基于图像识别混沌的弱信号检测方法研究

Method Research of Weak Signal Detection Based on Image Recognition Chao

分析了基于Melnikov法和相轨迹观察法的弱周期信号检测方法,针对该方法存在检测精度低等不足,通过对混沌相平面的分析,结合图像处理相关知识,提出了基于图像识别法的弱周期信号检测方法;首先给出相关理论基础,然后阐述了所提方法的原理和设计方案,并给出了相应判别程序流程图;该方法具有算法简单、计算量小且可以实现自动识别的优点;仿真结果验证了理论分析的正确性和所提方案的有效性,为弱信号的检测提供了一条新的途径。

The weak cycle signal detection based on Melnikov method and the trajectory observation method is analyzed. In view of low precision inadequate existing in observation method, through the phase plane analysis, and image processing knowledge, a new weak cycle of signal detection method based on image recognition is presented. At first, the basis of relevant theories is given out, and then, the principles and methods of design expounded, and the corresponding discriminate program flowchart is given out. The method has advantages of simple algorithm, small amount of calculation and automatic identifications the simulation results show the correctness of the theoretical analysis and the effectiveness of the programme. The result has provided one highly effective new way for the weak signal detection.