INTERPOLATION MODELS FOR SIGNAL RESTORATION IN TECHNOLOGIES INTERNET OF THINGS

Abstract

An approach is proposed concerning signal processing in technologies Internet of Things (IoT). Microprocessor technologies are used in these technologies, when creating information and measuring systems. The use of such technologies involves the submission of raw data in digital form. Naturally, at the same time, the increased interest of the developers of the new equipment attracts tasks related to the presentation of analog signals in digital form and their subsequent processing. In addition to breaking information security of communication networks, IoT technology faces additional problems in computing and processing information in emergencies that require further reproduction of a useful signal. For practical implementation, all surrounding objects and devices must be equipped with miniature identifying and sensory (sensitive) devices. Then, in the presence of the necessary channels of communication with them, it is possible not only to track these objects and their parameters in space and time, but also to manage them. And also to monitor the safety of data and the continuous receipt of information on the appropriate sensors. When considering the problems of representing signals in digital form and their subsequent processing in the role of criteria characterizing the quality of the representation choose the criteria for storing the shape of the signal. The method is based on the construction of interpolation models for the restoration of signals based on trigonometric splines, which have several advantages over other classes of interpolation functions. These advantages include the immutability of algorithms for constructing trigonometric splines for different values of its parameter and representing them as the only expression throughout the signal recovery interval.

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  • EP ID EP480527
  • DOI -
  • Views 105
  • Downloads 0

How To Cite

(2018). INTERPOLATION MODELS FOR SIGNAL RESTORATION IN TECHNOLOGIES INTERNET OF THINGS. Телекомунікаційні та інформаційні технології, 103(3), -. https://europub.co.uk/articles/-A-480527