(1) As a consequence, a neural network, considered as a kind of parallel random automata, delivers an output random field in response to the excitation provided by a random field that represents the activity of some input fibers.
(2) In this respect, the present article describes a simple model, based on binary variables and automata theory, which simulates the basic regulatory performance of the modulated enzyme.
(3) Real reproducing systems are contrasted with cellular automata-based models of self-reproduction.
(4) In order to modelize this characteristic, we designed automata with a finite number of instantaneous internal descriptions, with input(s) and output(s) and which are able to be functionally modified.
(5) In this paper we use cellular automata to study growth factor (IL-2) dependent proliferation of helper T cell (Th) and B cell clones at the level of individual cells.
(6) The joints thereby behave as a set of Tsetlin's abstract automata [11], each functioning independently and guided by a common, collective effect.
(7) The problem may be approached by viewing the egg as containing a program for development, and considering the logical nature of the program by treating cells as automata and ignoring the details of molecular mechanisms.
(8) Patterns are translated into finite state automata which allow very efficient searches.
(9) This problem is solved in the present work by automata based on a random distribution of excitable elements.
(10) When asynchronous updating is introduced for the transition of cellular automata, various kinds of patterns such as traveling waves, kinks, oscillatory local patterns etc.
(11) Cellular automata are desirable because of their intuitive appeal and efficient digital implementation, but until now they have not served as reliable models because they have lacked two essential properties of excitable media.
(12) The data processing is based on a one-pass computation involving automata theory and therefore it avoids the storage of the image in the computer memory.
(13) A recently introduced class of models, the Movable Finite Automata (MFA) models, are used for simulating the elongation of the polypeptide chain in protein biosynthesis.
(14) Ion channels in a cell membrane were modeled by a computer simulation of fluctuating pores distributed in a spatial array, a cellular automata.
(15) Each automaton in this model is characterized by a network of n x m processors that process the information contained in levels 0 to m. The effect of the automaton's architecture on its ability to satisfy variations in constraints is analysed, and automata-evolution experiments are described.
(16) The recurrent collateral inhibition existing between Purkinje cells was mimicked by means of an assembly of neuronal automata (NA) temporally evolving at random through three states ("silent", "tonic" and "phasic" and interacting with simple rules.
(17) Linear stability analysis, and numerical, and cellular automata simulations reveal that as parameters are varied, a bifurcation leads to loss of stability of a uniform (isotropic) steady state, in favor of an (anisotropic) patterned state in which cells are aligned in parallel arrays.
(18) By modeling Ca2+ release with cellular automata, the absolute refractory period for Ca2+ stores (4.7 seconds) was determined.
(19) Small networks of threshold automata are used to model complex interactions between populations of regulatory cells (helpers and suppressors, antigen specific and anti-idiotypic) which participate in the immune response.
(20) As an efficient alternative to partial differential equations, cellular automata have been proposed for the simulation of excitable media.