We consider 3D shape description as a probability modeling problem. The local surface properties are first measured via various features, and then the probability density function (pdf) of the multidimensional feature vector becomes the shape descriptor. Our prior work has shown that, for 3D object retrieval, pdf-based schemes can provide descriptors that are computationally efficient and perfo...

A direct numerical simulation ~DNS! database is used to develop a model of subgrid-scale temperature fluctuations for use in large-eddy simulations of turbulent, reacting hypersonic flows. The proposed model uses a probability density representation of the temperature fluctuations. The DNS database reveals a physically consistent relation between the resolved-scale flow conditions that may be u...

Methods for calculating bit error rate (BER) using probability density function (PDF) of impairments (ISI, crosstalk, jitter etc.) have been studied and presented in the past. These approaches calculate PDF of the signal & impairments at the decision point based on linear system analysis and deduce the BER from tail probability. A typical high speed system also has significant non linearity in ...

A new distance measure between probability density functions (pdfs) is introduced, which we refer to as the Laplacian pdf distance. The Laplacian pdf distance exhibits a remarkable connection to Mercer kernel based learning theory via the Parzen window technique for density estimation. In a kernel feature space defined by the eigenspectrum of the Laplacian data matrix, this pdf distance is show...

-In this paper, the critical clearing time, tcc in power system transient stability analysis is modeled as a random variable due to the randomness nature of power system load. A linear approximation approach that mainly involves the sensitivity calculation of the derivative of tcc to system load is developed to obtain the probability density function (pdf) of tcc based on the pdf of system load...

In this paper we investigate the performance of probability estimation methods for reliability analysis. The probability estimation methods typically construct the probability density function (PDF) of a system response using estimated statistical moments, and then perform reliability analysis based on the approximate PDF. In recent years, a number of probability estimation methods have been pr...

An expression for probability density function ( pdf ) of a K – out – of N : G system is proposed. A simple, fast and memory efficient recursive algorithm computes the pdf of K – out – of N : G system with unequal component failure probabilities. The special cases of constant failure rate, Weibull failure time distributions are provided for illustrating the results.

We present an analysis for evaluating the probability density function (pdf) of the noise at the output of the frequency demodulator. It is shown that the noise is non-Gaussian and that for low to medium signal-to-noise power ratios, its pdf differs very significantly from the Gaussian pdf commonly assumed in simplified analysis. These results are very important for analyzing the performance of...

In this paper, we extend our previously proposed Viterbi Bayesian predictive classification (VBPC) algorithm to accommodate a new class of prior probability density function (pdf) for continuous density hidden Markov model (CDHMM) based robust speech recognition. The initial prior pdf of CDHMM is assumed to be a finite mixture of natural conjugate prior pdf’s of its complete-data density. With ...