Results 211 to 220 of about 2,235,965 (245)

Recursive K-distribution parameter estimation

IEEE Transactions on Signal Processing, 2005
Recursive estimation of the parameter of the K-distribution is studied and tested. The probability density function (pdf) of the K-distribution is seen as a mixture pdf allowing the application of Titterington's recursive expectation-maximization (EM) technique.
Pei Jung Chung, William J. J. Roberts, Johann F. Böhme   +2 more
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Recursive estimation of K-distribution parameters

2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)., 2003
We address the problem of estimating parameters of K-distribution. A recursive procedure based on the recursive EM algorithm is derived to find the ML estimates. Recursive EM is a stochastic approximation procedure with a gain matrix derived from the augmented data. Under mild conditions estimates generated by such procedure are characterized by strong
Pei Jung Chung, William J. J. Roberts
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Radar detection in K-distributed clutter

IEE Proceedings - Radar, Sonar and Navigation, 1994
The paper compares two newly proposed detection schemes for targets in K-distributed clutter: the first implements generalised likelihood ratio test, and the second represents a discrete realisation of the classical Neymann-Pearson detector. Results indicate that the two optimisation strategies yield substantially equivalent performance, but the ...
CONTE E, LOPS M, RICCI, Giuseppe
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The Effect of K-Distributed Clutter on Trackability

IEEE Transactions on Signal Processing, 2016
In the field of target tracking, a tremendous amount of work has been done on designing and implementing algorithms. However, much less work has been performed on analyzing whether, for a given target in a given environment, tracking is possible at all. Our recent work developed a framework to answer just that.
Steven Schoenecker, Peter Willett 0001, Yaakov Bar-Shalom   +2 more
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INVERSE GAUSSIAN k-DISTRIBUTIONS

Journal of Quantitative Spectroscopy and Radiative Transfer, 1999
Abstract k-distributions corresponding to Malkmus’ narrow band model are inverse Gaussian distributions. Inverse Gaussian theory developments are therefore directly relevant to gas radiative transfer modeling. The present text illustrates some significant benefits that could be made from this observation: (i) k-distribution formulations are ...
J.L. DUFRESNE, R. FOURNIER, J.Y. GRANDPEIX   +2 more
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The Significance Of The Class Of K-Distributions

SPIE Proceedings, 1988
The statistical fluctuations developed by an optical wave, after passing through atmospheric turbulence, have a non-Gaussian nature. The detected optical intensity appears to have two separate time scales of fluctuations. This paper discusses a plausible physical model for the turbulence scattering of an optical wave that would give rise to a two-time ...
Phillips, Ronald L., Andrews, Larry C.
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K-distributed noise

Journal of Optics A: Pure and Applied Optics, 1999
A brief review of the history, properties and applications of K-distributed noise is presented. Statistical relationships and generalizations of the model are summarized, and processing techniques developed to extract signals embedded in this kind of noise are briefly discussed.
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Communication Generation for Cyclic(K) Distributions

1996
Communication resulting from references to arrays with general cyclic(k) distributions in data-parallel programs is not amenable to existing analyses developed for block and cyclic distributions. The methods for communication generation presented in this paper are based on exploiting the repetitive nature of array accesses.
Ken Kennedy, Nenad Nedeljkovic, Ajay Sethi   +2 more
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On low order moments of the homodyned-K distribution

Ultrasonics, 2005
Fractional low order moments have been reported as beneficial for sampling computations using the K distribution. However, it has been recently pointed out that this it not the case for the homodyned-K distribution for a tissue discrimination problem. In this paper we show that such an statement is not fully justified. To that end, we follow a standard
Marcos, Martín-Fernández, Carlos, Alberola-López   +1 more
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Simulating Correlated K-Distributed Clutter

2020 IEEE International Radar Conference (RADAR), 2020
A method of simulating the temporal and spatial correlation of k-distributed sea clutter has been developed. Long term correlation is simulated by interpolation and rotation of a correlation Gaussian surface which is then transformed a Gamma “texture” surface by a MNLT (Memoryless Nonlinear Transform).
Ellis Humphreys, Michael Antoniou, Chris Baker, William Stafford   +3 more
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