We have made observations of X-band radar sea clutter from the sea surface and sea-surface state in the Uraga Suido Traffic Route, which is used by ships entering and leaving Tokyo Bay, and the nearby Daini Kaiho Sea Fortress. We estimated the distributions of reflected amplitudes due to sea clutter using models that assume Weibull, Log-Weibull, Log-normal, and K-distributions. We then compared...

In this paper, estimation of the parameters of a certain family of two-parameter lifetime distributions based on progressively Type II right censored samples (including ordinary Type II right censoring) is studied. This family, of reverse hazard distributions, includes the Weibull, Gompertz and Lomax distributions. A new type of parameter estimation, named inverse estimation, is introduced for ...

in this paper, an extension of record models, well known as k-records, is considered. bayesian estimation as well as prediction based on k-records are presented when the underlying distribution is assumed to have a general form. the proposed procedure is applied to the exponential, weibull and pareto models in one parameter case. also, the two-parameter exponential distribution, when both param...

We address the problem of computing optimal policies for a finite-horizon newsvendor model with censored demand and perishable inventory. By combining an earlyperiod optimization based grid search with easily computable late-period bounds, we are able to handle a broad range of demand distributions and prior specifications. The grid-search is performed on a discretization of the demand-decision...

Many models involving combination of multiple Weibull distributions, modification of Weibull distribution or extension of its modified ones, etc. have been developed to model a given set of failure data. The application of these models to modeling a given data set can be based on plotting the data on Weibull probability paper (WPP). Of them, two or more models are appropriate to model one typic...

Annotation: In this papre We propose a neural network optimization algorithm for independent component analysis(ICA) which can separate mixtures of suband superGaussian source signals with self-adaptive nonlinearities. The ICA algorithem in the framework of natural Riemannian gradient, is derived using the parameterized Weibull density model. The nonlinear function in ICA algorithem is self-ada...

The contrast statistics of natural images can be adequately characterized by a two-parameter Weibull distribution. Here we show how distinct regimes of this Weibull distribution lead to various classes of visual content. These regimes can be determined using model selection techniques from information theory. We experimentally explore the occurrence of the content classes, as related to the glo...