Machine learning of radial basis function neural network based on Kalman filter: Introduction
| Autor: | Najdan Vukovic, Zoran Miljkovic |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
machine learning
Computer Science::Systems and Control lcsh:TA1-2040 021105 building & construction 0211 other engineering and technologies ComputerApplications_COMPUTERSINOTHERSYSTEMS 02 engineering and technology Kalman filter 010501 environmental sciences lcsh:Engineering (General). Civil engineering (General) 01 natural sciences artificial neural network 0105 earth and related environmental sciences |
| Zdroj: | Tehnika, Vol 69, Iss 4, Pp 613-620 (2014) Tehnika (2014) 69(4):613-620 |
| ISSN: | 2560-3086 0040-2176 |
| Popis: | This paper analyzes machine learning of radial basis function neural network based on Kalman filtering. Three algorithms are derived: linearized Kalman filter, linearized information filter and unscented Kalman filter. We emphasize basic properties of these estimation algorithms, demonstrate how their advantages can be used for optimization of network parameters, derive mathematical models and show how they can be applied to model problems in engineering practice. |
| Databáze: | OpenAIRE |
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