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Author: Yecai Guo Publisher: World Scientific ISBN: 9811249466 Category : Technology & Engineering Languages : en Pages : 449
Book Description
This comprehensive compendium highlights the research results of nonlinear channel modeling and simulation. Nonlinear channels include nonlinear satellite channels, nonlinear Volterra channels, molecular MIMO channels, etc.This volume involves wavelet theory, neural network, echo state network, machine learning, support vector machine, chaos calculation, principal component analysis, Markov chain model, correlation entropy, fuzzy theory and other theories for nonlinear channel modeling and equalization.The useful reference text enriches the theoretical system of nonlinear channel modeling and improving the means of establishing nonlinear channel model. It is suitable for engineering technicians, researchers and graduate students in information and communication engineering, and control science and engineering, intelligent science and technology.
Author: Yecai Guo Publisher: World Scientific ISBN: 9811249466 Category : Technology & Engineering Languages : en Pages : 449
Book Description
This comprehensive compendium highlights the research results of nonlinear channel modeling and simulation. Nonlinear channels include nonlinear satellite channels, nonlinear Volterra channels, molecular MIMO channels, etc.This volume involves wavelet theory, neural network, echo state network, machine learning, support vector machine, chaos calculation, principal component analysis, Markov chain model, correlation entropy, fuzzy theory and other theories for nonlinear channel modeling and equalization.The useful reference text enriches the theoretical system of nonlinear channel modeling and improving the means of establishing nonlinear channel model. It is suitable for engineering technicians, researchers and graduate students in information and communication engineering, and control science and engineering, intelligent science and technology.
Author: Han-Xiong Li Publisher: Springer Science & Business Media ISBN: 940070741X Category : Mathematics Languages : en Pages : 175
Book Description
The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein systems and their identifi cation methods. Then, the traditional Volterra model is extended to DPS, which results in the spatio-temporal Volterra model and its identification algorithm. All these methods are based on linear time/space separation. Sometimes, the nonlinear time/space separation can play a better role in modeling of very complex processes. Thus, a nonlinear time/space separation based neural modeling is also presented for a class of DPS with more complicated dynamics. Finally, all these modeling approaches are successfully applied to industrial thermal processes, including a catalytic rod, a packed-bed reactor and a snap curing oven. The work is presented giving a unifi ed view from time/space separation. The book also illustrates applications to thermal processes in the electronics packaging and chemical industry. This volume assumes a basic knowledge about distributed parameter systems, system modeling and identifi cation. It is intended for researchers, graduate students and engineers interested in distributed parameter systems, nonlinear systems, and process modeling and control.
Author: Danilo Comminiello Publisher: Butterworth-Heinemann ISBN: 0128129778 Category : Technology & Engineering Languages : en Pages : 390
Book Description
Adaptive Learning Methods for Nonlinear System Modeling presents some of the recent advances on adaptive algorithms and machine learning methods designed for nonlinear system modeling and identification. Real-life problems always entail a certain degree of nonlinearity, which makes linear models a non-optimal choice. This book mainly focuses on those methodologies for nonlinear modeling that involve any adaptive learning approaches to process data coming from an unknown nonlinear system. By learning from available data, such methods aim at estimating the nonlinearity introduced by the unknown system. In particular, the methods presented in this book are based on online learning approaches, which process the data example-by-example and allow to model even complex nonlinearities, e.g., showing time-varying and dynamic behaviors. Possible fields of applications of such algorithms includes distributed sensor networks, wireless communications, channel identification, predictive maintenance, wind prediction, network security, vehicular networks, active noise control, information forensics and security, tracking control in mobile robots, power systems, and nonlinear modeling in big data, among many others. This book serves as a crucial resource for researchers, PhD and post-graduate students working in the areas of machine learning, signal processing, adaptive filtering, nonlinear control, system identification, cooperative systems, computational intelligence. This book may be also of interest to the industry market and practitioners working with a wide variety of nonlinear systems. - Presents the key trends and future perspectives in the field of nonlinear signal processing and adaptive learning. - Introduces novel solutions and improvements over the state-of-the-art methods in the very exciting area of online and adaptive nonlinear identification. - Helps readers understand important methods that are effective in nonlinear system modelling, suggesting the right methodology to address particular issues.
Author: José Carlos Pedro Publisher: Cambridge University Press ISBN: 1108646417 Category : Technology & Engineering Languages : en Pages : 362
Book Description
Discover the nonlinear methods and tools needed to design real-world microwave circuits with this tutorial guide. Balancing theoretical background with practical tools and applications, it covers everything from the basic properties of nonlinear systems such as gain compression, intermodulation and harmonic distortion, to nonlinear circuit analysis and simulation algorithms, and state-of-the-art equivalent circuit and behavioral modeling techniques. Model formulations discussed in detail include time-domain transistor compact models and frequency-domain linear and nonlinear scattering models. Learn how to apply these tools to designing real circuits with the help of a power amplifier design example, which covers all stages from active device model extraction and the selection of bias and terminations, through to performance verification. Realistic examples, illustrative insights and clearly conveyed mathematical formalism make this an essential learning aid for both professionals working in microwave and RF engineering and graduate students looking for a hands-on guide to microwave circuit design.
Author: Khaled M. Gharaibeh Publisher: John Wiley & Sons ISBN: 1119964113 Category : Technology & Engineering Languages : en Pages : 387
Book Description
This book covers the principles of modeling and simulation of nonlinear distortion in wireless communication systems with MATLAB simulations and techniques In this book, the author describes the principles of modeling and simulation of nonlinear distortion in single and multichannel wireless communication systems using both deterministic and stochastic signals. Models and simulation methods of nonlinear amplifiers explain in detail how to analyze and evaluate the performance of data communication links under nonlinear amplification. The book addresses the analysis of nonlinear systems with stochastic inputs and establishes the performance metrics of communication systems with regard to nonlinearity. In addition, the author also discusses the problem of how to embed models of distortion in system-level simulators such as MATLAB and MATLAB Simulink and provides practical techniques that professionals can use on their own projects. Finally, the book explores simulation and programming issues and provides a comprehensive reference of simulation tools for nonlinearity in wireless communication systems. Key Features: Covers the theory, models and simulation tools needed for understanding nonlinearity and nonlinear distortion in wireless systems Presents simulation and modeling techniques for nonlinear distortion in wireless channels using MATLAB Uses random process theory to develop simulation tools for predicting nonlinear system performance with real-world wireless communication signals Focuses on simulation examples of real-world communication systems under nonlinearity Includes an accompanying website containing MATLAB code This book will be an invaluable reference for researchers, RF engineers, and communication system engineers working in the field. Graduate students and professors undertaking related courses will also find the book of interest.
Author: Soner Özgünel Publisher: ISBN: Category : Languages : en Pages :
Book Description
The objective of this thesis is to investigate the equalization and identification of the Volterra type of nonlinear channels using the multichannel adaptive lattice algorithms. The main contribution appears as the development of a new single input-multiple output system used in the models for the equalization and identification of nonlinear channels. This system is so defined that it takes a sequence of signals as its input and produces an output in the form of a vector with its elements obtained by the input and its delayed versions. Determination of the structure of the system is the crucial point here. It is so defined that the structures of the multichannel adaptive lattice equalizer and identifier models match to the nonlinear structure of the channel.In the first part of the thesis, a multichannel adaptive lattice equalizer model is developed using the above mentioned single input-multiple output system, and applied to the equalization of a second-order Volterra type of nonlinear channel. The performance of the model is investigated in the base of learning curves by some computer simulations examined for different parameters, such as channel noise, lattice length and step-size of the algorithm. In the second part, a multichannel adaptive lattice identifier model is developed using the single input-multiple output system, and applied to the identification of the same example of second-order nonlinear channel. The performance of the model is investigated in two parts, first in the base of learning curves and then in the base of estimating the linear and quadratic weights of the channel. The performance analysis is done for different parameters as in the equalization part.Finally, the equalization and identification of digital satellite channels are investigated. These channels have such a nonlinear structure that can be modeled by a Volterra series of higher-order, and therefore the structure of the single input-multiple output system is so defined that its output has the same order of nonlinearity as that of the channel. This means that the structure of the system matches to that of the channel. This single input-multiple output system is used in the multichannel adaptive lattice equalizer and identifier models, and their performances are investigated for a numerical example of 4-CPSK nonlinear satellite channel.
Author: Lipo Wang Publisher: Springer Science & Business Media ISBN: 9783540405757 Category : Mathematics Languages : en Pages : 424
Book Description
Soft computing, as opposed to conventional "hard" computing, tolerates imprecision and uncertainty, in a way very much similar to the human mind. Soft computing techniques include neural networks, evolutionary computation, fuzzy logic, and chaos. The recent years have witnessed tremendous success of these powerful methods in virtually all areas of science and technology, as evidenced by the large numbers of research results published in a variety of journals, conferences, as weil as many excellent books in this book series on Studies in Fuzziness and Soft Computing. This volume is dedicated to recent novel applications of soft computing in communications. The book is organized in four Parts, i.e., (1) neural networks, (2) evolutionary computation, (3) fuzzy logic and neurofuzzy systems, and (4) kernel methods. Artificial neural networks consist of simple processing elements called neurons, which are connected by weights that may be adjusted during learning. Part 1 of the book has seven chapters, demonstrating some of the capabilities of two major types of neural networks, i.e., multiplayer perceptron (MLP) neural networks and Hopfield-type neural networks.
Author: Johan A.K. Suykens Publisher: Springer Science & Business Media ISBN: 1461557038 Category : Technology & Engineering Languages : en Pages : 265
Book Description
Nonlinear Modeling: Advanced Black-Box Techniques discusses methods on Neural nets and related model structures for nonlinear system identification; Enhanced multi-stream Kalman filter training for recurrent networks; The support vector method of function estimation; Parametric density estimation for the classification of acoustic feature vectors in speech recognition; Wavelet-based modeling of nonlinear systems; Nonlinear identification based on fuzzy models; Statistical learning in control and matrix theory; Nonlinear time-series analysis. It also contains the results of the K.U. Leuven time series prediction competition, held within the framework of an international workshop at the K.U. Leuven, Belgium in July 1998.
Author: Yecai Guo
Author: Yecai Guo
Author: Han-Xiong Li
Author: Danilo Comminiello
Author: José Carlos Pedro
Author: José Carlos Pedro
Author: Khaled M. Gharaibeh
Author: Soner Özgünel
Author: Lipo Wang
Author: Robert Haber
Author: Johan A.K. Suykens