Optimization of Machine Learning Parameters for Spectrum Survey Analysis

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F14%3APU110396" target="_blank" >RIV/00216305:26220/14:PU110396 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Optimization of Machine Learning Parameters for Spectrum Survey Analysis
Original language description
This paper shows preliminary results of the optimization of machine learning parameters for cognitive radio application by brutal force calculations. We were analyzing frequency occupancy data of the huge measurement campaign of the spectrum background. For these date there are two possible states. Firstly, limited frequency band is occupied (detected signal level is above the threshold) by the other frequency signal | there will be an interference for our system for this frequency band. Secondly, the frequency band is free of any other wireless radiation. These true/false data are analyzed in a context of the cognitive radio by the reinforcement learning and simple learning. Each channel received a score from the learning algorithm given by weighting function. The quality of the output scores is discussed in this paper according to the learning algorithm parameters and optional learning time.
Czech name
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Czech description
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Project
<a href="/en/project/ED2.1.00%2F03.0072" target="_blank" >ED2.1.00/03.0072: Centre of sensor, information and communication systems</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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