Author: Joseph J.K. O Ruanaidh Publisher: Springer Science & Business Media ISBN: 1461207177 Category : Computers Languages : en Pages : 256
Book Description
This book is concerned with the processing of signals that have been sam pled and digitized. The fundamental theory behind Digital Signal Process ing has been in existence for decades and has extensive applications to the fields of speech and data communications, biomedical engineering, acous tics, sonar, radar, seismology, oil exploration, instrumentation and audio signal processing to name but a few [87]. The term "Digital Signal Processing", in its broadest sense, could apply to any operation carried out on a finite set of measurements for whatever purpose. A book on signal processing would usually contain detailed de scriptions of the standard mathematical machinery often used to describe signals. It would also motivate an approach to real world problems based on concepts and results developed in linear systems theory, that make use of some rather interesting properties of the time and frequency domain representations of signals. While this book assumes some familiarity with traditional methods the emphasis is altogether quite different. The aim is to describe general methods for carrying out optimal signal processing.
Author: James V. Candy Publisher: John Wiley & Sons ISBN: 1118210549 Category : Science Languages : en Pages : 404
Book Description
New Bayesian approach helps you solve tough problems in signal processing with ease Signal processing is based on this fundamental concept—the extraction of critical information from noisy, uncertain data. Most techniques rely on underlying Gaussian assumptions for a solution, but what happens when these assumptions are erroneous? Bayesian techniques circumvent this limitation by offering a completely different approach that can easily incorporate non-Gaussian and nonlinear processes along with all of the usual methods currently available. This text enables readers to fully exploit the many advantages of the "Bayesian approach" to model-based signal processing. It clearly demonstrates the features of this powerful approach compared to the pure statistical methods found in other texts. Readers will discover how easily and effectively the Bayesian approach, coupled with the hierarchy of physics-based models developed throughout, can be applied to signal processing problems that previously seemed unsolvable. Bayesian Signal Processing features the latest generation of processors (particle filters) that have been enabled by the advent of high-speed/high-throughput computers. The Bayesian approach is uniformly developed in this book's algorithms, examples, applications, and case studies. Throughout this book, the emphasis is on nonlinear/non-Gaussian problems; however, some classical techniques (e.g. Kalman filters, unscented Kalman filters, Gaussian sums, grid-based filters, et al) are included to enable readers familiar with those methods to draw parallels between the two approaches. Special features include: Unified Bayesian treatment starting from the basics (Bayes's rule) to the more advanced (Monte Carlo sampling), evolving to the next-generation techniques (sequential Monte Carlo sampling) Incorporates "classical" Kalman filtering for linear, linearized, and nonlinear systems; "modern" unscented Kalman filters; and the "next-generation" Bayesian particle filters Examples illustrate how theory can be applied directly to a variety of processing problems Case studies demonstrate how the Bayesian approach solves real-world problems in practice MATLAB notes at the end of each chapter help readers solve complex problems using readily available software commands and point out software packages available Problem sets test readers' knowledge and help them put their new skills into practice The basic Bayesian approach is emphasized throughout this text in order to enable the processor to rethink the approach to formulating and solving signal processing problems from the Bayesian perspective. This text brings readers from the classical methods of model-based signal processing to the next generation of processors that will clearly dominate the future of signal processing for years to come. With its many illustrations demonstrating the applicability of the Bayesian approach to real-world problems in signal processing, this text is essential for all students, scientists, and engineers who investigate and apply signal processing to their everyday problems.
Author: Paul Damien Publisher: Oxford University Press ISBN: 0199695601 Category : Mathematics Languages : en Pages : 717
Book Description
This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances in this field.
Author: David A. Rosenblueth, Publisher: Frontiers Media SA ISBN: 2889450422 Category : Languages : en Pages : 115
Book Description
The complexity of living organisms surpasses our unaided habilities of analysis. Hence, computational and mathematical methods are necessary for increasing our understanding of biological systems. At the same time, there has been a phenomenal recent progress allowing the application of novel formal methods to new domains. This progress has spurred a conspicuous optimism in computational biology. This optimism, in turn, has promoted a rapid increase in collaboration between specialists of biology with specialists of computer science. Through sheer complexity, however, many important biological problems are at present intractable, and it is not clear whether we will ever be able to solve such problems. We are in the process of learning what kind of model and what kind of analysis and synthesis techniques to use for a particular problem. Some existing formalisms have been readily used in biological problems, others have been adapted to biological needs, and still others have been especially developed for biological systems. This Research Topic has examples of cases (1) employing existing methods, (2) adapting methods to biology, and (3) developing new methods. We can also see discrete and Boolean models, and the use of both simulators and model checkers. Synthesis is exemplified by manual and by machine-learning methods. We hope that the articles collected in this Research Topic will stimulate new research.
Author: David Barber Publisher: Cambridge University Press ISBN: 0521196760 Category : Computers Languages : en Pages : 432
Book Description
The first unified treatment of time series modelling techniques spanning machine learning, statistics, engineering and computer science.
Author: Paul Van Den Hof Publisher: Elsevier ISBN: 0080913156 Category : Technology & Engineering Languages : en Pages : 2092
Book Description
The scope of the symposium covers all major aspects of system identification, experimental modelling, signal processing and adaptive control, ranging from theoretical, methodological and scientific developments to a large variety of (engineering) application areas. It is the intention of the organizers to promote SYSID 2003 as a meeting place where scientists and engineers from several research communities can meet to discuss issues related to these areas. Relevant topics for the symposium program include: Identification of linear and multivariable systems, identification of nonlinear systems, including neural networks, identification of hybrid and distributed systems, Identification for control, experimental modelling in process control, vibration and modal analysis, model validation, monitoring and fault detection, signal processing and communication, parameter estimation and inverse modelling, statistical analysis and uncertainty bounding, adaptive control and data-based controller tuning, learning, data mining and Bayesian approaches, sequential Monte Carlo methods, including particle filtering, applications in process control systems, motion control systems, robotics, aerospace systems, bioengineering and medical systems, physical measurement systems, automotive systems, econometrics, transportation and communication systems*Provides the latest research on System Identification*Contains contributions written by experts in the field*Part of the IFAC Proceedings Series which provides a comprehensive overview of the major topics in control engineering.
Author: Juan Chiachio-Ruano Publisher: CRC Press ISBN: 1351869655 Category : Mathematics Languages : en Pages : 289
Book Description
This book is devoted to a special class of engineering problems called Bayesian inverse problems. These problems comprise not only the probabilistic Bayesian formulation of engineering problems, but also the associated stochastic simulation methods needed to solve them. Through this book, the reader will learn how this class of methods can be useful to rigorously address a range of engineering problems where empirical data and fundamental knowledge come into play. The book is written for a non-expert audience and it is contributed to by many of the most renowned academic experts in this field.
Author: George V. Tsoulos Publisher: Wiley-IEEE Press ISBN: Category : Technology & Engineering Languages : en Pages : 790
Book Description
Electrical Engineering Adaptive Antennas for Wireless Communications In the past decade, the wireless communications community recognized adaptive antennas as a core technology that would help existing systems overcome problems related to spectrum efficiency and provide a vehicle to achieve the ambitious requirements of next-generation networks. The communications industry has already begun to develop adaptive antenna systems for commercial use and at the same time is working with standardization institutes around the world to produce adaptive antenna-friendly standards. Adaptive Antennas for Wireless Communications is a concise, detailed resource of information for all critical issues related to this technology and is compiled from the original published work of experts in the field. The extensive literature covers: * Historical and background aspects * Radio channel simulation techniques and characteristics * Adaptive algorithm performance under a variety of conditions * Adaptive antenna performance in different operational environments * Design and implementation issues * Experimental results * Other issues such as network planning and recent novel techniques Adaptive Antennas for Wireless Communications is a valuable reference for helping consultants, researchers, communications professionals, academics, and students gain an in-depth understanding of adaptive antenna technology.
Author: Joseph J.K. O Ruanaidh
Author: 
Author: James V. Candy
Author: Paul Damien
Author: David A. Rosenblueth,
Author: David Barber
Author: University of Michigan
Author: Paul Van Den Hof
Author: Juan Chiachio-Ruano
Author: George V. Tsoulos