Adaptive signal processing (ASP) and iterative signal processing (ISP) are important techniques in improving receiver performance in communication systems. Using examples from practical transceiver designs, this 2006 book describes the fundamental theory and practical aspects of both methods, providing a link between the two where possible. The first two parts of the book deal with ASP and ISP respectively, each in the context of receiver design over intersymbol interference (ISI) channels. In the third part, the applications of ASP and ISP to receiver design in other interference-limited channels, including CDMA and MIMO, are considered; the author attempts to illustrate how the two techniques can be used to solve problems in channels that have inherent uncertainty. Containing illustrations and worked examples, this book is suitable for graduate students and researchers in electrical engineering, as well as practitioners in the telecommunications industry.

This 2006 book describes the fundamental theory and practical aspects of using ASP, and ISP, to improve receiver performance.

Leading experts present the latest research results in adaptive signal processing Recent developments in signal processing have made it clear that significant performance gains can be achieved beyond those achievable using standard adaptive filtering approaches. Adaptive Signal Processing presents the next generation of algorithms that will produce these desired results, with an emphasis on important applications and theoretical advancements. This highly unique resource brings together leading authorities in the field writing on the key topics of significance, each at the cutting edge of its own area of specialty. It begins by addressing the problem of optimization in the complex domain, fully developing a framework that enables taking full advantage of the power of complex-valued processing. Then, the challenges of multichannel processing of complex-valued signals are explored. This comprehensive volume goes on to cover Turbo processing, tracking in the subspace domain, nonlinear sequential state estimation, and speech-bandwidth extension. Examines the seven most important topics in adaptive filtering that will define the next-generation adaptive filtering solutions Introduces the powerful adaptive signal processing methods developed within the last ten years to account for the characteristics of real-life data: non-Gaussianity, non-circularity, non-stationarity, and non-linearity Features self-contained chapters, numerous examples to clarify concepts, and end-of-chapter problems to reinforce understanding of the material Contains contributions from acknowledged leaders in the field Adaptive Signal Processing is an invaluable tool for graduate students, researchers, and practitioners working in the areas of signal processing, communications, controls, radar, sonar, and biomedical engineering.

Moreover, a model-order selection tool, the generalized information criterion (GIC) can be used in conjunction with ST-IAA to further improve the spectrogram quality. Finally, we present several iterative adaptive signal processing approaches to aeroacoustic noise analysis. One of the approaches is based on optimizing the maximum likelihood (ML) criterion via using the Newton's method. The other approaches, referred to as the Frobenius norm (FN) and Rank-1 methods, employ the cyclic optimization algorithm to solve the problem. We also derive the Cram\U+00b4\er-Rao Bounds (CRB) of the unbiased source power estimates. The proposed methods are evaluated using both simulated and measured data. The numerical examples show that these algorithms significantly outperform the existing least squares approach and provide accurate power estimates even under low SNR conditions. Furthermore, the MSEs of the so-obtained estimates are close to the corresponding CRB, especially when the number of data samples is large. The experimental results show that the power estimates obtained by the proposed approaches are consistent with one another.

Advanced Signal Processing for Communication Systems consists of 20 contributions from researchers and experts. The first group of chapters deals with the audio and video processing for communications applications, including topics ranging from multimedia content delivery over the Internet, through the speech processing and recognition to recognition of non-speech sounds that can be attributed to the surrounding environment. The book also includes sections on applications of error control coding, information theory, and digital signal processing for communication systems like modulation, software-defined radio, and channel estimation. Advanced Signal Processing for Communication Systems is written for researchers working on communication systems and signal processing, as well as telecommunications industry professionals.

Presents the concept of Optimum and Adaptive Signal Processing, while providing a straightforward explanation of all the intermediate steps in a mathematical expression derivation and its physical meaning. Chapters 1-8 and 9-17, addressing, respectively, optimum signal processing and adaptive signal processing, can serve as separate texts.

The creation of the text really began in 1976 with the author being involved with a group of researchers at Stanford University and the Naval Ocean Systems Center, San Diego. At that time, adaptive techniques were more laboratory (and mental) curiosities than the accepted and pervasive categories of signal processing that they have become. Over the lasl 10 years, adaptive filters have become standard components in telephony, data communications, and signal detection and tracking systems. Their use and consumer acceptance will undoubtedly only increase in the future. The mathematical principles underlying adaptive signal processing were initially fascinating and were my first experience in seeing applied mathematics work for a paycheck. Since that time, the application of even more advanced mathematical techniques have kept the area of adaptive signal processing as exciting as those initial days. The text seeks to be a bridge between the open literature in the professional journals, which is usually quite concentrated, concise, and advanced, and the graduate classroom and research environment where underlying principles are often more important.