Hidden Markov Model is a popular statisical method that is used in continious and discrete speech recognition. The probability density function of observation vectors in each state is estimated with discrete density or continious density modeling. The performance (in correct word recognition rate) of continious density is higher than discrete density HMM, but its computation complexity is very ...

We consider a network of controllers that observe and control a plant whose dynamics is determined by a finite set of continuous variables. At any given time a variable evolves at a constant rate. However, a controller can switch the rates of a designated subset of the continuous variables. These mode changes are determined by the current values of a designated subset of the variables that the ...

This thesis proposal defines the problem of recovery in distributed discrete real-time simulations with external actions; real-time simulations with simulation actions in the real world. A problem that these simulations encounter is that they cannot rely on rollback-based recovery (use of checkpoints) for two reasons. First, some actions in the ”real world” cannot be undone, and second, the tim...

This paper dealswith the distributed discrete-time coordinated tracking problem formulti-agent systems with Markovian switching topologies. In the multi-agent team, only some of the agents can obtain the leader’s state directly. The leader’s state considered is time varying. We present necessary and sufficient conditions for boundedness of the tracking error system and show the ultimate bound o...

this paper offers an approach that could be useful for diverse types of layout problems or even area allocation problems. by this approach there is no need to large number of discrete variables and only by few continues variables large-scale layout problems could be solved in polynomial time. this is resulted from dividing area into discrete and continuous dimensions. also defining decision var...

this paper is concerned with the problem of delay dependent H∞ control of discrete-time uncertain recurrent neural networks with time varying-delays. The neural network is subject to parameter uncertainty, and time-varying delay. For the robust H∞ stabilization problem, a state feedback controller is designed to ensure global robust stability of the closed-loop system about its equilibrium poin...

We decompose time-varying beta for stock into beta for continuous systematic risk and beta for discontinuous systematic risk. Brownian motion is assumed as nature of price movements in our modeling. Our empirical research is based on high-frequency data for stocks from Tehran Stock Exchange. Our market portfolio experiences 136 days out of 243 trading days with jumps which is a considerable rat...