algorithm deriving by the so called SOMs (Self Organizing Maps) and implementing a classical statistical mechanics renormalization approach in which each element of a system re-orientates itself coherently with the orientation of the neighbors and iterating the same model at different scales [ 1, 19, 20].
We propose a new approach, by implementing a generalized multiscale framework, based on the classical Poisson Nernst Planck theory, which is valid for both charged and uncharged porous media.
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WebConf implements a classical review process similar to the processes used by Springer, Elsevier and other large commercial publishers.
The third algorithm implements a classical hysteresis scheme, where a reoptimization is only applied if the throughput is improved by a configurable amount.
However, a connectionist network can implement a classical Turing machine architecture (see, e.g., Fodor and McLaughlin 1990; Chalmers 1993).
They argue that systematicity and productivity fail in connectionist models, except when the connectionist model implements a classical model.
Many, if not most, of the adherents of classical computation, for example proponents of CTM, think that the brain is an associative network, one which implements a classical computational program.
We obtain a clustering approach for trees by implementing classical statistical tests on this parameter, thus providing well balanced drawings of trees offering better aspect ratios which can be useful when dealing with large, irregular hierarchical data.
(Kent (1999) has shown that one can implement a secure classical bit commitment protocol by exploiting relativistic signalling constraints in a timed sequence of communications between verifiably separated sites for both Alice and Bob).
