本論文主旨在探討混沌通訊的適應性盲蔽式通道等化，提出了一種在接收端以使用延伸型卡爾曼濾波器為基礎的混沌通訊系統設計。首先，利用最佳線性化方法來找出混沌系統操作點的精確線性化模型，然後把多重路徑和時變的通道參數化成自回歸模型。盲蔽式通道等化可視為一種估測混合非線性參數和狀態的問題，從自回歸模型建立出一盲蔽式聯合通道與信號估測準則，然後使用延伸型卡爾曼濾波器來估測已加入訊號的系統參數與狀態。經由延伸型卡爾曼濾波器與最佳線性化模型的設計，可以在接收端將傳輸訊號完整地估測出來。由例題和模擬結果可顯示出本方法的效能。

　　A blind-channel equalization for the extended-Kalman-filter-based chaotic communication is first proposed in this thesis. First, the optimal linearization technique is utilized to find the exact linear models of the chaotic system at operating states of interest. The proposed blind-channel equalization is formulated as a mixed nonlinear parameter and state estimation problem by an autoregressive (AR) model. The channel coefficients of a fading and multipath channel can be represented by an AR process. Then, an extended Kalman filter algorithm is utilized to reduce the effect of channel noise. By using the extended Kalman filter, the channel coefficients and the state of the system which is the signal before going through the channel can be estimated. The stability problem of the proposed blind-channel equalization is also addressed. Numerical examples and simulations are given to show the effectiveness and the speed of convergence for the proposed methodology.

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