Reconstructed Quantized Coefficients Modeled with Generalized Gaussian Distribution with Exponent 1/3
نویسندگان
چکیده
منابع مشابه
promotion time cure model with generalized poisson-inverse gaussian distribution
background & aim: in the survival data with long-term survivors the event has not occurred for all the patients despite long-term follow-up, so the survival time for a certain percent is censored at the end of the study. mixture cure model was introduced by boag, 1949 for reaching a more efficient analysis of this set of data. because of some disadvantages of this model non-mixtur...
متن کاملUnimodality of generalized Gaussian coefficients
A combinatorial proof of the unimodality of the generalized q-Gaussian coefficients [ N λ ] q based on the explicit formula for Kostka-Foulkes polynomials is given. 1. Let us mention that the proof of the unimodality of the generalized Gaussian coefficients based on theoretic-representation considerations was given by E.B. Dynkin [1] (see also [2], [10], [11]). Recently K.O’Hara [6] gave a cons...
متن کاملStochastic Information Gradient Algorithm with Generalized Gaussian Distribution Model
This paper presents a parameterized version of the stochastic information gradient (SIG) algorithm, in which the error distribution is modeled by generalized Gaussian density (GGD), with location, shape, and dispersion parameters. Compared with the kernel-based SIG (SIGKernel) algorithm, the GGD-based SIG (SIG-GGD) algorithm does not involve kernel width selection. If the error is zero-mean, th...
متن کاملQuantized Chebyshev polynomials and cluster characters with coefficients
We introduce quantized Chebyshev polynomials as deformations of generalized Chebyshev polynomials previously introduced by the author in the context of acyclic coefficient-free cluster algebras. We prove that these quantized polynomials arise in cluster algebras with principal coefficients associated to acyclic quivers of infinite representation types and equioriented Dynkin quivers of type A. ...
متن کاملStructured Preex Codes for Quantized Low-shape-parameter Generalized Gaussian Sources Structured Preex Codes for Quantized Low-shape-parameter Generalized Gaussian Sources
The highly peaked, wide-tailed pdfs that are encountered in many image coding algorithms are often modeled using the family of generalized Gaussian (GG) pdfs. We study entropy coding of quantized GG sources using preex codes that are highly structured, and which therefore involve low computational complexity to utilize. We provide bounds for the redundancy associated with applying these codes t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Image Processing & Communications
سال: 2016
ISSN: 2300-8709
DOI: 10.1515/ipc-2016-0019