Font Size: a A A

Research On Adaptive Polynomial Transform Chaos And Its Circuit Design

Posted on:2021-05-20Degree:MasterType:Thesis
Country:ChinaCandidate:R H ZhangFull Text:PDF
GTID:2438330602994972Subject:Circuits and Systems
Abstract/Summary:PDF Full Text Request
Chaotic signals are widely used in information encryption and chaotic masking due to their good Quasi-random property and wide power spectrum characteristics,but there are still some limitations in the application of chaotic signals.On one hand,the chaotic signal contains a lot of characteristic information of its chaotic system,so it can be attacked by phase space reconstruction.On the other hand,the chaos carrier has a rich power spectrum within its main frequency range,while there is no frequency component outside the main frequency,which severely limits the use of chaotic signals to conceal the information signal of higher frequency.To solve the above problems,a new method for transforming chaos-adaptive polynomial transformation is proposed.The basic polynomial function with good nonlinearity in a certain interval is obtained by polynomial fitting,then adjust the range of chaotic signal or the domain of the basic polynomial function to make them match each other,and transform the chaotic signal.The theoretical analysis and demonstration of the new method in resisting the attack of phase space reconstruction and broadening the scope of chaotic carrier frequency are carried out in detail,theoretical analysis and simulation results show that the new method is correct.In order to realize the method in hardware,an adaptive polynomial transform circuit is designed according to its principle.The results show that the adaptive polynomial transformation can make the chaotic signal resist chaos type recognition and chaos prediction attacks,and obviously expand the frequency distribution range of chaotic carrier,making it more suitable to cover the high frequency information signal.
Keywords/Search Tags:Phase space reconstruction, Chaos covers, Polynomial transformation, Spectrum analysis
PDF Full Text Request
Related items