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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. 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.

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    Joshua Schroeder. Introduction to Wireless Digital Communication. Robert W. Heath Jr. Distributed Multiple Description Coding. Huihui Bai. Shahid Mumtaz. Software Defined Networks. Paul Goransson. 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. It also covers channel equalization with neural networks and fuzzy logic, and classifies various equalizers.