Investigation Of Secure Communication And Waveform Recognition Based On Chaos

In the information age, people pay a close attention to information security and the capability of large data processing. For now, security communication based on chaos is already more mature, and information processing based on chaos gradually attracts the attention of experts. This thesis mainly focuses on the security communication and waveform recognition based on chaos. What I did in this paper as follows:(1)Simulated the bidirectional chaos laser security communication utilizing the mathematical model of chaos transmitter, chaos receiver and fiber channel according to the schematic diagram of chaos laser security communication. The forward and backward transmitted information rate is 1.25 Gb/s and transmission distance is 10km, the Q factor of the recovered information is 2.2 and 2.1, respectively. Designed the the experimental system for bidirectional chaotic optical secure communication and realized it. Two oppositely transmitted data streams with bit rates of 1.25Gb/s can be encrypted and decrypted successfully between two communication terminals over a 25-km single mode fiber channel. The Q-factor values of recovered data in forward and backward transmission are 2.1 and 2.0, respectively.(2)Studied the states of Mackey-Glass nonlinear equation with different values of intrinsic parameters p and 77. Simulated the waveform identification when the Mackey-Glass nonlinear system works in different states and selected the values of intrinsic parameters according to the simulated results. Simulated the waveform recognition between sin wave and square wave changing the number of virtual node from 50 to 100, the NRMSE is 0.22. After implementing the waveform recognition between sin wave and square wave, simulated the waveform recognition of sins with different phases and sins with different frequencies, got the results is 0.18 and 0.15, respectively.(3)Studied the states of opto-electronic oscillator nonlinear equation with different values of intrinsic parameters, simulated the waveform identification between sin wave and square wave when the feedback parameters was 1 and 4, and found that when the nonlinear system worked in the rectilinear oscillation states the results of the waveform recognition is much better. Simulated the waveform recognition between sin wave and square wave changing the number of virtual node from 50 to 100, the NRMSE is 0.15. After implementing the waveform recognition between sin wave and square wave, simulated the waveform recognition of sins with different phases and sins with different frequencies, got the results is 0.13 and 0.14, respectively.