信号处理传统上是借助统计工具来实现的，而混沌信号的处理则提供了另一种选择，现实生活中的许多信号的随机性质可以利用非线性动力学来处理。另外，混沌可以利用简单的硬件实现来产生，这使得混沌系统比较容易应用在通信和安全等需要随机信号的学科领域。《混沌信号处理（英文版）》重点介绍了非线性动力学在雷达系统、曰标识别、通信、系统辨识和运算逻辑等众多领域的应用，展示了在这些领域的最新研究成果。

《混沌信号处理（英文版）》既包含了混沌信号处理的基本理论和应用，也讨论了该领域的最新的技术发展。主要内容包括：

·基于非线性动力学的目标识别

·非线性动力学的逻辑学

·利用混沌进行系统辨识

·混沌通信的滤波器设计

·混沌雷达

·利用混沌同步压缩感知

前辅文
1 An Overview of Chaotic Signal Processing
  Henry Leung
  1.1 Introduction
  1.2 Problem Formulation
  1.3 Detection Techniques
  1.4 Estimation Techniques
  1.5 Summary
  References
2 Target Recognition Using Nonlinear Dynamics
  T. L. Carroll and F. J. Rachford
  2.1 Introduction
  2.2 Radar
  2.3 Nonlinear Dynamics
  2.4 Adaptive Maps for Target Identification
  2.5 Signal Processing Methods
  2.6 Conclusions
  References
3 Communicating with Exactly Solvable Chaos
  Ned J. Corron, Jonathan N. Blakely, and Shawn D. Pethel
  3.1 Introduction
  3.2 Communications
  3.3 Exactly Solvable Chaos
  3.4 Symbolic Dynamics Control
  3.5 Matched Filter Receiver
  3.6 Conclusions
  References
4 Logic from Dynamics
  William L. Ditto, Abraham Miliotis, K. Murali, and Sudeshna Sinha
  4.1 Introduction
  4.2 Review of the Chaos Computing Paradigm
  4.3 Direct Implementation of SR Flip-Flop Using a Single Chaotic System
  4.4 Logical Cellular Automata
  4.5 Summary
  References
5 System Identification Using Chaos
  Henry Leung and Ajeesh Kurian
  5.1 Introduction
  5.2 Problem Formulation
  5.3 Blind Equalization Techniques
  5.4 Performance Evaluation
  5.5 Application to Noncoherent Ranging
  5.6 Conclusions
  References
6 Characterization and Optimization of a Chaotic LADAR System for High Resolution Range Determination
  Berenice Verdin and Benjamin C. Flores
  6.1 Introduction
  6.2 Theoretical Background
  6.3 Characterization of Chaotic Signal
  6.4 Optimization of Control Parameters
  6.5 LADAR Implementation
  6.6 Conclusion
  Acknowledgments
  References
7 Reverse Engineering of Complex Dynamical Systems Based on Compressive Sensing
  Ying-Cheng Lai
  7.1 Introduction
  7.2 Predicting Catastrophic Bifurcations in Nonlinear Dynamical Systems
  7.3 Time-Series-Based Prediction of Complex Oscillator Networks
  7.4 Reconstruction of Social Networks Based on Evolutionary-Game Data
  7.5 Conclusions
  References
Index

Henry Leung 是加拿大 Calgary 大学电子和计算机工程系的教授. 他的研究领域为: adaptive complex systems, computational intelligence, data mining, information fusion, nonlinear dynamics, sensor networks, wireless communications. 发表了15余篇论文。

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