A sequential sampling algorithm that adapts to the uncertain sparsity in signal environment

A model of the generalized criterion for the maximum deviation of a signal (process) is proposed and investigated, which makes it possible to determine a constant time interval between adjacent samples from a signal (process). The criterion is based on the properties of convex power functions of the time modulus, depends on the order of the power function and the magnitude of the permissible error of the stepwise or linear approximation of the function from the samples. The criterion is intended for use in real‑time management systems, it allows to reasonably determine the time sampling interval. In the criterion, several maximum parameters of the signal are mathematically interrelated, which distinguishes it from known analogues. It is shown that for the calculation of the time interval of the signal, it is optimal to use more than three maximal values of its initial derivatives. The calculation technique is given and an example of practical application of the obtained results is given when constructing the data acquisition channel of the real‑time control system.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

hi@scite.ai

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

A sequential sampling algorithm that adapts to the uncertain sparsity in signal environment

Cited by 2 publications

References 11 publications

Adaptive Analog-to-Information Converter Design with Limited Random Sequence Modulation

Adaptive Analog-to-Information Converter Design with Limited Random Sequence Modulation

Model of Extreme Signal Behavior (Process) and Development of the Criteria of Most Deviation

Contact Info

Product

Resources

About