The processing of signals from sensors to observe objects in various physical fields
| Autor: | Vladimir I. Lutin, N. Akamsina, Vladimir E. Mager, Elena N. Desyatirikova, Oksana Kuripta |
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| Rok vydání: | 2018 |
| Předmět: |
Signal processing
Heuristic (computer science) business.industry Computer science Comparison results 020206 networking & telecommunications Pattern recognition 02 engineering and technology Joint observation Bayesian risk Quality (physics) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence Image sensor business Sufficient statistic |
| Zdroj: | 2018 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus). |
| DOI: | 10.1109/eiconrus.2018.8317285 |
| Popis: | Based on the theory of distinguishing statistical hypotheses, an algorithm for detecting objects based on the results of joint observation in several physical fields was synthesized. The quality of the work of the synthesized algorithm is analyzed and comparison results with heuristic algorithms are shown, which show the advantage of complex processing of signals from image sensors. The algorithm was developed within the framework of the theory of distinguishing statistical hypotheses. The efficiency of complex signal processing by simulation is estimated. It is established that an increase in observation media leads to an improvement in the quality of the discrepancy between hypotheses. |
| Databáze: | OpenAIRE |
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