We can view a Bayesian network as a compact representation of a joint probability distribution (the computational view). We can also view it as a graphical representation of a set of conditional independence statements (the conditional independence view). As it turns out, the two views are equivalent. (For more details please refer to [1] and [2]). In this class, we will focus exclusively on th...

We present a new approach to the source separation problem for multiple speech signals. Using the extra visual information of the speaker’s face, the method aims to extract an acoustic speech signal from other acoustic signals by exploiting its coherence with the speaker’s lip movements. We define a statistical model of the joint probability of visual and spectral audio input for quantifying th...

We derive general, unified expressions for the probability density function, cumulative distribution function, and mean SNR of generalized selection combining operating over multibranch, arbitrary, correlated, non-identical fading channels. The expressions are written in terms of the joint probability density function of the branch signals and allow for the equalgain and maximal-ratio methods i...

Multispectral digital imagery acquired from Soda Butte and Cache Creeks, Montana and Wyoming was used in conjunction with field data to classify and map hydrogeomorphic stream units on four stream reaches. The morphologic units that were field mapped were eddy drop zones, glides, low gradient riffles, high gradient riffles, lateral scour pools, attached bars, detached bars, and large woody debr...

To the Editor: We read with concern the recent paper by Fallest-Strobl, Olafsdottir, Wiebe, and Westgard (1) in which the authors state, “. . . the NCEP recommendations fail to adequately consider the quality control requirements necessary to detect medically important systematic errors.” We also note that Westgard, Petersen, and Wiebe (2) published a similar paper in 1991 questioning the adequ...

It is well known that the joint probability density of the eigenvalues of Gaussian ensembles of random matrices may be interpreted as a Coulomb gas. We review these classical results for hermitian and complex random matrices, with special attention devoted to electrostatic analogies. We also discuss the joint probability density of the zeros of polynomials whose coefficients are complex Gaussia...

We present a new approach to the source separation problem for multiple speech signals. Using the extra visual information of the face speaker, the method aims to extract an acoustic speech signal from other acoustic signals by exploiting its coherence with the speaker’s lip movements. We define a statistical model of the joint probability of visual and spectral audio input for quantifying the ...

This paper presents a new spectral modeling and conversion method for voice conversion. In contrast to the conventional Gaussian mixture model (GMM) based methods, we use restricted Boltzmann machines (RBMs) as probability density models to model the joint distributions of source and target spectral features. The Gaussian distribution in each mixture of GMM is replaced by an RBM, which can bett...

In this paper, we use a novel duration model to study joint retirement in married couples using the Health and Retirement Study. Whereas conventionally used models cannot account for joint retirement, our model admits joint retirement with positive probability and nests the traditional proportional hazards model. In contrast to other statistical models for simultaneous durations, it is based on...

In this paper we will introduce a new index of interactivity between marginal possibility distributions A and B of a joint possibility distribution C. The starting point of our approach is to equip each γ-level set of C with a uniform probability distribution, then the probabilistic correlation coefficient between its marginal probability distributions is interpreted as an index of interactivit...