Expanded to cover more advanced applications where statistical properties of data can be nonstationary and the physical systems nonlinear as opposed to only linear. Stresses the practical use and interpretation of analyzed data to solve problems. Special attention is given to bias and random errors involved in desired estimates and the proper interpretation of results from specific applications. Includes numerous case studies concerned with dynamic problems which can occur in a variety of fields.
Introduction and background; Probability functions and amplitude measures; Correlation and spectral density functions; Single input/single output relationships; System identification and response; Propagation path identification; Single input/multiple output problems; Multiple input/output relationships; Energy source identification; Procedures for solving multiple input/output problems; Statistical errors in measurements.
The study of complex dynamic processes governed by nonlinear and nonstationary characteristics is a problem of great importance in the analysis and control of power system oscillatory behavior. Power system dynamic processes are highly random, nonlinear to some extent, and intrinsically nonstationary even over short time intervals as in the case of severe transient oscillations in which switching events and control actions interact in a complex manner. Phenomena observed in power system oscillatory dynamics are diverse and complex. Measured ambient data are known to exhibit noisy, nonstationary fluctuations resulting primarily from small magnitude, random changes in load, driven by low-scale motions or nonlinear trends originating from slow control actions or changes in operating conditions. Forced oscillations resulting from major cascading events, on the other hand, may contain motions with a broad range of scales and can be highly nonlinear and time-varying. Prediction of temporal dynamics, with the ultimate application to real-time system monitoring, protection and control, remains a major research challenge due to the complexity of the driving dynamic and control processes operating on various temporal scales that can become dynamically involved. An understanding of system dynamics is critical for reliable inference of the underlying mechanisms in the observed oscillations and is needed for the development of effective wide-area measurement and control systems, and for improved operational reliability.
A valuable introduction to the fundamentals of continuous and discrete time signal processing, this book is intended for the reader with little or no background in this subject. The emphasis is on development from basic principles. With this book the reader can become knowledgeable about both the theoretical and practical aspects of digital signal processing.Some special features of this book are: (1) gradual and step-by-step development of the mathematics for signal processing, (2) numerous examples and homework problems, (3) evolutionary development of Fourier series, Discrete Fourier Transform, Fourier Transform, Laplace Transform, and Z-Transform, (4) emphasis on the relationship between continuous and discrete time signal processing, (5) many examples of using the computer for applying the theory, (6) computer based assignments to gain practical insight, (7) a set of computer programs to aid the reader in applying the theory.
Spectral analysis requires subjective decisions which influence the final estimate and mean that different analysts can obtain different results from the same stationary stochastic observations. Statistical signal processing can overcome this difficulty, producing a unique solution for any set of observations but that is only acceptable if it is close to the best attainable accuracy for most types of stationary data. This book describes a method which fulfils the above near-optimal-solution criterion, taking advantage of greater computing power and robust algorithms to produce enough candidate models to be sure of providing a suitable candidate for given data.
RANDOM DATA A TIMELY UPDATE OF THE CLASSIC BOOK ON THE THEORY AND APPLICATION OF RANDOM DATA ANALYSIS First published in 1971, Random Data served as an authoritative book on the analysis of experimental physical data for engineering and scientific applications. This Fourth Edition features coverage of new developments in random data management and analysis procedures that are applicable to a broad range of applied fields, from the aerospace and automotive industries to oceanographic and biomedical research. This new edition continues to maintain a balance of classic theory and novel techniques. The authors expand on the treatment of random data analysis theory, including derivations of key relationships in probability and random process theory. The book remains unique in its practical treatment of nonstationary data analysis and nonlinear system analysis, presenting the latest techniques on modern data acquisition, storage, conversion, and qualification of random data prior to its digital analysis. The Fourth Edition also includes: A new chapter on frequency domain techniques to model and identify nonlinear systems from measured input/output random data New material on the analysis of multiple-input/single-output linear models The latest recommended methods for data acquisition and processing of random data Important mathematical formulas to design experiments and evaluate results of random data analysis and measurement procedures Answers to the problem in each chapter Comprehensive and self-contained, Random Data, Fourth Edition is an indispensible book for courses on random data analysis theory and applications at the upper-under-graduate and graduate level. It is also an insightful reference for engineers and scientists who use statistical methods to investigate and solve problems with dynamic data.
The NATO Advanced Study Institute on Adaptive Methods in Underwater Acoustics was held on 30 July - 10 August 1984 in LLineburg, Germany. The Institute was primarily concerned with signal processing for underwater appl ica tions. The majority of the presentations, when taken together, yield a definite picture of the present status of understanding of adaptive and high resolution processing, setting out the progress achieved over the past four years together with the major problem areas remaining. Major effort was made to obtain a commensurate contribution of tutorial and advanced research papers. It is my hope that the material in this volume may be equally well suited for students getting an introduction to some of the basic problems in underwater signal processing and for the professionals who may obtain an up-to-date overview of the present state of the art. This might be especially useful in view of the controversy and lack of adequate interrelationships which have marked this rapidly expanding field in the past. Practical reinforcement of this picture is provided by the material concerning digital and optical processing technology, giving some guidance to achievable adaptive and high resolution techniques with current processing devices. The formal programme was extended and detailed by a series of six evening work shops on specific topics, during which informal discussions took place among the participants. Summaries of these workshops are also included in these Proceedings.
Published in 1995: Breath Sounds Methodology is a practical introduction to the measurement of the acoustic properties of the respiratory system. The author describes objective and quantitative methods for extracting the information embedded in the sounds produced in the airways and by the lung during breathing.
