In order to improve the ability of reconstruction modeling and analysis of chaotic signal in wireless network, it is necessary to optimize modeling and phase space reconstruction of chaotic signal in wireless network. An artificial intelligence-based algorithm for chaotic signal reconstruction of wireless network is proposed, constructs the influence model of phase space reconstruction on chaotic signal of wireless network, uses fractional Fourier transform for dynamic compression of chaotic signal of wireless network, extracts the spectral characteristic of chaotic signal of wireless network, uses adaptive beamforming method for beam-focus analysis and spectral feature analysis of chaotic signal of wireless network in phase space reconstruction, and uses blind source separation method to realize optimal detection and recognition of chaotic signal of wireless network in phase space reconstruction. The simulation results show that this method can improve the feature extraction and detection ability of chaotic signal in the phase space reconstruction, and has strong anti-interference ability for signal detection and modeling.
Software And Hardware
• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL