Search results for "Turing"
showing 10 items of 2644 documents
Geometric and conceptual knowledge representation within a generative model of visual perception
1989
A representation scheme of knowledge at both the geometric and conceptual levels is offered which extends a generative theory of visual perception. According to this theory, the perception process proceeds through different scene representations at various levels of abstraction. The geometric domain is modeled following the CSG (constructive solid geometry) approach, taking advantage of the geometric modelling scheme proposed by A. Pentland, based on superquadrics as representation primitives. Recursive Boolean combinations and deformations are considered in order to enlarge the scope of the representation scheme and to allow for the construction of real-world scenes. In the conceptual doma…
Heuristics for the Constrained Incremental Graph Drawing Problem
2019
Abstract Visualization of information is a relevant topic in Computer Science, where graphs have become a standard representation model, and graph drawing is now a well-established area. Within this context, edge crossing minimization is a widely studied problem given its importance in obtaining readable representations of graphs. In this paper, we focus on the so-called incremental graph drawing problem, in which we try to preserve the user’s mental map when obtaining successive drawings of the same graph. In particular, we minimize the number of edge crossings while satisfying some constraints required to preserve the position of vertices with respect to previous drawings. We propose heur…
Diffusive neural network
2002
Abstract A non-connectionist model of a neuronal network based on passive diffusion of neurotransmitters is presented as an alternative to hard-wired artificial neural networks. Classic thermodynamical approach shows that the diffusive network is capable of exhibiting asymptotic stability and a dynamics resembling that of a chaotic system. Basic computational capabilities of the net are discussed based on the equivalence with a Turing machine. The model offers a way to represent mass-sustained brain functions in terms of recurrent behaviors in the phase space.
Quantum versus Probabilistic One-Way Finite Automata with Counter
2001
The paper adds the one-counter one-way finite automaton [6] to the list of classical computing devices having quantum counterparts more powerful in some cases. Specifically, two languages are considered, the first is not recognizable by deterministic one-counter one-way finite automata, the second is not recognizable with bounded error by probabilistic one-counter one-way finite automata, but each recognizable with bounded error by a quantum one-counter one-way finite automaton. This result contrasts the case of one-way finite automata without counter, where it is known [5] that the quantum device is actually less powerful than its classical counterpart.
Multiple Usage of Random Bits in Finite Automata
2012
Finite automata with random bits written on a separate 2-way readable tape can recognize languages not recognizable by probabilistic finite automata. This shows that repeated reading of random bits by finite automata can have big advantages over one-time reading of random bits.
Tally languages accepted by Monte Carlo pushdown automata
1997
Rather often difficult (and sometimes even undecidable) problems become easily decidable for tally languages, i.e. for languages in a single-letter alphabet. For instance, the class of languages recognizable by 1-way nondeterministic pushdown automata equals the class of the context-free languages, but the class of the tally languages recognizable by 1-way nondeterministic pushdown automata, contains only regular languages [LP81]. We prove that languages over one-letter alphabet accepted by randomized one-way 1-tape Monte Carlo pushdown automata are regular. However Monte Carlo pushdown automata can be much more concise than deterministic 1-way finite state automata.
The computational power of continuous time neural networks
1997
We investigate the computational power of continuous-time neural networks with Hopfield-type units. We prove that polynomial-size networks with saturated-linear response functions are at least as powerful as polynomially space-bounded Turing machines.
Ultrametric Finite Automata and Turing Machines
2013
We introduce a notion of ultrametric automata and Turing machines using p-adic numbers to describe random branching of the process of computation. These automata have properties similar to the properties of probabilistic automata but complexity of probabilistic automata and complexity of ultrametric automata can differ very much.
Ultrametric Algorithms and Automata
2015
We introduce a notion of ultrametric automata and Turing machines using p-adic numbers to describe random branching of the process of computation. These automata have properties similar to the properties of probabilistic automata but complexity of probabilistic automata and complexity of ultrametric automata can differ very much.
How to simulate free will in a computational device
1999
Since we believe that human brain is not a purely deterministic device merely reacting to the environment but rather it is capable to a free will, Theoretical Computer Science has also tried to develop a system of notions generalizing determinism. Nondeterministic and probabilistic algorithms were the first generalizations. Nondeterministic machines constitute an important part of the Theory of Computation. Nondeterminism is a useful way to describe possible choices. In real life there are many regulations restricting our behavior. These regulations nearly always leave some freedom for us how to react. Such regulations are best described in terms of nondeterministic algorithms. Nondetermini…