This manual will be valuable to practicing engineers who need an introduction to polyspectra from a signal processing perspective. In response to the recent growth of interest in polyspectra, this timely text provides an introduction to signal processing methods that are based on polyspectra and cumulants concepts. The emphasis of the book is placed on the presentation of signal processing tools for use in situations where the more common power spectrum estimation techniques fall short.
This report discusses the detection performance of a variety of higher order spectra for a variety of signals. Of particular significance is the introduction of a new type of higher order spectra called nonstationary higher order spectra. Nonstationary higher order spectra are not the stationary higher order spectral representations of nonstationary process, but are in fact different spectra which contain the stationary higher order spectra as a subset of their domain. It is shown quantitatively through theoretical predictions and simulations that these type of spectra perform better at detecting nonstationary signals than do the traditional stationary spectra. For the first time, small sample statistics have been derived and applied to the detection performance rather than asymptotic statistics, resulting in a more accurate performance prediction for typical sample sizes for nonstationary signals.
Higher-Order Statistical Signal Processing brings together some most recent innovations in the field of higher-order statistical signal processing. It is structured to provide a comprehensive understanding of the fundamentals of the discipline, as well as a treatment of recent advances.
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.
A unified discussion of the formulation and analysis of special methods of mixed initial boundary-value problems. The focus is on the development of a new mathematical theory that explains why and how well spectral methods work. Included are interesting extensions of the classical numerical analysis.
This book is an up-to-date introduction to univariate spectral analysis at the graduate level, which reflects a new scientific awareness of spectral complexity, as well as the widespread use of spectral analysis on digital computers with considerable computational power. The text provides theoretical and computational guidance on the available techniques, emphasizing those that work in practice. Spectral analysis finds extensive application in the analysis of data arising in many of the physical sciences, ranging from electrical engineering and physics to geophysics and oceanography. A valuable feature of the text is that many examples are given showing the application of spectral analysis to real data sets. Special emphasis is placed on the multitaper technique, because of its practical success in handling spectra with intricate structure, and its power to handle data with or without spectral lines. The text contains a large number of exercises, together with an extensive bibliography.
About 123 attendees from the United States, France, United Kingdom, Italy, Japan, and Israel participated in the Workshop on Higher-Order Spectral Analysis. Held in Vail, Colorado, the three day event turned out to be very successful in terms of participation and quality of contributions. The objective of the workshop was to provide a forum for discussion of new theories and methods for processing signals that are based on Higher-Order Spectra. The overwhelming response to its announcement, as well as the breadth and depth of contributions and informal discussions among participants, clearly established that higher-order spectra is a new and emerging technology in signal processing and is expanding rapidly. The workshop featured two tutorial sessions, two keynote addresses, one panel discussion and ten technical sessions. Total of fifty papers were presented. There were no parallel sessions at the workshop. The technical program was truly outstanding. In addition, the workshop provided a very relaxing atmosphere where many informal discussions took place. This final report describes the events, and subject matter. Keywords: Symposia. (kt).
"Spectral Audio Signal Processing is the fourth book in the music signal processing series by Julius O. Smith. One can say that human hearing occurs in terms of spectral models. As a result, spectral models are especially useful in audio applications. For example, with the right spectral model, one can discard most of the information contained in a sound waveform without changing how it sounds. This is the basis of modern audio compression techniques."--Publisher's description.
