This report explains the theory of Hidden Markov Models (HMMs). The emphasis is on the theory aspects in conjunction with the implementation issues that are encountered in a floating point processor. The main theory and implementation issues are based on the use of a Gaussian Mixture Model (GMM) as the state density in the HMM, and a Continuous Density Hidden Markov Model (CDHMM) is assumed. Su...

We present a computational model of blame attribution. Recently Mao and Gratch, following Attribution theory, created a computational model that assigned blame to an agent for a negative occurrence. Their model made categorical judgments, and could only assign blame to a single agent. Our model extends this work, using QP theory to provide a continuous model for the parameters involved in attri...

In the absolutely continuous case, order statistics, record values and several other models of ordered random variables can be viewed as special cases of generalized order statistics, which enables a unified treatment of their theory. This paper deals with discontinuous generalized order statistics, continuing on the recent work of Tran (2006). Specifically, we show that in general neither re...

the pupose of this paper is modeling of partial digest problem (pdp) as a mathematical programming problem. in this paper we present a new viewpoint of pdp. we formulate the pdp as a continuous optimization problem and develope a method to solve this problem. finally we constract a linear programming model for the problem with an additional constraint. this later model can be solved by the simp...

A constraint is a limitation or a restriction that poses a threat to the performance and efficiency of a system. This paper presented a tactical review approach to production constraints modeling. It discussed the theory of constraints (TOC) as a thinking process and continuous improvement strategy to curtail constraints in other to constantly increase the performance and efficiency of a system...