由于混沌系统具有对小信号的敏感性及对噪声的免疫性等特点，使得混沌在信息检测技术中具有很好的发展前景。
Chaos system is sensitive to weak signals and immune to noise, which make chaos have good prospects in information detection technique.
本文应用人工免疫算法的参数和结构双重可塑性来产生多模型控制策略控制律，由此提出了一种新的混沌控制方法。
A new control method was presented that the control laws of multi-model solution were generated by artificial immune algorithm to obtain double plasticity of parameter and structure.
基于混沌理论构建的信号检测系统具有敏感微弱周期信号和对噪声有强免疫力的特点，用于微弱信号检测领域优势明显。
Signal detection system based on chaos theory has the critical sensitivity to periodic signal and the immunity to the strong noise, which can be used in weak signal detection area.
为了提高人工免疫系统中抗体生成速度，基于免疫系统的混沌特征，提出了混沌否定选择算法。
To increase antibody generating speed in artificial immune system, a chaos negative selection algorithm was presented which is based on the chaotic character of immune system.
利用混沌振子的初值敏感性和对噪声的免疫力可以检测微弱信号。
The weak signal can be detected by chaotic oscillator owing to its property of sensitive dependence on initial conditions and of immunity from noise.
临界混沌状态的周期振子对噪声具有免疫力，而对微弱的正弦信号或相位编码信号比较敏感。
The periodic oscillators at critical state are immune to noise and have sensitive dependence on weak sine signals or phase-coded signals at the same time.
临界混沌状态的周期振子对噪声具有免疫力，而对微弱的正弦信号或相位编码信号比较敏感。
The periodic oscillators at critical state are immune to noise and have sensitive dependence on weak sine signals or phase-coded signals at the same time.
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