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Chaos-based signal processing

机译:基于混沌的信号处理

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Nonlinear Systems exhibiting chaotic behavior can be considered as a source of a great variety of signals. Given a time series measured from a known or an unknown dynamical system we address a series of problems, such as section-wise approximation of the measured signal by pieces of trajectories from a chosen nonlinear dynamical system (model); signal restoration when the measured signal has been corrupted e.g. by quantization; signal coding and compression. The key to attack these problems is estimation of the initial conditions for a dynamical system which is used as the generator of approximating waveforms.
机译:表现出混沌行为的非线性系统可以被认为是各种信号的源。考虑到从已知的或未知动力系统测量的时间序列,我们解决了一系列问题,例如由所选非线性动力系统(型号)的轨迹由轨迹的曲线剖面近似的剖视近似;当测量信号已损坏时,信号恢复。量化;信号编码和压缩。攻击这些问题的关键是估计动态系统的初始条件,其用作近似波形的发电机。

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