Showing papers on "Continuous automaton published in 1993"

Partially permutive cellular automata

Abstract: One-dimensional cellular automata are analysed via their generalized permutivity. Invariant subalphabets provide a systematic way of identifying periodic and aperiodic tilings as well as stationary distributions invariant under the cellular automaton iteration. In the case of several invariant subalphabets a hierarchy of interaction phenomena arise. In particular the interaction of subalphabets can generate random walks as well as their degenerate forms. A comprehensive scheme emerges that unifies the analysis of topological defects in cellular automata. The probabilistic details of the random walks involved are treated in the companion paper in this issue.

Phase-transition study of a one-dimensional probabilistic site-exchange cellular automaton

Abstract: The effect of mixing on one-dimensional probabilistic cellular automaton with totalistic rule has been investigated by different methods. The evolution of system depends on two parameters, the probability p and the degree of mixing m. The two-dimensional phase space of parameters has been explored by simulation. The results are compared to multiple-point-correlation approximation. By increasing the mixing, the order of the phase transition has been found to change from second order to first order. The tricritical point has been located and estimates are given for the \ensuremath{\beta} exponent. Short- and long-range mixing are compared.

Inhomogeneous cellular automata for weighted random pattern generation

Abstract: Weighted random pattern testing methods produce higher fault coverage with shorter test lengths than random pattern testing methods. Here we present the weighted cellular automaton (WCA), an inhomogeneous cellular automaton that generates weighted random patterns on a test per clock basis. The WCA is a complete automaton that contains no external weighting logic and no multiplexers between flip-flop outputs and the circuit under test that add to critical path delays. Since the structure is based on cellular automata there are no complex routing problems. We also give a design algorithm, WCARGO, that automatically generates WCA from an ordered set of weights. >

Oscillatory patterns in an autocatalytic reaction ring network simulated by a probabilistic cellular automaton

Abstract: A two dimensional probabilistic cellular automaton is presented. It simulates a reaction-diffusion process occurring in biomembranes during active transport described by an autocatalytic ring network. The automaton suffers a transition from a completely disordered state to a state with well defined oscillations and spatial inhomogeneous patterns by changing the parameters. The different dynamic states have been characterized by means of Fourier transforms of concentration time evolution and through the definition of an agglomeration parameter. Vacancy concentration and lattice size effects are analyzed.

Prototype for memory effects in the time evolution of damage.

Abstract: We introduce a one-dimensional cellular automaton as a prototype for memory effects on damage. The associated Hamming distance as a function of time correctly mimics complex dynamical systems and, for different values of the external parameters, gradually varies between a noiselike behavior and a plateaulike one

Cellular automata, a simple approach to complexity

Abstract: Publisher Summary Structure formation in nature is often based on simple interaction between spatially distributed basic units. To deal with structure formation, it is necessary to understand the relation between its local and global aspects. According to John von Neumann's definition, a cellular automaton consists of a finite number of cells that may be depicted as, for instance, the various squares in a planar checkerboard pattern. To each of these cells, a finite number of states are ascribed among which the cell is allowed to vary. Given a configuration of states, one for each cell, the next configuration of states is determined according to local interaction rules. This chapter describes the approach of cellular automata, which can be used to find out which particular feature of the dynamics of a complex molecular system may be responsible for the observed formation of particular patterns or structures.