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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/1298

Title: 混沌序列扩频信号特征分析
Other Titles: The Characteristic Analysis of Chaotic Spreading Time Series
Authors: 申深
清华大学电机系
Keywords: 最大李雅普诺夫指数
相关性
功率谱密度
maximal Lyapunov exponent
correlation
power spectrum density
Issue Date: 16-Jun-2008
Abstract: 针对10种由混沌映射产生的扩频信号,通过研究其最大李雅普诺夫指数、相关性和功率谱密度等混沌动力学以及统计学的特性,证明了混沌时间扩频序列能够保留混沌序列的特性,相对传统扩频序列做为扩频码具有优越性。此外,采用对混沌序列扩频信号叠加高斯白噪声和实现数字低通滤波的方法,分析噪声、高频成分对混沌时间扩频序列动力学特性的影响。
Based on ten chaotic spreading time series generated from iteration of chaotic maps, such chaotic dynamic and statistical characters as maximal Lyapunov exponent, correlation function, and power spectrum density are calculated, respectively, which indicate chaotic spreading time series have the key feature to well retain chaotic properties, with better performance as spreading codes, comparing to traditional spreading time series. In addition, added Gaussian white noise and a digital low-pass filter are investigated in order to analyze the characters of chaotic time series used as spreading time series, as well as the influences caused by noise and high frequency component
Description: 参考文献21
URI: http://hdl.handle.net/123456789/1298
Appears in Collections:本科生优秀毕业论文(2008)

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