Abstract. This work focuses on the synthesis of finite-state machines (FSMs) by observing its input/output behaviors. Evolutionary approaches that have been proposed to solve this problem do not include strategies to escape from local optima, a typical problem found in simple evolutionary algorithms, particularly in the evolution of sequential machines. Simulations show that the proposed approach improves significantly the state space search.
Finite State Machine (FSM) based state identification problem is widely used for analysis of discret...
The authors describe a state assignment algorithm for FSMs which produces an assignment of non-neces...
Genetic Algorithms (GAS) are stochastic, non-derivative optimization method. They use popula-tions o...
A significant part of digital circuits is constituted by sequen-tial synchronous circuits behaviour ...
We give an algorithm that derives a finite state machine (FSM) from a given abstract state machine (...
This paper presents a finite state machine (FSM) re-engineering method that enhances the FSM synthes...
Finite State Machine (FSM) is the backbone of an important class of applications in many domains. It...
Computations are developed for the synthesis of a finite state machine (FSM) embedded in a known FSM...
Abstract--State space traversal algorithms for Finite State Machine (FSM) models of synchronous sequ...
A technique for the automated synthesis of FSMs (finite state machines) from sets of interworkings (...
In this paper a search-based method for constructing finite-state machines (FSMs) with continuous (r...
optimization method. They use populations of acceptable solutions (genes) of the given problem, whic...
Finite-state models, such as finite-state machines (FSMs), aid software engineering in many ways. Th...
State space exploration of finite state machines is used to prove properties about sequential behavi...
Finite State Machines (FSMs) are widely used for analysis and synthesis of hardware designs. In part...
Finite State Machine (FSM) based state identification problem is widely used for analysis of discret...
The authors describe a state assignment algorithm for FSMs which produces an assignment of non-neces...
Genetic Algorithms (GAS) are stochastic, non-derivative optimization method. They use popula-tions o...
A significant part of digital circuits is constituted by sequen-tial synchronous circuits behaviour ...
We give an algorithm that derives a finite state machine (FSM) from a given abstract state machine (...
This paper presents a finite state machine (FSM) re-engineering method that enhances the FSM synthes...
Finite State Machine (FSM) is the backbone of an important class of applications in many domains. It...
Computations are developed for the synthesis of a finite state machine (FSM) embedded in a known FSM...
Abstract--State space traversal algorithms for Finite State Machine (FSM) models of synchronous sequ...
A technique for the automated synthesis of FSMs (finite state machines) from sets of interworkings (...
In this paper a search-based method for constructing finite-state machines (FSMs) with continuous (r...
optimization method. They use populations of acceptable solutions (genes) of the given problem, whic...
Finite-state models, such as finite-state machines (FSMs), aid software engineering in many ways. Th...
State space exploration of finite state machines is used to prove properties about sequential behavi...
Finite State Machines (FSMs) are widely used for analysis and synthesis of hardware designs. In part...
Finite State Machine (FSM) based state identification problem is widely used for analysis of discret...
The authors describe a state assignment algorithm for FSMs which produces an assignment of non-neces...
Genetic Algorithms (GAS) are stochastic, non-derivative optimization method. They use popula-tions o...