K.C. Raveendranathan's Books

Neuro-Fuzzy Equalizers for Mobile Cellular Channels

By: K.C. Raveendranathan

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Neuro-Fuzzy Equalizers for Mobile Cellular Channels

By: K.C. Raveendranathan

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

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Page Count

238

Publisher

CRC Press

Published Date

ISBN 10

135183178X

ISBN 13

9781351831789

Signal Processing Techniques for Communication

By: K.C. Raveendranathan

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Signal Processing Techniques for Communication

By: K.C. Raveendranathan

The reference text discusses signal processing tools and techniques used for the design, testing, and deployment of communication systems. It further explores software simulation and modeling tools like MATLAB, GNU Octave, Mathematica, and Python for modeling, simulation, and detailed analysis leading to comprehensive insights into communication systems. The book explains topics such as source coding, pulse demodulation systems, and the principle of sampling and aliasing. This book: Discusses modern techniques including analog and digital filter design, and modulation principles including quadrature amplitude modulation, and differential phase shift keying. Covers filter design using MATLAB, system simulation using Simulink, signal processing toolbox, linear time-invariant systems, and non-linear time-variant systems. Explains important pulse keying techniques including Gaussian minimum shift keying and quadrature phase shift keying. Presents signal processing tools and techniques for communication systems design, modeling, simulation, and deployment. Illustrates topics such as software-defined radio (SDR) systems, spectrum sensing, and automated modulation sensing. The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer science, and engineering.

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