混沌信號的重構(gòu)及其在基于混沌的通信中的應(yīng)用

內(nèi)容概要

本書系統(tǒng)地總結(jié)了作者近年來涉及的嵌入在基于混沌的通信中的最基本問題——混沌信號的重構(gòu)及其應(yīng)用的研究成果，覆蓋了關(guān)于混純信號重構(gòu)的基本問題和幾個(gè)高層次的問題。共分為四個(gè)層次進(jìn)行深入的論述：1在無噪聲的信道里如何重構(gòu)原始混沌信號，這是將Takens定理推廣到時(shí)變的連續(xù)時(shí)間與離散時(shí)間系統(tǒng)，2如何通過噪聲污染的混沌信號重構(gòu)原始混沌系統(tǒng)的動(dòng)力學(xué)，3如何通過噪聲污染同時(shí)也被信道畸變的混沌信號重構(gòu)原始混沌系統(tǒng)的動(dòng)力學(xué)，4基于混沌同步的思想重構(gòu)原始混沌系統(tǒng)的動(dòng)力學(xué)。所有這些問題都是圍繞基于混沌的寬帶通信在實(shí)際通信環(huán)境里的實(shí)現(xiàn)為研究目的。    該書對于信號與信息處理、非線性電路、通信、智能信息處理和自動(dòng)化等學(xué)科的大專院校高年級學(xué)生和有關(guān)研究人員具有很強(qiáng)的可讀性和重要的參考價(jià)值，并能起到拋起引玉的作用。

書籍目錄

PrefaceAcknowledgements1  Chaos and Communications  1.1 Historical Account  1.2 Chaos  1.3 Quantifying Chaotic Behavior  1.4 Properties of Chaos  1.5 Chaos-Based Communications  1.6 Communcations Using Chaos as Carriers  1.7 Remarks on Chaos-Based Communications2  Reconstruction of Signals  2.1 Reconstruction of System Dynamics  2.2 Differentable Embeddings  2.3 Phase Space Reconstruction-Example  2.4 Problems and Research Approaches3  Fundamentals of Neural Networks  3.1 Motivation  3.2 Benefits of Neural Networks  3.3 Radial Basis Function Neural Networks  3.4 Recurrent Neural Networks4  Signal Reconstrucion in Noisefree and Distortionless Channels  4.1 Reconstruction of Attractor for Continuous Time-Varying Systems  4.2 Reconstruction and Observability  4.3 Communication Based on Reconstruction Approach  4.4 Reconstruction of Attractor of r Discrete Time-Varying Systems  4.5 Summary5  Signal Reconsturcation from a Filtering Viewpoint:Theory  5.1 The Kalman Filter and Extended Kalman Filter  5.2 The Unscented Kalman Filter  5.3 Summary6  Signal Reconstruction from a Filtering Viewpoint:Application  6.1 Interoduction  6.2 Filtering of Noisy Chaotic Signals  6.3 Blind Equalization for Fading Channels  6.4 Summary7  Signal Reconstruction in Noisy Channels8  Signal Reconstruction in Noisy Distorted Channels9  Chaotic Network Synchronization and Its Applications in Communications10  ConclusionsBibliographyIndex

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