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Neuro-Fuzzy Equalizers for Mobile Cellular Channels (Hardcover, New)
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Neuro-Fuzzy Equalizers for Mobile Cellular Channels (Hardcover, New)
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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 (R) as the simulation
tool in all the above cases
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