格值有限自动机等价判定算法

引入了完备L-Fuzzy矩阵的概念,给出了基于格半群的模糊有限自动机的形式化定义,即完备格值有限自动机,研究了它的主要性质;给出了完备格值有限自动机的行为矩阵,从行为矩阵出发,给出了自动机状态等价和自动机等价的定义。最后,得到了该类自动机等价的判定算法。     

模糊Moore型自动机的性质(英文)

给出了模糊Moore型自动机可逆、可达和完备的定义;讨论了其相关性质,进而表明这些性质之间的关系,并且研究了模糊Moore型自动机的最小化性质。最后,系统地给出了关于它们的一些重要结果。     

量子Mealy自动机和量子Moore自动机的等价

随着大数分解的量子算法和量子搜索算法的给出,量子计算进入了一个全新的迅速的发展时期.量子自动机是近十年来兴起的量子计算理论,是一个很活跃的研究领域,量子自动机的研究已经相当丰富.首先定义了字符集上的有限维Fock空间,给出基于有限维Fock空间的量子Mealy自动机和量子Moore自动机的定义,考虑在不受外界环境影响下的两种量子自动机构成的封闭的量子系统,详细地研究了量子Mealy自动机和量子Moore自动机的演化过程,利用量子力学中密度算子的基本理论给出量子Mealy自动机和量子Moore自动机生成的量子语言.最后,在考虑纯态的情形下证明了量子Mealy自动机与量子Moore自动机是等价的.     

论回溯自动机

为了描述集成化软件工程环境用户接口中选单的控制机构,需要引入回溯自动机的概念。本文给出了回溯自动机概念的严格数学定义,并讨论了它与有穷自动机、确定的下推自动机等之间的关系,证明了它所接受的语言类处于正则语言类与确定的上下文无关语言类之间。     

格值有限状态自动机的半群

提出了格值有限状态自动机的定义,给出了格值有限状态自动机的两种同余关系,研究了格值有限状态自动机的半群的若干性质,最后给出了两种有限半群E(A)和E(A)的关系。     

两类具有输出字符功能的模糊自动机的关系

在文中,对文献8中介绍的具有输出字符功能的模糊自动机和模糊有限状态自动机的定义作了修改,并对它们进行了系统的研究,揭示了此两类自动机和取分配格的代数性质的紧密联系;得到了此两类自动机在:(1)强等价;(2)等价;(3)弱等价条件下的许多重要结论。     

模糊树自动机语言的封闭性

给出了[Σ-]代数、[Σ-]树、模糊[Σ-]树自动机、模糊[Σ-]树自动机行为的定义。引入了模糊树自动机语言的并、交、连接和Kleene闭包运算,证明了在这些运算下模糊树自动机语言的封闭性。     

基于非齐整自动机模型的离散事件系统监控

本文研究了一类不能用齐整自动机建模的离散事件系统的监控问题,首先介绍了自动机齐整性的定义及检测方法，接着给出了将系统分解为若干个子系统的算法，最后讨论了系统监控问题，所得结果具有一定的参考价值。     

同步格值自动机的约简和最小化算法

引入了完备L-Fuzzy矩阵的概念,提出了取值于格半群上的输入字符和输出字符长度相同的模糊自动机的概念,即完备的同步格值自动机的概念,研究了它的主要性质;从行为矩阵出发,给出了完备的同步格值自动机状态等价和自动机等价的定义,从自动机的状态等价,研究了该自动机可约简的条件,并得到了该自动机的最小化算法。     

概率有限自动机的积和分解

给出几种概率有限自动机的积,讨论了他们之间的相互关系,并在文献[1]的基础上利用这些积给出匀概率有限自动机的分解,证明了一个匀概率有限自动机可以分解为一个随机编码源、一个伯努利过程和一些确定有限自动机的串联积。     

赋权型自动机的不同模型研究

自动机理论是理论计算机科学的基础理论之一,在很多领域自动机有着广泛的应用,有穷状态自动机是正则语言的识别机器,通常分为确定型与非确定型两种模型,其识别语言的能力是等价的。赋权自动机是另一类重要的自动机模型,自动机的每条转移规则和状态可以赋以某一代数结构上的某一数值,从而可以计算输入字符串的权值。任何有穷状态自动机都可以视为一特殊赋权自动机,因此赋权自动机功能更强大,应用更为广泛。     

基于有限状态自动机的服务组合模型

分析了目前服务计算的研究现状和存在的问题，在D Berardi和A Wombacher的基础上提出了一种带条件的有限状态自动机模型cFSA（Finite State Automata with condition），并给出了基于cFSA的服务理论模型．在该服务理论模型的基础上提出了一种基于有限状态自动机的服务组合形式化模型，并给出了该模型的代数性质和实现方法．     

基于摩尔奇偶型的元胞自动机演化模型

由于元胞自动机的理论基础较为薄弱,对元胞自动机的演化规则的研究和分析是个倍受关注的挑战问题.在奇偶元胞自动机的基础上,提出了一种摩尔奇偶型的元胞自动机演化模型,通过大量的计算机仿真实验,证实PCA与MPCA在演化过程中均具有一定的演化基元、演化框架和演化周期规律.提供了研究元胞自动机演化规则的新思路,并进一步将提出的演...     

Sufficient conditions of deterministic implementation of finite-state automata with retention of the numbers of their states

The following three conditions for nondeterministic finite-state automata are defined: input embeddability, output embeddability, and input decomposability. Automata satisfying these conditions are called nondeterministic automata with embeddability. A method for deterministic implementation of such automata with retention of the numbers of their states is proposed. These automata correspond to block-procedural high-level programming languages. Translated from Kibernetika i Sistemnyi Analiz, No. 3, pp. 55–62, May–June, 2000.     

基于元胞自动机扩展模型的图的最短路径算法

利用元胞自动机在元胞空间上的并行特性，采用元胞动态邻居，时间段自适应调整的方法，构造出一种新的基于元胞自动机扩展模型的最短路径搜索算法，即通过简单规则的元胞状态演化，得到带权图的最短路径；该方法经过优化，能够达到Dijkstra算法的时间效率；并且为基于元胞自动机扩展模型解决图的问题的提供了新的思路。     

Weak bisimulation for Probabilistic Timed Automata

We are interested in describing timed systems that exhibit probabilistic behaviour. To this purpose, we consider a model of Probabilistic Timed Automata and introduce a concept of weak bisimulation for these automata, together with an algorithm to decide it. The weak bisimulation relation is shown to be preserved when either time, or probability is abstracted away. As an application, we use weak bisimulation for Probabilistic Timed Automata to model and analyze a timing attack on the dining cryptographers protocol.     

An approximation algorithm for state minimization in 2-MDFAs

In this paper, we analyze the problem of state minimization in a class of Finite State Automata called Two Start State Deterministic Finite State Automata (2-MDFAs). A 2-MDFA is similar to a deterministic finite state automaton (DFA), in that on a given input, each state has precisely one destination state; however, it differs from a DFA in that there are two start states. A string is accepted by a 2-MDFA if and only if there exists a transitional path from either start state to a finish state, on that string. Observe that 2-MDFAs provide a limited amount of non-determinism and hence investigating their properties from the perspective of state minimization is a worthwhile pursuit. In case of unbounded non-determinism, i.e., Non-deterministic finite state automata (NFAs), it is well-known that the state minimization problem is PSPACE-complete [Jiang and Ravikumar in Proceedings of the 18th International Colloquium on Automata, Languages and Programming, ICALP’91, Madrid, Spain, July 8–12, 1991] and further that such automata can be exponentially more succinct than DFAs [Meyer and Fischer in Proceedings of the 12th SWAT(Annual Symposium on switching and automata theory), pp 188-191, 1971]. Even in the case of 2-MDFAs, the minimization problem remains non-trivial; indeed, Malcher in Theor Comput Sci 327(3):375–390, 2004 shows that the corresponding decision problem is NP-complete. We focus on deriving approximability bounds for the state minimization problem in 2-MDFAs. Our main contribution in the current paper, is the design of an n-approximation algorithm for state minimization in 2-MDFAs, where n denotes the minimum number of states required to represent the input language as a 2-MDFA. We also present a proof that this bound is tight for our algorithm.The work of K. Subramani was supported in part by the Air-Force office of Scientific Research under Grant FA9550-06-1-0050     

线性有限自动机的同步序列及其生成算法

文章主要讨论了线性有限自动机的同步序列,得到了线性有限自动机有同步序列的充要条件,还讨论了一类输入存贮线性有限自动机及可等价嵌入输入存贮线性有限自动机的极小线性有限自动机的同步序列。最后给出了判断线性有限自动机有无同步序列以及求线性有限自动机(最短)同步序列的一些算法。     

Fusion of learning automata theory and granular inference systems: ANLAGIS. Applications to pattern recognition and machine learning

In this paper the fusion of artificial neural networks, granular computing and learning automata theory is proposed and we present as a final result ANLAGIS, an adaptive neuron-like network based on learning automata and granular inference systems. ANLAGIS can be applied to both pattern recognition and learning control problems. Another interesting contribution of this paper is the distinction between pre-synaptic and post-synaptic learning in artificial neural networks. To illustrate the capabilities of ANLAGIS some experiments on knowledge discovery in data mining and machine learning are presented. The main, novel contribution of ANLAGIS is the incorporation of Learning Automata Theory within its structure; the paper includes also a novel learning scheme for stochastic learning automata.     

Checking Temporal Duration Properties of Timed Automata

In this paper, the problem of checking a timed automaton for a Duration Calculus formula of the form Temporal Duration Property is addressed. It is shown that Temporal Duration Properties are in the class of discretisable real-time properties of Timed Automata, and an algorithm is given to solve the problem based on linear programming techniques and the depth-first search method in the integral region graph of the automaton. The complexity of the algorithm is in the same class as that of the solution of the reachability problem of timed automata.