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Author: Chuan-Chin Pu Publisher: LAP Lambert Academic Publishing ISBN: 9783838320144 Category : Languages : en Pages : 120
Book Description
Digital communications over bandlimited channels often encounter the problem of intersymbol interference (ISI), which can degrade signal quality down to an unacceptable level. As such, a channel equaliser is usually used at the receiving end to mitigate the ISI. This book presents study of adaptive channel equalisation based on soft- computing techniques. The main types of equalisers considered in this book are based on fuzzy neural networks (FNNs) and radial basis function networks (RBFNs). The training procedures used to adapt the networks include back propagation (BP) for FNN, and a combination of unsupervised (K-means) and supervised (Least mean square, LMS) learning for RBFN. Minimal resource allocation network (MRAN) is also discussed. The performances of the RBFN and FNN- based equalisers are evaluated by comparing with the conventional linear transversal equaliser (LTE) and the multilayer perceptron (MLP) based equalisers. Simulation results are included to demonstrate the performance of each network and algorithm.
Author: Chuan-Chin Pu Publisher: LAP Lambert Academic Publishing ISBN: 9783838320144 Category : Languages : en Pages : 120
Book Description
Digital communications over bandlimited channels often encounter the problem of intersymbol interference (ISI), which can degrade signal quality down to an unacceptable level. As such, a channel equaliser is usually used at the receiving end to mitigate the ISI. This book presents study of adaptive channel equalisation based on soft- computing techniques. The main types of equalisers considered in this book are based on fuzzy neural networks (FNNs) and radial basis function networks (RBFNs). The training procedures used to adapt the networks include back propagation (BP) for FNN, and a combination of unsupervised (K-means) and supervised (Least mean square, LMS) learning for RBFN. Minimal resource allocation network (MRAN) is also discussed. The performances of the RBFN and FNN- based equalisers are evaluated by comparing with the conventional linear transversal equaliser (LTE) and the multilayer perceptron (MLP) based equalisers. Simulation results are included to demonstrate the performance of each network and algorithm.
Author: Paulo S.R. Diniz Publisher: Springer Science & Business Media ISBN: 1475736371 Category : Technology & Engineering Languages : en Pages : 582
Book Description
Adaptive Filtering: Algorithms and Practical Implementation, Second Edition, presents a concise overview of adaptive filtering, covering as many algorithms as possible in a unified form that avoids repetition and simplifies notation. It is suitable as a textbook for senior undergraduate or first-year graduate courses in adaptive signal processing and adaptive filters. The philosophy of the presentation is to expose the material with a solid theoretical foundation, to concentrate on algorithms that really work in a finite-precision implementation, and to provide easy access to working algorithms. Hence, practicing engineers and scientists will also find the book to be an excellent reference. This second edition contains a substantial amount of new material: -Two new chapters on nonlinear and subband adaptive filtering; -Linearly constrained Weiner filters and LMS algorithms; -LMS algorithm behavior in fast adaptation; -Affine projection algorithms; -Derivation smoothing; -MATLAB codes for algorithms.
Author: Cs. Banyasz Publisher: Elsevier ISBN: 148329689X Category : Technology & Engineering Languages : en Pages : 491
Book Description
Leading academic and industrial researchers working with adaptive systems and signal processing have been given the opportunity to exchange ideas, concepts and solutions at the IFAC Symposia on Adaptive Systems in Control and Signal Processing. This postprint volume contains all those papers which were presented at the 5th IFAC Symposium in Budapest in 1995. The technical program was composed of a number of invited and contributed sessions and a special case study session, providing a good balance between applications and theory oriented papers.
Author: Tülay Adali Publisher: John Wiley & Sons ISBN: 0470575743 Category : Science Languages : en Pages : 428
Book Description
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.
Author: Lino Garcia Morales Publisher: BoD – Books on Demand ISBN: 9533071583 Category : Computers Languages : en Pages : 414
Book Description
Adaptive filtering is useful in any application where the signals or the modeled system vary over time. The configuration of the system and, in particular, the position where the adaptive processor is placed generate different areas or application fields such as prediction, system identification and modeling, equalization, cancellation of interference, etc., which are very important in many disciplines such as control systems, communications, signal processing, acoustics, voice, sound and image, etc. The book consists of noise and echo cancellation, medical applications, communications systems and others hardly joined by their heterogeneity. Each application is a case study with rigor that shows weakness/strength of the method used, assesses its suitability and suggests new forms and areas of use. The problems are becoming increasingly complex and applications must be adapted to solve them. The adaptive filters have proven to be useful in these environments of multiple input/output, variant-time behaviors, and long and complex transfer functions effectively, but fundamentally they still have to evolve. This book is a demonstration of this and a small illustration of everything that is to come.
Author: Weifeng Liu Publisher: John Wiley & Sons ISBN: 1118211219 Category : Science Languages : en Pages : 167
Book Description
Online learning from a signal processing perspective There is increased interest in kernel learning algorithms in neural networks and a growing need for nonlinear adaptive algorithms in advanced signal processing, communications, and controls. Kernel Adaptive Filtering is the first book to present a comprehensive, unifying introduction to online learning algorithms in reproducing kernel Hilbert spaces. Based on research being conducted in the Computational Neuro-Engineering Laboratory at the University of Florida and in the Cognitive Systems Laboratory at McMaster University, Ontario, Canada, this unique resource elevates the adaptive filtering theory to a new level, presenting a new design methodology of nonlinear adaptive filters. Covers the kernel least mean squares algorithm, kernel affine projection algorithms, the kernel recursive least squares algorithm, the theory of Gaussian process regression, and the extended kernel recursive least squares algorithm Presents a powerful model-selection method called maximum marginal likelihood Addresses the principal bottleneck of kernel adaptive filters—their growing structure Features twelve computer-oriented experiments to reinforce the concepts, with MATLAB codes downloadable from the authors' Web site Concludes each chapter with a summary of the state of the art and potential future directions for original research Kernel Adaptive Filtering is ideal for engineers, computer scientists, and graduate students interested in nonlinear adaptive systems for online applications (applications where the data stream arrives one sample at a time and incremental optimal solutions are desirable). It is also a useful guide for those who look for nonlinear adaptive filtering methodologies to solve practical problems.
Author: Stefano Basagni Publisher: ISBN: Category : Ad hoc networks (Computer networks) Languages : en Pages : 15
Book Description
A distributed algorithm is presented that partitions the nodes of a fully mobile network (ad hoc network) into clusters, thus giving the network a hierarchical organization. The algorithm is proven to be adaptive to changes in the network topology due to nodes' mobility and to nodes addition/removal. A new weight-based mechanism is introduced for the efficient cluster formation/maintenance that allows the cluster organization to be configured for specific applications and adaptive to changes in the network status, not available in previous solutions. Simulation results are provided that demonstrate up to an 85% reduction on the communication overhead associated with the cluster maintenance with respect to clustering algorithms previously proposed.
Author: Chuan-Chin Pu
Author: Chuan-Chin Pu
Author: Anuradha K. Kamath
Author: Paulo S.R. Diniz
Author: Andrew Storm
Author: Cs. Banyasz
Author: Tülay Adali
Author: Lino Garcia Morales
Author: Weifeng Liu
Author: 
Author: Stefano Basagni