Search results for "Finite-state machine"
showing 10 items of 97 documents
Latent Nestling Method: A new fault diagnosis methodology for complex systems
2008
This paper presents a new methodology for permanent and intermittent fault diagnosis, named faults latent nestling method (FLNM), using coloured Petri nets (CPNs). CPNs and FLNM method allow for an enhanced capability for synthesis and modelling of complex systems in contrast to the classical phenomena of combinational state explosion when using finite state machine based methods.
Modular fault diagnosis based on discrete event systems for a mixer chemical process
2003
The knowledge of failure type and their location is an indispensable requirement for the establishment of tasks of adequate recovery strategies and maintenance of both factory automation and process control systems. The failure diagnosis methodology presented in the paper is based on discrete event systems models and on the diagnosers concept, those which permit the analysis off-line and online of diagnosability of failures that can occur in the processes. We present an approach for models and associated diagnosers based on a modular decomposition of the global system, with the purpose of avoiding the problems of the exponential explosion of the number of states and of the computational com…
Fault diagnosis with Coloured Petri Nets using Latent Nestling Method
2008
This paper presents a new methodology for permanent and intermittent fault diagnosis, named Faults Latent Nestling Method (FLNM), using Coloured Petri Nets (CPNs). CPNs and FLNM method allow for an enhanced capability for synthesis and modelling in contrast to the classical phenomena of combinational state explosion when using Finite State Machine based methods.
Finite state verifiers with constant randomness
2014
We give a new characterization of $\mathsf{NL}$ as the class of languages whose members have certificates that can be verified with small error in polynomial time by finite state machines that use a constant number of random bits, as opposed to its conventional description in terms of deterministic logarithmic-space verifiers. It turns out that allowing two-way interaction with the prover does not change the class of verifiable languages, and that no polynomially bounded amount of randomness is useful for constant-memory computers when used as language recognizers, or public-coin verifiers. A corollary of our main result is that the class of outcome problems corresponding to O(log n)-space …
Quantum, stochastic, and pseudo stochastic languages with few states
2014
Stochastic languages are the languages recognized by probabilistic finite automata (PFAs) with cutpoint over the field of real numbers. More general computational models over the same field such as generalized finite automata (GFAs) and quantum finite automata (QFAs) define the same class. In 1963, Rabin proved the set of stochastic languages to be uncountable presenting a single 2-state PFA over the binary alphabet recognizing uncountably many languages depending on the cutpoint. In this paper, we show the same result for unary stochastic languages. Namely, we exhibit a 2-state unary GFA, a 2-state unary QFA, and a family of 3-state unary PFAs recognizing uncountably many languages; all th…
New Results on Vector and Homing Vector Automata
2019
We present several new results and connections between various extensions of finite automata through the study of vector automata and homing vector automata. We show that homing vector automata outperform extended finite automata when both are defined over $ 2 \times 2 $ integer matrices. We study the string separation problem for vector automata and demonstrate that generalized finite automata with rational entries can separate any pair of strings using only two states. Investigating stateless homing vector automata, we prove that a language is recognized by stateless blind deterministic real-time version of finite automata with multiplication iff it is commutative and its Parikh image is …
Exact affine counter automata
2017
We introduce an affine generalization of counter automata, and analyze their ability as well as affine finite automata. Our contributions are as follows. We show that there is a language that can be recognized by exact realtime affine counter automata but by neither 1-way deterministic pushdown automata nor realtime deterministic k-counter automata. We also show that a certain promise problem, which is conjectured not to be solved by two-way quantum finite automata in polynomial time, can be solved by Las Vegas affine finite automata. Lastly, we show that how a counter helps for affine finite automata by showing that the language MANYTWINS, which is conjectured not to be recognized by affin…
Power flow management controller within a grid connected photovoltaic based active generator as a finite state machine using hierarchical approach wi…
2020
Abstract Grid integration of photovoltaic (PV) system with a hybrid energy storage can help not only in increasing more penetration of PV system into the network but also in improving the power system dynamics and control in addition to helping the demand side management. In this work, a PV system with a hybrid energy storage including a battery array and a super capacitor bank is going to work as an active generator with innovative load management and power flow control strategies for managing the active power demand locally considering the grid constraints. This work proposes an architecture for a PV based active generator, which can provide active power in controlled manner while maintai…
A Novel Multi-step Finite-State Automaton for Arbitrarily Deterministic Tsetlin Machine Learning
2020
Due to the high energy consumption and scalability challenges of deep learning, there is a critical need to shift research focus towards dealing with energy consumption constraints. Tsetlin Machines (TMs) are a recent approach to machine learning that has demonstrated significantly reduced energy usage compared to neural networks alike, while performing competitively accuracy-wise on several benchmarks. However, TMs rely heavily on energy-costly random number generation to stochastically guide a team of Tsetlin Automata (TA) to a Nash Equilibrium of the TM game. In this paper, we propose a novel finite-state learning automaton that can replace the TA in TM learning, for increased determinis…
Improvement of Fingerprint Sensor Reading Using FPGA Devices
2008
In order to realize fingerprint recognition system in real time environment, we describe in this paper signal controller to read fingerprint sensor generated in FPGA devices. Basically this signal is generated using state machine. The simulation result for behavioral simulation and signal generation read by logic analyzer are presented in this paper. Initialization and reading time for 76800 pixels are 50.99 mS. It is faster than fingerprint sensor using USB connection, which is more than 250 ms.