Abstract
The adaptive approach of strongly non-linear fast-changing signals identification is discussed. The approach is devised by adaptive sampling based on chaotic mapping “in yourself” of a signal. Presented sampling way may be utilized online in the automatic control of chemical reactor (throughout identification of concentrations and temperature oscillations in real-time), in medicine (throughout identification of ECG and EEG signals in real-time), etc. In this paper, we presented it to identify the Weierstrass function and ECG signal.
Highlights
One of fundamental problems in signals analyses and transformation is their identification, most often by means of sampling
The determination of the boundary frequency is not always possible in practice, especially in the case of fast-changing signals. Under such circumstances sampling should be performed at uneven time intervals, for example: by adaptive sampling, in which the actual sampling moment depends on the previous sample value
The scope of this paper is the adaptive sampling approach that is much easier than the so far described approaches. It is based on uneven adaptive sampling with the use of the chaotic representation of the tested signal
Summary
One of fundamental problems in signals analyses and transformation is their identification, most often by means of sampling. The determination of the boundary frequency is not always possible in practice, especially in the case of fast-changing signals. Under such circumstances sampling should be performed at uneven time intervals, for example: by adaptive sampling, in which the actual sampling moment depends on the previous sample value. The scope of this paper is the adaptive sampling approach that is much easier than the so far described approaches. It is based on uneven adaptive sampling with the use of the chaotic representation of the tested signal. Notations: a, b – Weierstrass function parameters, E – information entropy, N – number of samples, observations horizon, p – probability, t – time, λ – Lyapunov’s exponent, w(t) – function generating nonlinear oscillations
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
