Titlebook: Unconventional Models of Computation, UMC’2K; Proceedings of the S I. Antoniou,C. S. Calude,M. J. Dinneen Conference proceedings 2001 Sprin

束以馬具

Macroscopic Molecular Computation with Gene Networks,ion, neural networks, neuromorphic engineering and other analog VLSI devices. Since the 60’s genetic regulatory systems are thought of as “circuits” or “networks” of interacting components. The genetic material is the “program” that guides protein production in a cell. Protein levels determine the e

Cerumen

, Transcriptional Circuits,inning of their study [.,.]. Generic properties of both types of network have been analyzed using the same class of abstract models [.]. The same rate equations proposed for recurrent neural networks [.] have been used, with a few embellishments, to model genetic regulatory circuits controlling deve

voluble

Parallelizing with Limited Number of Ancillae,lable ancillae is limited and parallelization means that a given quantum circuit is reconstructed as one with smaller depth. As a by-product, for the three types of .-input quantum circuits, upper bounds on the number of ancillae for parallelizing to logarithmic depth are reduced to 1/ log . of the

FRONT

Upper and Lower Bounds on Continuous-Time Computation,ns in continuous time. We show that several classical computation classes have natural analog counterparts, including the primitive recursive functions, the elementary functions, the levels of the Grzegorczyk hierarchy, and the arithmetical and analytical hierarchies.

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Concomitant

On P Systems with Active Membranes,ve membranes. First, we show that the Hamiltonian Path Problem can be solved in polynomial time by P systems with active membranes where the membranes are only divided into two new membranes (a result of this type was obtained by Krishna and Rama, [.], but making use of the possibility of dividing a

紀(jì)念

Spatial Computing on Self-Timed Cellular Automata,ters with very homogeneous structures like cellular automata. It is expected that such computers can be manufactured cost-effectively in nanotechnology and will be at least ten orders of magnitude more powerful than current computers. Attempts to do general-purpose computations on cellular automata,

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食料

Computational Methods and Tools for Modeling and Analysis of Complex Processes,al networks for the function approximation and for the reconstruction and prediction of chaotic time series, and 3) the use of cellular automata (CA) in pattern recognition and in modeling of complex dynamical systems.