Wszystkie pola: non-Gaussian noise - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Modeling of joint signal detection and parameter estimation on the background of non-Gaussian noise
Autorzy:: Palahin, V.
Filipov, V.
Leleko, S.
Ivchenko, O.
Palahina, O.
Powiązania:: https://bibliotekanauki.pl/articles/122532.pdf
Data publikacji:: 2015
Wydawca:: Politechnika Częstochowska. Wydawnictwo Politechniki Częstochowskiej
Tematy:: non-Gaussian noise
moment and cumulant representation of random variables
truncated stochastic polynom
polynomial solving rules
Opis:: The paper presents the results and describes the process of modeling of a system of joint signal detection and parameter estimation on the background of a non-Gaussian noise based on moment and cumulant description of random variables, polynomials of Kunchenko and moment quality criterion type of Neyman-Pearson.
Źródło:: Journal of Applied Mathematics and Computational Mechanics; 2015, 14, 3; 87-94
2299-9965
Pojawia się w:: Journal of Applied Mathematics and Computational Mechanics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Minimum dispersion coefficient criteria based positioning algorithm for BDS
Autorzy:: Wang, L.
Li, L.
Powiązania:: https://bibliotekanauki.pl/articles/141700.pdf
Data publikacji:: 2018
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: alpha-stable distribution
BeiDou satellites
Kalman filter
minimum dispersion coefficient criteria
non-Gaussian noise
positioning algorithm
Opis:: The BeiDou navigation satellite system (BDS) is one of the four global navigation satellite systems. More attention has been paid to the positioning algorithm of the BDS. Based on the study on the Kalman filter (KF) algorithm, this paper proposed a novel algorithm for the BDS, named as the minimum dispersion coefficient criteria Kalman filter (MDCCKF) positioning algorithm. The MDCCKF algorithm adopts minimum dispersion coefficient criteria (MDCC) to remove the influence of noise with an alpha-stable distribution (ASD) model which can describe non-Gaussian noise effectively, especially for the pulse noise in positioning. By minimizing the dispersion coefficient of the positioning error, the MDCCKF assures positioning accuracy under both Gaussian and non-Gaussian environment. Compared with the original KF algorithm, it is shown that the MDCCKF algorithm has higher positioning accuracy and robustness. The MDCCKF algorithm provides insightful results for potential future research.
Źródło:: Archives of Electrical Engineering; 2018, 67, 4; 739-753
1427-4221
2300-2506
Pojawia się w:: Archives of Electrical Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Stochastic multivariable self-tuning tracker for non-Gaussian systems
Autorzy:: Filipovic, V.
Powiązania:: https://bibliotekanauki.pl/articles/908532.pdf
Data publikacji:: 2005
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: model ARMAX
statystyka odpornościowa
stabilność globalna
ARMAX model
self-tuning tracker
non-Gaussian noise
robust statistics
global stability
optimality
Opis:: This paper considers the properties of a minimum variance self-tuning tracker for MIMO systems described by ARMAX models. It is assumed that the stochastic noise has a non-Gaussian distribution. Such an assumption introduces into a recursive algorithm a nonlinear transformation of the prediction error. The system under consideration is minimum phase with different dimensions for input and output vectors. In the paper the concept of Kronecker’s product is used, which allows us to represent unknown parameters in the form of vectors. For parameter estimation a stochastic approximation algorithm is employed. Using the concept of the stochastic Lyapunov function, global stability and optimality of the feedback system are established.
Źródło:: International Journal of Applied Mathematics and Computer Science; 2005, 15, 3; 351-357
1641-876X
2083-8492
Pojawia się w:: International Journal of Applied Mathematics and Computer Science
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Performance of Turbo Codes with SOVA Algorithm in DSSS over Channels with non-white Additive Gaussian Noise
Autorzy:: Bykowski, Marek.
Powiązania:: Biuletyn Wojskowego Instytutu Łączności 2006, s. 45-49
Data publikacji:: 2006
Tematy:: Łączność wojskowa
Opis:: Rys.; Bibliogr.; Abstr.
Dostawca treści:: Bibliografia CBW

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Skocz do pozycji: 5.

Tytuł:: An Adaptive Richardson-Lucy Algorithm for Medical Image Restoration
Autorzy:: Yaqoub, Qunoot A.
Al-Ani, Ayad A.
Powiązania:: https://bibliotekanauki.pl/articles/2200960.pdf
Data publikacji:: 2023
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: constraint least square filter
Gaussian blurring function
Gaussian noise function
inverse filter
non-blind deconvolution
point spread function
Richardson-Lucy algorithm
Wiener filter
Opis:: Image restoration is the process of estimating the original image content from a degraded picture. In this paper, the Richardson-Lucy iterative algorithm was developed to improve the quality of degraded medical images. It has been assumed that medical images are exposed to two types of degradation. The first type is the blur function in the Gaussian form with different widths, i.e. σ = 1 , 2, and 3. The second type of degradation was assumed to be of the independent white Gaussian noise type with different signal-to-noise ratio values: SNR = 10, 50 , and 100. The results obtained from the adaptive filter are compared, quantitatively, with different conventional filters: inverse, Wiener, and constraint least square, by applying different measures, such as: power signal to noise ratio (PSNR), structural similarity index (SSID), and root mean square error (RMSE). The comparison showed that the adaptive recovery filter achieves better results.
Źródło:: Journal of Telecommunications and Information Technology; 2023, 1; 66--77
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

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