The slope stability is a very important problem in geotechnical engineering. This paper presents an approach for slope reliability analysis based on the maximum-entropy method. The key idea is to implement the maximum entropy principle in estimating the probability density function. The performance function is formulated by the Simplified Bishop’s method to estimate the slope failure probabilit...

The Kaplan-Yorke conjecture suggests a simple relationship between the fractal dimension of a system and its Lyapunov spectrum. This relationship has important consequences in the broad field of nonlinear dynamics where dimension and Lyapunov exponents are frequently used descriptors of system dynamics. We develop an experimental system with controllable dimension by making use of the Kaplan-Yo...

PIH64 FamIly PreFerences In tHe Volume Versus outcome Debate: ImPlIcatIons For tHe DelIVery oF comPlex PeDIatrIc care O’Leary G.1, Lockhart A.1, Mullenger R.2, Warren A.2, Hancock Friesen C.2, Levy A.2, Molinari M.2, O’Blenes S.2 1IWK Health Centre, Halifax, NS, Canada, 2Dalhousie University, Halifax, NS, Canada Objectives: A Relationship between volume and outcome for complex medical procedure...

ÐGibbsian fields or Markov random fields are widely used in Bayesian image analysis, but learning Gibbs models is computationally expensive. The computational complexity is pronounced by the recent minimax entropy (FRAME) models which use large neighborhoods and hundreds of parameters [22]. In this paper, we present a common framework for learning Gibbs models. We identify two key factors that ...

We consider a minimum-entropy criterion to tackle some statistical signal and image processing problems. We focus on semiparametric models, with the aim to estimate a vector of unknown parameters, say θ⋆, of a given model in the presence of errors of unknown density. The lack of information on these errors is such that it is difficult to obtain both asymptotically efficient and robust procedure...

The entropy rate quantifies the amount of uncertainty or disorder produced by any dynamical system. In a spiking neuron, this uncertainty translates into the amount of information potentially encoded and thus the subject of intense theoretical and experimental investigation. Estimating this quantity in observed, experimental data is difficult and requires a judicious selection of probabilistic ...

In this paper, new techniques that allow conditional entropy to estimate the 1 combinatorics of symbols are applied to animal communication studies to estimate the 2 communication’s repertoire size. By using the conditional entropy estimates at multiple 3 orders, the paper estimates the total repertoire sizes for animal communication across 4 bottlenose dolphins, humpback whales, and several sp...

market volatility remains one of the most important research fields in agricultural economics.interestingly, price transmission mechanism seems to be symmetric in sectors that are likely to be of high political power.this paper analyzes the price transmission effects from international markets to domestic markets for corn in iran. for this purpose, we estimate the elasticity of substitution bet...

This paper considers the problem of estimating the power consumption at logic and register transfer levels of design from an information theoretical point of view. In particular, it is demonstrated that the average switching activity in the circuit can be calculated using either entropy or informational energy averages. For control circuits and random logic, the output entropy (informational en...

Entropy and information are common measures of probabilistic models of data, frequently used for discrete and discretized but more rarely for continuous data. We employ finite mixture models, which handle continuous and discrete data simultaneously, to construct a probabilistic model whose entropy can be estimated. Analytic estimates of entropy are intractable for some models, so an approximate...