Implementing and using finite automata toolkits

Finite automata and various extensions of them, such as transducers, are used in areas as diverse as compilers, spelling checking, natural language grammar checking, communication protocol design, digital circuit simulation, digital flight control, speech recognition and synthesis, genetic sequencing, and Java program verification. Unfortunately, as the number of applications has grown, so has the variety of implementations and implementation techniques. Typically, programmers will be confused enough to resort to their text books for the most elementary algorithms. Recently, advances have been made in taxonomizing algorithms for constructing and minimizing automata and in evaluating various implementation strategies Watson 1995. Armed with this, a number of general-purpose toolkits have been developed at universities and companies. One of these, FIRE Lite, was developed at the Eindhoven University of Technology, while its commercial successor, FIRE Engine II, has been developed at Ribbit Software Systems Inc. Both of these toolkits provide implementations of all of the known algorithms for constructing automata from regular expressions, and all of the known algorithms for minimizing deterministic finite automata. While the two toolkits have a great deal in common, we will concentrate on the structure and use of the noncommercial FIRE Lite. The prototype version of FIRE Lite was designed with compilers in mind. More recently, computation linguists and communications protocol designers have become interested in using the toolkit. This has led to the development of a much more general interface to FIRE Lite, including the support of both Mealy and Moore regular transducers. While such a toolkit may appear extremely complex, there are only a few choices to be made. We also consider a ‘recipe’ for making good use of the toolkits. Lastly, we consider the future of FIRE Lite. While FIRE Engine II has obvious commercial value, we are committed to maintaining a version which is freely available for academic use.

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JESSI 0.8 μm CMOS transistor model for analogue and digital circuit simulation

10.3403/00837001 ◽

1996 ◽

Keyword(s):

Circuit Simulation ◽

Digital Circuit ◽

Cmos Transistor ◽

Transistor Model

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Improving Datapath Testability by Modifying Controller Specification

VLSI Design ◽

10.1080/1065514021000012101 ◽

2002 ◽

Vol 15 (2) ◽

pp. 491-498 ◽

Cited By ~ 1

Author(s):

M. L. Flottes ◽

B. Rouzeyre ◽

L. Volpe

Keyword(s):

Finite Automata ◽

Digital Circuit ◽

Automata Theory ◽

Sharp Fall ◽

Testability Analysis ◽

Controllability And Observability ◽

Control Part

A digital circuit includes two main parts: a controller and a datapath. After connection of these two parts, both are subject to a sharp fall in testability due to the lack of controllability and observability at the interface. In this paper, we propose a method for specifying the control part in order to restore the testability of the datapath to a level close to the initial one, in other words its testability before connection. This testability driven specification affects the next state logic as well as the decoder part of the controller but does not make use of any scan-based element. Based on the finite automata theory and on results of a testability analysis performed on the datapath, the proposed method entails very little area penalty.

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An investigation on the robustness, accuracy and simulation performance of a physics-based deep-submicronmeter BSIM model for analog/digital circuit simulation

Proceedings of Custom Integrated Circuits Conference ◽

10.1109/cicc.1996.510567 ◽

2002 ◽

Author(s):

Yuhua Cheng ◽

Min-Chie Jeng ◽

Zhihong Liu ◽

Kai Chen ◽

Mansun Chan ◽

...

Keyword(s):

Circuit Simulation ◽

Digital Circuit ◽

Simulation Performance

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Java Program Verification via a JVM Deep Embedding in ACL2

Lecture Notes in Computer Science - Theorem Proving in Higher Order Logics ◽

10.1007/978-3-540-30142-4_14 ◽

2004 ◽

pp. 184-200 ◽

Cited By ~ 15

Author(s):

Hanbing Liu ◽

J. Strother Moore

Keyword(s):

Program Verification ◽

Deep Embedding ◽

Java Program

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Computer Simulation of Partial Discharges in Voids inside Epoxy Resins Using Three-Capacitance and Analytical Models

Polymers ◽

10.3390/polym12010077 ◽

2020 ◽

Vol 12 (1) ◽

pp. 77 ◽

Cited By ~ 4

Author(s):

Johnatan M. Rodríguez-Serna ◽

Ricardo Albarracín-Sánchez ◽

Ming Dong ◽

Ming Ren

Keyword(s):

Epoxy Resins ◽

Circuit Simulation ◽

Electric Circuit ◽

Real Data ◽

Theoretical Background ◽

General Purpose ◽

Partial Discharges ◽

Analytical Models ◽

Advantages And Disadvantages ◽

Capacitance Model

Epoxy resin is one of the most common polymers used as part of the insulation system in key electrical assets such as power transformers and hydrogenerators. Thus, it is necessary to know their main characteristics and to evaluate their condition when subjected to High Voltage (HV). A brief review of epoxy resins’ applications as insulating materials is made, their main characteristics as insulating media are given, the improvements with nano-fillers are summarized and the main electric properties required for Partial Discharges (PD) modelling are listed. In addition, the theoretical background and state-of-the-art of the three-capacitance and analytical models for simulating PD in solid dielectrics, such as epoxy resins, are reviewed in detail. Besides, their main advantages and disadvantages are presented, some critical arguments to the modelling procedure and assumptions are made and some improvements are proposed, taking into account conclusions made from other authors using models related to the PD development process. Finally, a case study was simulated using a modified three-capacitance model and the analytical model. The PD rate, q-φ-n diagrams and the minimum, mean and maximum PD electric charge are compared with measurements reported in the literature. Simulation results are in reasonable agreement with measured values. Capacitance models can be implemented in general purpose electric circuit simulation packages; however, its simulation is computationally expensive. Additional to this, although the modified three-capacitance model is not as accurate as finite elements or analytical models, results are also in agreement with real data.

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