Adaptive Detection of Normal Mixture Signals with Pre-Estimated Gaussian Mixture Noise
Autor: | Andrey Gorshenin |
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Rok vydání: | 2019 |
Předmět: |
Distribution (number theory)
Noise (signal processing) Homogeneity (statistics) 02 engineering and technology 01 natural sciences Computer Graphics and Computer-Aided Design Signal Gaussian mixture noise 010309 optics 0103 physical sciences Pattern recognition (psychology) 0202 electrical engineering electronic engineering information engineering Probability distribution 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Algorithm Change detection Mathematics |
Zdroj: | Pattern Recognition and Image Analysis. 29:377-383 |
ISSN: | 1555-6212 1054-6618 |
Popis: | The paper describes the adaptive method of estimating the parameters of the distribution of the useful signal under the assumption that the noise distribution can be pre-estimated. It is based on the method of moving separation of the finite normal mixtures and implemented for the estimating both signal-noise and signal distribution parameters. We assume that the probability distribution of the signal, signal with noise and “pure” noise can be presented in form of finite normal mixtures. Also, a method for change point detection based on testing the homogeneity hypothesis using the Kolmogorov criterion is proposed. |
Databáze: | OpenAIRE |
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