We formulate general rules for a coarse graining of the dynamics, which we term "symbolic dynamics," of feedback networks with monotonic interactions, such as most biological modules. Networks which are more complex than simple cyclic structures can exhibit multiple different symbolic dynamics. Nevertheless, we show several examples where the symbolic dynamics is dominated by a single pattern t...

Connectionist models often offer good performance in pattern recognition and generalization, and present such qualities as natural learning ability, noise tolerance and graceful degradation. By contrast, symbolic models often present a complementary profile: they offer good performance in reasoning and deduction, and present such qualities as natural symbolic manipulation and explanation abilit...

Computation is classically studied in terms of automata, formal languages and algorithms; yet, the relation between neural dynamics and symbolic representations and operations is still unclear in traditional eliminative connectionism. Therefore, we suggest a unique perspective on this central issue, to which we would like to refer as transparent connectionism, by proposing accounts of how symbo...

We describe the structure and the usage of a new software tool, called r-TuBound, for deriving symbolic loop iteration bounds in the worst-case execution time (WCET) analysis of programs. r-TuBound implements algorithms for pattern-based recurrence solving and program flow refinement, and it was successfully tested on a wide range of examples. The purpose of this article is to illustrate what r...

In this paper, the Exp-function method, with the aid of a symbolic computation system such as Maple, is applied to the (2+1) -dimensional Calogero Bogoyavlanskii Schiff equation. Exact and explicit generalized solitary solutions are obtained in more general forms. The free parameters can be determined by initial or boundary conditions. The method is straightforward and concise, and its applicat...

In the real world, an operational text classification system is usually placed in the environment where the amount of human-annotated training documents is small in spite of thousands of classes. In this environment text classifier are probably the most appropriate methods for the practical systems rather than other complex learning models. Text classifiers are basically used for free flowing t...

In this paper, we introduce a novel data model for representing symbolic trajectories along with a pattern language enabling both the matching and the rewriting of trajectories. We illustrate in particular the trajectory data type and two operations for querying symbolic trajectories inside the database system Secondo. As an important application of our theory, the classification and depiction ...