Recurrent neural networks and hidden Markov models have been the popular tools for sequence recognition problems such as automatic speech recognition. This work investigates the combination of recurrent neural networks and hidden Markov models into the hybrid architecture. This combination is feasible due to the similarity of the architectural dynamics of the two systems. Initial experiments we...

the main goal of the present study was to implement a hybrid pattern of cellular automata model and particle swarm optimization algorithm based on tm and etm+ imagery of landsat satellite from 1988 to 2010 for simulating the urban sprawling. in this study, an alternative model was implemented in two ways: the first method was based on two images (1988 and 2010) and the second one was based on t...

We introduce the framework of hybrid automata as a model and speci cation language for hybrid systems. Hybrid automata can be viewed as a generalization of timed automata, in which the behavior of variables is governed in each state by a set of di erential equations. We show that many of the examples considered in the workshop can be de ned by hybrid automata. While the reachability problem is ...

Discreteness and continuity are two opposite ways of describing the world. However, there are many situations, from engines to cells, in which an hybrid description, mixing both such ingredients, seems more adequate. In this presentation, we focus on stochastic hybrid systems. We present Piecewise Deterministic Markov Processes, and we provide a simpler description language, Transition-Driven S...

Model-based diagnosis and mode estimation capabilities excel at diagnosing systems whose symptoms are clearly distinguished from normal behavior. A strength of mode estimation, in particular, is its ability to track a system’s discrete dynamics as it moves between different behavioral modes. However, often failures bury their symptoms amongst the signal noise, until their effects become catastr...

In this paper, we study a model of quantum Markov chains that is a quantum analogue of Markov chains and is obtained by replacing probabilities in transition matrices with quantum operations. We show that this model is very suited to describe hybrid systems that consist of a quantum component and a classical one, although it has the same expressive power as another quantum Markov model proposed...

This paper describes the implementation of predicate abstraction techniques to automatically compute symbolic backward reachable sets of high dimensional piecewise affine hybrid automata, used to model Delta-Notch biological cell signaling networks. These automata are analyzed by creating an abstraction of the hybrid model, which is a finite state discrete transition system, and then performing...

The main goal of the present study was to implement a hybrid pattern of cellular automata model and particle swarm optimization algorithm based on TM and ETM+ imagery of landsat satellite from 1988 to 2010 for simulating the urban sprawling. In this study, an alternative model was implemented in two ways: the first method was based on two images (1988 and 2010) and the second one was based on t...