宋國(guó)棟 張懷遠(yuǎn)

摘要：通過(guò)對(duì)歸一化LMS算法（NLMS）進(jìn)行拉格朗日方程最小值運(yùn)算而得到的CS-LMS算法具有良好的收斂性和靈活性。該文為進(jìn)一步解決自適應(yīng)濾波算法不能有效處理既要求收斂速度快又要求穩(wěn)態(tài)誤差小的矛盾,建立了步長(zhǎng)與信號(hào)誤差之間的一種非線性函數(shù)模型，并將改進(jìn)的CS-LMS算法應(yīng)用到混沌通信中。仿真結(jié)果表明,改進(jìn)算法的收斂速度和穩(wěn)態(tài)誤差性能都有較大的提高。

關(guān)鍵詞：LMS；步長(zhǎng)；非線性函數(shù)模型；自適應(yīng)CS-LMS算法；混沌通信

中圖分類號(hào)：TP311文獻(xiàn)標(biāo)識(shí)碼：A文章編號(hào)：1009-3044(2012)16-3867-02

An Improved Adaptive CS-LMS Algorithm and its Performance Analysis in Chaotic Communication

SONG Guo-dong, ZHANG Huai-yuan

(Electronic and Information Engineering College of Southwest University , Chongqing 400715,China)

Abstract: CS-LMS algorithm provides faster convergence and higher flexibility than the normalized least mean square (NLMS) by mini? mizing the Lagrangian function. This paper, in order to solve adaptive filters conflict of gaining the fast convergence speed and low steady state error, a non- linear functional model between step size and signal error will be established, and we will continue to apply this new al? gorithm to chaotic communication. Simulation results present the proposed algorithm enhances the speed of convergence and quality of sta? bility distinctly.

Key words: LMS; step size; a non- Linear functional model; adaptive CS-LMS filter; chaotic communication

該文給出的改進(jìn)的CS-LMS算法,是在步長(zhǎng)參數(shù)μ與誤差信號(hào)e(n)之間建立了一種新的非線性函數(shù)關(guān)系,該算法與傳統(tǒng)LMS和CS-LMS算法自適應(yīng)濾波算法相比，具有較快的收斂速率并且在高信噪比下穩(wěn)態(tài)誤差方面表現(xiàn)的比較優(yōu)越，但在仿真中也發(fā)現(xiàn)，非線性函數(shù)中的參數(shù)對(duì)算法性能有著決定性的影響，所以一定要結(jié)合實(shí)際情況合理選擇各類步長(zhǎng)參數(shù)。

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