We propose a statistical method for modeling the non-Poisson variability of spike trains observed in a wide range of brain regions. Central to our approach is the assumption that the variance and the mean of interspike intervals are related by a power function characterized by two parameters: the scale factor and exponent. It is shown that this single assumption allows the variability of spike ...

the effect of drought indices on hydrostatic variations and qualitative parameters of the zahedan plain's aquifer was investigated. for this purpose, 12-year statistics from observational and piezometry wells in the plain, the drought index of percentage normal )pn), standardized precipitation index )spi(, and 30-year precipitation statistics of zahedan station were used. results revealed ...

We report on a new approach to a global CKM matrix analysis taking into account most recent experimental and theoretical results. The statistical framework (Rfit) developed in this paper advocates frequentist statistics. Other approaches, such as Bayesian statistics or the 95% CL scan method are also discussed. We emphasize the distinction of a model testing and a model dependent, metrological ...

The level set approach is a powerful tool for segmenting images. This paper proposes a method for segmenting brain tumor images from MR images. A new signed pressure function (SPF) that can efficiently stop the contours at weak or blurred edges is introduced. The local statistics of the different objects present in the MR images were calculated. Using local statistics, the tumor objects were id...

How does a neuron vary its mean output firing rate if the input changes from random to oscillatory coherent but noisy activity? What are the critical parameters of the neuronal dynamics and input statistics? To answer these questions, we investigate the coincidence-detection properties of an integrate-and-fire neuron. We derive an expression indicating how coincidence detection depends on neuro...

We present a method for labeling the land-cover in an aerial image using image texture statistics and a trained neural network to interpret the texture data. The introduction includes a brief discussion of land-cover mapping and the types of land-cover classes we would like to identify. There is a section describing the texture statistics used and the Gray Level Cooccurrence Matrix (GLCM) for c...

The paper addresses the problem of line-of-sight (LOS) vs. non-line-of-sight (NLOS) propagation link identification in ultrawideband (UWB) wireless networks, which is necessary for improving the accuracy of radiolocation and positioning applications. A LOS/NLOS likelihood hypothesis testing approach is applied based on exploiting distinctive statistical features of the channel impulse response ...

In this paper we emphasize the importance of the Sloan Digital Sky Survey (SDSS) QSO clustering statistics as a unique probe of the Universe. Because the complete SDSS QSO sample covers a quarter of the observable universe, cosmological parameters estimated from the clustering statistics have an implication as a test of the cosmological principle, by comparing with those from local galaxies and...

The efficiency and safety of a new treatment is occasionally evaluated using Poisson distributed count data as the criteria in clinical studies. In such scenarios, non-inferiority tests using Poisson distributed count data are often employed and evaluated in frequentist frameworks. However, in our previous work, we proposed and presented an index that demonstrated that the Poisson parameter obt...