In knowledge discovery from time series the goal is to detect interesting patterns in the series that may help a human to better recognize the regularities in the observed variables and thereby improve the understanding of the system. Computer programs are very good in number crunching, but knowledge arises only in the head of a human. Ideally, knowledge discovery algorithms therefore use time ...

Variable Time-Fraction Collaborative Communications Patrick Tooher, Ph.D. Concordia University 2009 In order to improve the performance of the wireless channel, collaborative communications has recently been proposed. In such a scenario, a source wishing to transmit a signal to a destination can be aided by an otherwise idle transmitter (labeled a relay). Due to the half duplex constraint, the ...

This paper considers an extension of probability space based on interval random variables. In this approach, first, a notion of interval random variable is introduced. Then, based on a family of continuous distribution functions with interval parameters, a concept of probability space of an interval random variable is proposed. Then, the mean and variance of an interval random variable are intr...

in a structural time series regression model, binary variables have been used to quantify qualitative or categorical quantitative events such as politic and economic structural breaks, regions, age groups and etc. the use of the binary dummy variables is not reasonable because the effect of an event decreases (increases) gradually over time not at once. the simple and basic idea in this paper i...