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93
Security in computing
, 2006
"... Abstract. Comparing technical notions of communication and computation leads to a surprising result, these notions are often not conceptually distinguishable. This paper will show how the two notions may fail to be clearly distinguished from each other. The most famous models of computation and comm ..."
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Abstract. Comparing technical notions of communication and computation leads to a surprising result, these notions are often not conceptually distinguishable. This paper will show how the two notions may fail to be clearly distinguished from each other. The most famous models of computation and communication, Turing Machines and (Shannonstyle) information sources, are considered. The most significant difference lies in the types of statetransitions allowed in each sort of model. This difference does not correspond to the difference that would be expected after considering the ordinary usage of these terms. However, the natural usage of these terms are surprisingly difficult to distinguish from each other. The two notions may be kept distinct if computation is limited to actions within a system and communications is an interaction between a system and its environment. Unfortunately, this decision requires giving up much of the nuance associated with natural language versions of these important terms. 1.
The PhaseSpace Dynamics of Systems of Spiking Neurons
, 2001
"... This thesis investigates the dynamics of systems of neurons in the brain. It considers two questions: (1) Are there coherent spatiotemporal structures in the dynamics of neuronal systems that can denote discrete computational states, and (2) If such structures exist, what restrictions do the dynami ..."
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This thesis investigates the dynamics of systems of neurons in the brain. It considers two questions: (1) Are there coherent spatiotemporal structures in the dynamics of neuronal systems that can denote discrete computational states, and (2) If such structures exist, what restrictions do the dynamics of the system at the physical level impose on the dynamics of the system at the corresponding abstracted computational level. These problems are addressed by way of an investigation of the phasespace dynamics of a general model of local systems of biological neurons. An abstract physical system is constructed based on a limited set of realistic assumptions about the biological neuron. The system, in consequence, accommodates a wide range of neuronal models. Appropriate instantiations of the system are used to simulate the dynamics of a typical column in the neocortex. The results demonstrate that the dynamical behavior of the system is akin to that observed in neurophysiological experiments. Formal analysis of local properties of flows reveals contraction, expansion, and folding in different sections of the phasespace. A stochastic process is formulated in order to determine
Lazy XML Processing
, 2002
"... This paper formalizes the domain of treebased XML processing and classifies several implementation approaches. The lazy approach, an original contribution, is presented in depth. ..."
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This paper formalizes the domain of treebased XML processing and classifies several implementation approaches. The lazy approach, an original contribution, is presented in depth.
Turing Oracle Machines, Online Computing, and Three Displacements in Computability Theory
, 2009
"... ..."
Symbol Processing Systems, Connectionist Networks, and Generalized Connectionist Networks
 IN S. GOONATILAKE AND S.KHEBBAL, EDITORS INTELLIGENT HYBRID SYSTEMS
, 1990
"... Many authors have suggested that SP (symbol processing) and CN (connectionist network) models offer radically, or even fundamentally, different paradigms for modeling intelligent behavior (see Schneider, 1987) and the design of intelligent systems. Others have argued that CN models have little to co ..."
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Cited by 9 (6 self)
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Many authors have suggested that SP (symbol processing) and CN (connectionist network) models offer radically, or even fundamentally, different paradigms for modeling intelligent behavior (see Schneider, 1987) and the design of intelligent systems. Others have argued that CN models have little to contribute to our efforts to understand intelligence (Fodor & Pylyshyn, 1988). A critical examination of the popular characterizations of SP and CN models suggests that neither of these extreme positions is justified. There are many advantages to be gained by a synthesis of the best of both SP and CN approaches in the design of intelligent systems. The Generalized connectionist networks (GCN) (alternately called generalized neuromorphic systems (GNS)) introduced in this paper provide a framework for such a synthesis.
What is a Universal HigherOrder Programming Language?
 In Proc. International Conference on Automata, Languages, and Programming. Lecture Notes in Computer Science
, 1993
"... . In this paper, we develop a theory of higherorder computability suitable for comparing the expressiveness of sequential, deterministic programming languages. The theory is based on the construction of a new universal domain T and corresponding universal language KL. The domain T is universal for ..."
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. In this paper, we develop a theory of higherorder computability suitable for comparing the expressiveness of sequential, deterministic programming languages. The theory is based on the construction of a new universal domain T and corresponding universal language KL. The domain T is universal for observably sequential domains; KL can define all the computable elements of T, including the elements corresponding to computable observably sequential functions. In addition, domain embeddings in T preserve the maximality of finite elementspreserving the termination behavior of programs over the embedded domains. 1 Background and Motivation Classic recursion theory [7, 13, 18] asserts that all conventional programming languages are equally expressive because they can define all partial recursive functions over the natural numbers. This statement, however, is misleading because real programming languages support and enforce a more abstract view of data than bitstrings. In particular, mo...
How much can analog and hybrid systems be proved (super)Turing
 Applied Mathematics and Computation
, 2006
"... Church thesis and its variants say roughly that all reasonable models of computation do not have more power than Turing Machines. In a contrapositive way, they say that any model with superTuring power must have something unreasonable. Our aim is to discuss how much theoretical computer science can ..."
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Church thesis and its variants say roughly that all reasonable models of computation do not have more power than Turing Machines. In a contrapositive way, they say that any model with superTuring power must have something unreasonable. Our aim is to discuss how much theoretical computer science can quantify this, by considering several classes of continuous time dynamical systems, and by studying how much they can be proved Turing or superTuring. 1
Termination, ACTermination and Dependency Pairs of Term Rewriting Systems
 Ph.D. thesis, JAIST
, 2000
"... Copyright c ○ 2000 by Keiichirou KUSAKARI Recently, Arts and Giesl introduced the notion of dependency pairs, which gives effective methods for proving termination of term rewriting systems (TRSs). In this thesis, we extend the notion of dependency pairs to ACTRSs, and introduce new methods for eff ..."
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Copyright c ○ 2000 by Keiichirou KUSAKARI Recently, Arts and Giesl introduced the notion of dependency pairs, which gives effective methods for proving termination of term rewriting systems (TRSs). In this thesis, we extend the notion of dependency pairs to ACTRSs, and introduce new methods for effectively proving ACtermination. Since it is impossible to directly apply the notion of dependency pairs to ACTRSs, we introduce the head parts in terms and show an analogy between the root positions in infinite reduction sequences by TRSs and the head positions in those by ACTRSs. Indeed, this analogy is essential for the extension of dependency pairs to ACTRSs. Based on this analogy, we define ACdependency pairs. To simplify the task of proving termination and ACtermination, several elimination transformations such as the dummy elimination, the distribution elimination, the general dummy elimination and the improved general dummy elimination, have been proposed. In this thesis, we show that the argument filtering method combined with the ACdependency pair technique is essential in all the elimination transformations above. We present remarkable simple proofs for the soundness of these elimination transformations based on this observation. Moreover, we propose a new elimination transformation, called the argument filtering transformation, which is not only more powerful than all the other elimination transformations but also especially useful to make clear an essential relationship among them.