discrete stochastic processes and optimal filtering digital signal and image processing

Download Book Discrete Stochastic Processes And Optimal Filtering Digital Signal And Image Processing in PDF format. You can Read Online Discrete Stochastic Processes And Optimal Filtering Digital Signal And Image Processing here in PDF, EPUB, Mobi or Docx formats.

Discrete Stochastic Processes And Optimal Filtering

Author : Jean-Claude Bertein
ISBN : 9781118615492
Genre : Technology & Engineering
File Size : 61. 97 MB
Format : PDF, Mobi
Download : 205
Read : 1210

Download Now


Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals. Moreover, it is a fundamental feature in a range of applications, such as in navigation in aerospace and aeronautics, filter processing in the telecommunications industry, etc. This book provides a comprehensive overview of this area, discussing random and Gaussian vectors, outlining the results necessary for the creation of Wiener and adaptive filters used for stationary signals, as well as examining Kalman filters which are used in relation to non-stationary signals. Exercises with solutions feature in each chapter to demonstrate the practical application of these ideas using Matlab.

Optimal Filtering

Author : Brian D. O. Anderson
ISBN : 9780486136899
Genre : Science
File Size : 35. 20 MB
Format : PDF, Kindle
Download : 408
Read : 324

Download Now


Graduate-level text extends studies of signal processing, particularly regarding communication systems and digital filtering theory. Topics include filtering, linear systems, and estimation; discrete-time Kalman filter; time-invariant filters; more. 1979 edition.

Digital Signal And Image Processing Using Matlab Volume 2

Author : Gérard Blanchet
ISBN : 9781848216419
Genre : Technology & Engineering
File Size : 40. 60 MB
Format : PDF
Download : 449
Read : 1292

Download Now


Volume 2 of the second edition of the fully revised and updated Digital Signal and Image Processing using MATLAB® is essentially a collection of examples and exercises which also presents applications of digital signal- or image processing, and techniques which were not touched upon in the previous volume. 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. 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.

Regularization And Bayesian Methods For Inverse Problems In Signal And Image Processing

Author : Jean-François Giovannelli
ISBN : 9781848216372
Genre : Technology & Engineering
File Size : 45. 97 MB
Format : PDF, Docs
Download : 870
Read : 821

Download Now


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.

Digital Signal Processing Dsp With Python Programming

Author : Maurice Charbit
ISBN : 9781786301260
Genre : Technology & Engineering
File Size : 32. 97 MB
Format : PDF, Docs
Download : 114
Read : 392

Download Now


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.

Tracking With Particle Filter For High Dimensional Observation And State Spaces

Author : Sverine Dubuisson
ISBN : 9781848216037
Genre : Technology & Engineering
File Size : 28. 31 MB
Format : PDF, Mobi
Download : 918
Read : 594

Download Now


This title concerns the use of a particle filter framework to track objects defined in high-dimensional state-spaces using high-dimensional observation spaces. Current tracking applications require us to consider complex models for objects (articulated objects, multiple objects, multiple fragments, etc.) as well as multiple kinds of information (multiple cameras, multiple modalities, etc.). This book presents some recent research that considers the main bottleneck of particle filtering frameworks (high dimensional state spaces) for tracking in such difficult conditions.

Optimal Filtering

Author : V.N. Fomin
ISBN : 9789401153263
Genre : Mathematics
File Size : 46. 6 MB
Format : PDF, Kindle
Download : 828
Read : 1248

Download Now


This book is devoted to an investigation of some important problems of mod ern filtering theory concerned with systems of 'any nature being able to per ceive, store and process an information and apply it for control and regulation'. (The above quotation is taken from the preface to [27]). Despite the fact that filtering theory is l'argely worked out (and its major issues such as the Wiener-Kolmogorov theory of optimal filtering of stationary processes and Kalman-Bucy recursive filtering theory have become classical) a development of the theory is far from complete. A great deal of recent activity in this area is observed, researchers are trying consistently to generalize famous results, extend them to more broad classes of processes, realize and justify more simple procedures for processing measurement data in order to obtain more efficient filtering algorithms. As to nonlinear filter ing, it remains much as fragmentary. Here much progress has been made by R. L. Stratonovich and his successors in the area of filtering of Markov processes. In this volume an effort is made to advance in certain of these issues. The monograph has evolved over many years, coming of age by stages. First it was an impressive job of gathering together the bulk of the impor tant contributions to estimation theory, an understanding and moderniza tion of some of its results and methods, with the intention of applying them to recursive filtering problems.

Top Download:

Best Books