Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
One of the major practical problems in digital communication systems is channel distortion which causes errors due to intersymbol interference. Since the source signal is in general broadband, the various frequency components experience different steady state amplitude and phase changes as they pass through the channel, causing distortion in the received message. This distortion translates into errors in the received sequence. Our problem as communication engineers is to restore the transmitted sequence or, equivalently, to identify the inverse of the channel, given the observed sequence at the channel output. This task is accomplished by adaptive equalizers. Typically, adaptive equalizers used in digital communications require an initial training period, during which a known data sequence is transmitted. A replica of this sequence is made available at the receiver in proper synchronism with the transmitter, thereby making it possible for adjustments to be made to the equalizer coefficients in accordance with the adaptive filtering algorithm employed in the equalizer design. When the training is completed, the equalizer is switched to its decision directed mode. Decision feedback equalizers are used extensively in practical communication systems. They are more powerful than linear equalizers especially for severe inter-symbol interference (ISI) channels without as much noise enhancement as the linear equalizers. This thesis addresses the problem of adaptive channel equalization in environments where the interfering noise exhibits Gaussian behavior. In this thesis, radial basis function (RBF) network is used to implement DFE. Advantages and problems of this system are discussed and its results are then compared with DFE using multi layer perceptron net (MLP). Results indicate that the implemented system outperforms both the least-mean square(LMS) algorithm and MLP, given the same signal-to-noise ratio as it offers minimum mean square error. The learning rate of the im.
Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
The field of digital data communications has experienced an explosive growth in the last three decade with the growth of internet technologies, high speed and efficient data transmission over communication channel has gained significant importance. The rate of data transmissions over a communication system is limited due to the effects of linear and nonlinear distortion. Linear distortions occure in from of inter-symbol interference (ISI), co-channel interference (CCI) and adjacent channel interference (ACI) in the presence of additive white Gaussian noise. Nonlinear distortions are caused due to the subsystems like amplifiers, modulator and demodulator along with nature of the medium. Some times burst noise occurs in communication system. Different equalization techniques are used to mitigate these effects. Adaptive channel equalizers are used in digital communication systems. The equalizer located at the receiver removes the effects of ISI, CCI, burst noise interference and attempts to recover the transmitted symbols. It has been seen that linear equalizers show poor performance, where as nonlinear equalizer provide superior performance. Artificial neural network based multi layer perceptron (MLP) based equalizers have been used for equalization in the last two decade. The equalizer is a feed-forward network consists of one or more hidden nodes between its input and output layers and is trained by popular error based back propagation (BP) algorithm. However this algorithm suffers from slow convergence rate, depending on the size of network. It has been seen that an optimal equalizer based on maximum a-posterior probability (MAP) criterion can be implemented using Radial basis function (RBF) network. In a RBF equalizer, centres are fixed using K-mean clustering and weights are trained using LMS algorithm. RBF equalizer can mitigate ISI interference effectively providing minimum BER plot. But when the input order is increased the number of centre of the network incr.
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: Paulo S. R. Diniz Publisher: Springer Science & Business Media ISBN: 1461441064 Category : Technology & Engineering Languages : en Pages : 664
Book Description
In the fourth edition of Adaptive Filtering: Algorithms and Practical Implementation, author Paulo S.R. Diniz presents the basic concepts of adaptive signal processing and adaptive filtering in a concise and straightforward manner. The main classes of adaptive filtering algorithms are presented in a unified framework, using clear notations that facilitate actual implementation. The main algorithms are described in tables, which are detailed enough to allow the reader to verify the covered concepts. Many examples address problems drawn from actual applications. New material to this edition includes: Analytical and simulation examples in Chapters 4, 5, 6 and 10 Appendix E, which summarizes the analysis of set-membership algorithm Updated problems and references Providing a concise background on adaptive filtering, this book covers the family of LMS, affine projection, RLS and data-selective set-membership algorithms as well as nonlinear, sub-band, blind, IIR adaptive filtering, and more. Several problems are included at the end of chapters, and some of these problems address applications. A user-friendly MATLAB package is provided where the reader can easily solve new problems and test algorithms in a quick manner. Additionally, the book provides easy access to working algorithms for practicing engineers.
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: K.C. Raveendranathan Publisher: CRC Press ISBN: 135183178X Category : Computers Languages : en Pages : 238
Book Description
Equalizers are present in all forms of communication systems. Neuro-Fuzzy Equalizers for Mobile Cellular Channels details the modeling of a mobile broadband communication channel and designing of a neuro-fuzzy adaptive equalizer for it. This book focuses on the concept of the simulation of wireless channel equalizers using the adaptive-network-based fuzzy inference system (ANFIS). The book highlights a study of currently existing equalizers for wireless channels. It discusses several techniques for channel equalization, including the type-2 fuzzy adaptive filter (type-2 FAF), compensatory neuro-fuzzy filter (CNFF), and radial basis function (RBF) neural network. Neuro-Fuzzy Equalizers for Mobile Cellular Channels starts with a brief introduction to channel equalizers, and the nature of mobile cellular channels with regard to the frequency reuse and the resulting CCI. It considers the many channel models available for mobile cellular channels, establishes the mobile indoor channel as a Rayleigh fading channel, presents the channel equalization problem, and focuses on various equalizers for mobile cellular channels. The book discusses conventional equalizers like LE and DFE using a simple LMS algorithm and transversal equalizers. It also covers channel equalization with neural networks and fuzzy logic, and classifies various equalizers. This being a fairly new branch of study, the book considers in detail the concept of fuzzy logic controllers in noise cancellation problems and provides the fundamental concepts of neuro-fuzzy. The final chapter offers a recap and explores venues for further research. This book also establishes a common mathematical framework of the equalizers using the RBF model and develops a mathematical model for ultra-wide band (UWB) channels using the channel co-variance matrix (CCM). Introduces the novel concept of the application of adaptive-network-based fuzzy inference system (ANFIS) in the design of wireless channel equalizers Provides model ultra-wide band (UWB) channels using channel co-variance matrix Offers a formulation of a unified radial basis function (RBF) framework for ANFIS-based and fuzzy adaptive filter (FAF) Type II, as well as compensatory neuro-fuzzy equalizers Includes extensive use of MATLAB® as the simulation tool in all the above cases
Author: Lino Garcia Morales Publisher: BoD – Books on Demand ISBN: 9533073063 Category : Technology & Engineering 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: Masoud Mohammadian Publisher: IOS Press ISBN: 9789051994766 Category : Computational intelligence Languages : en Pages : 396
Book Description
Computational Intelligence is a broad and active research area that is growing rapidly due to the many successful applications of these new techniques in very diverse problems. Many industries have benefited from adopting this technology. The increased number of patents and diverse range of products developed using computational intelligence methods is evidence of this fact. The goal of this book is to provide highlights of the current research in computational intelligence area. The book consists of research papers in the fields of neural networks, fuzzy logic, evolutionary computing, hybrid evolutionary computing-fuzzy logic systems, hybrid neural networks-evolutionary computing and fuzzy logic systems, image processing and vision, advances in robotics, control and manufacturing, and rough sets.
Author: Diego Andina Publisher: Springer Science & Business Media ISBN: 0387374523 Category : Computers Languages : en Pages : 220
Book Description
Computational Intelligence is tolerant of imprecise information, partial truth and uncertainty. This book presents a selected collection of contributions on a focused treatment of important elements of CI, centred on its key element: learning. This book presents novel applications and real world applications working in Manufacturing and Engineering, and it sets a basis for understanding Domotic and Production Methods of the XXI Century.
Author: Sudeep Tanwar Publisher: CRC Press ISBN: 1000487792 Category : Technology & Engineering Languages : en Pages : 389
Book Description
Machine Learning in Signal Processing: Applications, Challenges, and the Road Ahead offers a comprehensive approach toward research orientation for familiarizing signal processing (SP) concepts to machine learning (ML). ML, as the driving force of the wave of artificial intelligence (AI), provides powerful solutions to many real-world technical and scientific challenges. This book will present the most recent and exciting advances in signal processing for ML. The focus is on understanding the contributions of signal processing and ML, and its aim to solve some of the biggest challenges in AI and ML. FEATURES Focuses on addressing the missing connection between signal processing and ML Provides a one-stop guide reference for readers Oriented toward material and flow with regards to general introduction and technical aspects Comprehensively elaborates on the material with examples and diagrams This book is a complete resource designed exclusively for advanced undergraduate students, post-graduate students, research scholars, faculties, and academicians of computer science and engineering, computer science and applications, and electronics and telecommunication engineering.
Author: 
Author: 
Author: Lino Garcia Morales
Author: Paulo S. R. Diniz
Author: Chuan-Chin Pu
Author: K.C. Raveendranathan
Author: Lino Garcia Morales
Author: Masoud Mohammadian
Author: Diego Andina
Author: Sudeep Tanwar