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Published in Phillip A. Laplante, Dictionary of Computer Science, Engineering, and Technology, 2017
finite state machine (FSM) a mathematical model that is characterized by a mapping function from state, input symbol to a new next state. If the mapping is always to a unique next state, the automaton is designated as a deterministic finite state automaton (DFSA). If the mapping is to two or more next states, the automaton is designated as a nondeterministic finite state automaton (NDFSA). If a qualifier specifying determinism is not specified, generally a deterministic FSA is intended. A FSM describes many different concepts in communications such as convolutional coding/decoding, CPM modulation, ISI channels, CDMA transmission, shift-register sequence generation, data transmission, and computer protocols.
Introduction
Published in A. W. Jayawardena, Environmental and Hydrological Systems Modelling, 2013
Some dynamic systems are modelled best with state equations, while others are modelled best with state machines.1 State-equation systems are modelled with equations. For example, a projectile’s motion can be modelled with state equations for position and velocity, which are functions of time. State-machine systems focus less on physical variables and more on logical attributes. Therefore, such systems have memory and are modelled with finite state machines.2 Most computer systems are modelled with finite state machines.
Three-Dimensional Molecular Electronics and Integrated Circuits for Signal and Information Processing Platforms
Published in Sergey Edward Lyshevski, Nano and Molecular Electronics Handbook, 2018
The evolution of a molecular platform is due to inputs, events, state evolutions, parameter variations, etc. A vocabulary (or an alphabet) A is a finite nonempty set of symbols (elements). A world (or sentence) over A is a string of finite length of elements of A. The empty (null) string is the string which does not contain symbols. The set of all words over A is denoted as Aw. A language over A is a subset of Aw. A finite-state machine with output CFS={X,AR,AY,FR,FY,X0} consists of a finite set of states S, a finite input alphabet AR, a finite output alphabet AY, a transition function FY that assigns a new state to each state and input pair, an output function FY that assigns an output to each state and input pair, and an initial state X0. Using the input–output map, the evolution of C can be expressed as EC⊆R×Y. That is, if C in state e∈ X receives an input r∈ R, it moves to the next state f(x,r), and produces the output y(x,r). One can represent the molecular platform using the state tables, which describe the state and output functions. In addition, the state transition diagram (a direct graph whose vertices correspond to the states, and its edges correspond to the state transitions, where each edge is labeled with the input and output associated with the transition) is frequently used.
An approach integrating planning and image-based visual servo control for road following and moving obstacles avoidance
Published in International Journal of Control, 2020
Ramses Reyes, Rafael Murrieta-Cid
A finite-state machine (FSM) or automaton is defined as a mathematical model of computation, it is conceived as an abstract machine that can be in one of a finite number of states (Hopcroft, Motwani, & Ullman, 2000). Figure 2 shows a graphical representation of an automaton corresponding to the general plan or strategy to follow the road and pass or avoid collision with other cars. The automaton has five states: Start, Following left lane, Following right lane, Changing to left lane and Changing to right lane. The transitions among the states are represented with arrows, each arrow has a label corresponding to the observation (or condition) required to given a state change to other state. A state corresponds to the general internal condition of the robot, in each one of these states two variables are controlled: (1) the position in the image of the centre of the lane that the robot follows, which is regulated through the angular velocity of the vehicle and (2) the linear velocity of the vehicle, which depends on the presence or absence of obstacles and the curvature of the road. In our current implementation, the state Start is trivial, the automaton immediately transits to state Following right line, since we assume that the car starts on the right lane. It would be possible to extend this state to reach the road starting with the car placed outside the track.