Results 11  20
of
11,664
Generalized Krätzel integral and associated statistical densities
 International Journal of Mathematical Analysis
, 2012
"... Abstract Krätzel integral is one of the integrals appearing in applied analysis, engineering, physics and other areas. There is an integral transform associated with this basic integral, known as Krätzel transform. This transform is given generalization in the form of Ptransform. This integral is ..."
Abstract

Cited by 1 (1 self)
 Add to MetaCart
is also connected with various quantities in different disciplines such as inverse Gaussian density in statistical analysis, Bessel functions, Mellin convolution etc. Various generalizations to the basic Krätzel integral, and the associated statistical densities, are given in the present paper. At each
TITLE: STATISTICAL DENSITY AND AMPLITUDE TAPERED ARRAYS
, 1988
"... Statistical density and amplitude tapering are combined to improve the radiation characteristics of thinned, density tapered arrays by allowing changes in both element density and amplitude weight to better approximate the model amplitude distribution. Statistical density tapering (which uses only u ..."
Abstract
 Add to MetaCart
Statistical density and amplitude tapering are combined to improve the radiation characteristics of thinned, density tapered arrays by allowing changes in both element density and amplitude weight to better approximate the model amplitude distribution. Statistical density tapering (which uses only
The minimum description length principle in coding and modeling
 IEEE TRANS. INFORM. THEORY
, 1998
"... We review the principles of Minimum Description Length and Stochastic Complexity as used in data compression and statistical modeling. Stochastic complexity is formulated as the solution to optimum universal coding problems extending Shannon’s basic source coding theorem. The normalized maximized ..."
Abstract

Cited by 394 (18 self)
 Add to MetaCart
We review the principles of Minimum Description Length and Stochastic Complexity as used in data compression and statistical modeling. Stochastic complexity is formulated as the solution to optimum universal coding problems extending Shannon’s basic source coding theorem. The normalized maximized
The beta reputation system
 In Proceedings of the 15th Bled Conference on Electronic Commerce
, 2002
"... Reputation systems can be used to foster good behaviour and to encourage adherence to contracts in ecommerce. Several reputation systems have been deployed in practical applications or proposed in the literature. This paper describes a new system called the beta reputation system which is based on ..."
Abstract

Cited by 364 (18 self)
 Add to MetaCart
on using beta probability density functions to combine feedback and derive reputation ratings. The advantage of the beta reputation system is flexibility and simplicity as well as its foundation on the theory of statistics. 1
Noise power spectral density estimation based on optimal smoothing and minimum statistics
 IEEE TRANS. SPEECH AND AUDIO PROCESSING
, 2001
"... We describe a method to estimate the power spectral density of nonstationary noise when a noisy speech signal is given. The method can be combined with any speech enhancement algorithm which requires a noise power spectral density estimate. In contrast to other methods, our approach does not use a ..."
Abstract

Cited by 276 (7 self)
 Add to MetaCart
smoothing of the power spectral density of the noisy speech signal. Based on the optimally smoothed power spectral density estimate and the analysis of the statistics of spectral minima an unbiased noise estimator is developed. The estimator is well suited for real time implementations. Furthermore
Unsupervised learning of models for recognition
 In ECCV
, 2000
"... Abstract. We present a method to learn object class models from unlabeled and unsegmented cluttered scenes for the purpose of visual object recognition. We focus on a particular type of model where objects are represented as flexible constellations of rigid parts (features). The variability within a ..."
Abstract

Cited by 356 (30 self)
 Add to MetaCart
a class is represented by a joint probability density function (pdf) on the shape of the constellation and the output of part detectors. In a first stage, the method automatically identifies distinctive parts in the training set by applying a clustering algorithm to patterns selected by an interest
Observation of BoseEinstein condensation in a dilute atomic vapor
 Science
, 1995
"... A BoseEinstein condensate was produced in a vapor of rubidium87 atoms that was confined by magnetic fields and evaporatively cooled. The condensate fraction first appeared near a temperature of 170 nanokelvin and a number density of 2.5 x 1012 per cubic centimeter and could be preserved for more t ..."
Abstract

Cited by 354 (7 self)
 Add to MetaCart
A BoseEinstein condensate was produced in a vapor of rubidium87 atoms that was confined by magnetic fields and evaporatively cooled. The condensate fraction first appeared near a temperature of 170 nanokelvin and a number density of 2.5 x 1012 per cubic centimeter and could be preserved for more
Background and Foreground Modeling Using Nonparametric Kernel Density Estimation for Visual Surveillance
 PROCEEDINGS OF THE IEEE
, 2002
"... ... This paper focuses on two issues related to this problem. First, we construct a statistical representation of the scene background that supports sensitive detection of moving objects in the scene, but is robust to clutter arising out of natural scene variations. Second, we build statistical repr ..."
Abstract

Cited by 294 (8 self)
 Add to MetaCart
utilize general nonparametric kernel density estimation techniques for building these statistical representations of the background and the foreground. These techniques estimate the pdf directly from the data without any assumptions about the underlying distributions. Example results from applications
Minimum complexity density estimation
 IEEE TRANS. INF. THEORY
, 1991
"... The minimum complexity or minimum descriptionlength criterion developed by Kolmogorov, Rissanen, Wallace, So&in, and others leads to consistent probability density estimators. These density estimators are defined to achieve the best compromise between likelihood and simplicity. A related issue ..."
Abstract

Cited by 247 (8 self)
 Add to MetaCart
is the compromise between accuracy of approximations and complexity relative to the sample size. An index of resolvability is studied which is shown to bound the statistical accuracy of the density estimators, as well as the informationtheoretic redundancy.
On the Minimum Node Degree and Connectivity of a Wireless Multihop Network
 ACM MobiHoc
, 2002
"... This paper investigates two fundamental characteristics of a wireless multihop network: its minimum node degree and its k–connectivity. Both topology attributes depend on the spatial distribution of the nodes and their transmission range. Using typical modeling assumptions — a random uniform distri ..."
Abstract

Cited by 318 (4 self)
 Add to MetaCart
distribution of the nodes and a simple link model — we derive an analytical expression that enables the determination of the required range r0 that creates, for a given node density ρ, an almost surely k–connected network. Equivalently, if the maximum r0 of the nodes is given, we can find out how many nodes
Results 11  20
of
11,664