Conditionalization, i.e., computation of a conditional probability distribution given a joint probability distribution of two or more random variables is an important operation in some probabilistic database models. While the computation of the conditional probability distribution is straightforward when the exact point probabilities are involved, it is often the case that such exact point prob...

Multiagent Partially Observable Markov Decision Processes are a popular model of multiagent systems with uncertainty. Since the computational cost for finding an optimal joint policy is prohibitive, a Joint Equilibrium-based Search for Policies with Nash Equilibrium (JESP-NE) is proposed that finds a locally optimal joint policy in which each policy is a best response to other policies; i.e., t...

In this paper we consider a system for coherent demodulation of M-ary FSK signals in the presence of Gaussian noise, impulse noise and variable signal amplitude. These annoyances can seriously degrade the performance of communication systems [1]-[3]. In the paper [4], the performance evaluation of several types of FSK and CPFSK receivers was investigated in detail using the modified moment’s me...

The modeling of joint probability distributions of correlated variables and the evaluation of reliability under incomplete probability information remain a challenge that has not been studied extensively. This article aims to investigate the effect of copulas for modeling dependence structures between variables on reliability under incomplete probability information. First, a copula-based metho...

To derive a Fokker-Planck equation, which deals with probabilities, we should start by stating the probabilistic notation and properties we will use. The probability that event A occurs is P [A]. Summing over all possible mutually exclusive events must yield a total of one: ∑ A P [A] = 1. If you include non-exlusive events, the probability sum can exceed one, so any sums will be performed over ...

A method for constructing confidence intervals on parameters of a continuous probability distribution is developed in this paper. The objective is to present a model for an uncertainty represented by parameters of a probability density function.  As an application, confidence intervals for the two parameters of the Weibull distribution along with their joint confidence interval are derived. The...

The aim of seismic inversion is mapping all of the subsurface structures from seismic data. Due to the band-limited nature of the seismic data, it is difficult to find a unique solution for seismic inversion. Deterministic methods of seismic inversion are based on try and error techniques and provide a smooth map of elastic properties, while stochastic methods produce high-resolution maps of el...

We present a method of automatically constructing a domain-specific Korean sentiment dictionary which can be used to classify the sentiment of online movie reviews. More than 1.18 million online movie reviews with movie ratings ranging between 1 to 4 and 7 to 10 were collected across fourteen different movie genres to calculate the joint probability of a given word and the sentiment of movie re...

Contents: Introduction. 1. The basic Gaussian Hidden Markov model. — 2. Some joint probability density functions of the process.-2.1. The joint pdf of (Y 1 , ..., Y T).-2.2. The joint pdf of the observations and one state of the Markov chain.-2.3. The joint pdf of the observations and two consecutive states of the Markov chain. — 3.