This paper describes a source modeling method for hidden Markov model (HMM) based speech synthesis for improved naturalness. A speech corpus is rst decomposed into the glottal sou...
Tuomo Raitio, Antti Suni, Hannu Pulakka, Martti Va...
We study a sequential variance reduction technique for Monte Carlo estimation of functionals in Markov Chains. The method is based on designing sequential control variates using s...
We study the problem of dynamic spectrum sensing and access in cognitive radio systems as a partially observed Markov decision process (POMDP). A group of cognitive users cooperati...
Jayakrishnan Unnikrishnan, Venugopal V. Veeravalli
Markov decision processes (MDPs) with discrete and continuous state and action components can be solved efficiently by hybrid approximate linear programming (HALP). The main idea ...
Abstract— In this paper we consider several problems involving control with limited actuation and sampling rates. Event-based control has emerged as an attractive approach for ad...