDF Author: Gérard Blanchet
Publisher: John Wiley & Sons
ISBN: 1118999606
Category : Technology & Engineering
Languages : en
Pages : 274

Get Book

Book Description
The most important theoretical aspects of Image and SignalProcessing (ISP) for both deterministic and random signals, thetheory being supported by exercises and computer simulationsrelating to real applications. More than 200 programs and functions are provided in theMATLAB® language, with useful comments and guidance, to enablenumerical experiments to be carried out, thus allowing readers todevelop a deeper understanding of both the theoretical andpractical aspects of this subject. Following on from thefirst volume, this second installation takes a more practicalstance, providing readers with the applications of ISP.

Regularization and Bayesian Methods for Inverse Problems in Signal and Image Processing

Regularization and Bayesian Methods for Inverse Problems in Signal and Image Processing PDF Author: Jean-Francois Giovannelli
Publisher: John Wiley & Sons
ISBN: 1118827074
Category : Technology & Engineering
Languages : en
Pages : 322

Get Book

Book Description
The focus of this book is on "ill-posed inverse problems". These problems cannot be solved only on the basis of observed data. The building of solutions involves the recognition of other pieces of a priori information. These solutions are then specific to the pieces of information taken into account. Clarifying and taking these pieces of information into account is necessary for grasping the domain of validity and the field of application for the solutions built. For too long, the interest in these problems has remained very limited in the signal-image community. However, the community has since recognized that these matters are more interesting and they have become the subject of much greater enthusiasm. From the application field’s point of view, a significant part of the book is devoted to conventional subjects in the field of inversion: biological and medical imaging, astronomy, non-destructive evaluation, processing of video sequences, target tracking, sensor networks and digital communications. The variety of chapters is also clear, when we examine the acquisition modalities at stake: conventional modalities, such as tomography and NMR, visible or infrared optical imaging, or more recent modalities such as atomic force imaging and polarized light imaging.

Topographical Tools for Filtering and Segmentation 2

Topographical Tools for Filtering and Segmentation 2 PDF Author: Fernand Meyer
Publisher: John Wiley & Sons
ISBN: 1119575125
Category : Technology & Engineering
Languages : en
Pages : 273

Get Book

Book Description
Mathematical morphology has developed a powerful methodology for segmenting images, based on connected filters and watersheds. We have chosen the abstract framework of node- or edge-weighted graphs for an extensive mathematical and algorithmic description of these tools. Volume 2 proposes two physical models for describing valid flooding on a node- or edge-weighted graph, and establishes how to pass from one to another. Many new flooding algorithms are derived, allowing parallel and local flooding of graphs. Watersheds and flooding are then combined for solving real problems. Their ability to model a real hydrographic basin represented by its digital elevation model constitutes a good validity check of the underlying physical models. The last part of Volume 2 explains why so many different watershed partitions exist for the same graph. Marker-based segmentation is the method of choice for curbing this proliferation. This book proposes new algorithms combining the advantages of the previous methods which treated node- and edge-weighted graphs differently.

Topographical Tools for Filtering and Segmentation 1

Topographical Tools for Filtering and Segmentation 1 PDF Author: Fernand Meyer
Publisher: John Wiley & Sons
ISBN: 1119579546
Category : Technology & Engineering
Languages : en
Pages : 286

Get Book

Book Description
Mathematical morphology has developed a powerful methodology for segmenting images, based on connected filters and watersheds. We have chosen the abstract framework of node- or edge-weighted graphs for an extensive mathematical and algorithmic description of these tools. Volume 1 is devoted to watersheds. The topography of a graph appears by observing the evolution of a drop of water moving from node to node on a weighted graph, along flowing paths, until it reaches regional minima. The upstream nodes of a regional minimum constitute its catchment zone. The catchment zones may be constructed independently of each other and locally, in contrast with the traditional approach where the catchment basins have to be constructed all at the same time. Catchment zones may overlap, and thus, a new segmentation paradigm is proposed in which catchment zones cover each other according to a priority order. The resulting partition may then be corrected, by local and parallel treatments, in order to achieve the desired precision.