The linear complexity and k-error linear complexity of sequences are important measures of the strength of key-streams generated by stream ciphers. The counting function of a sequence complexity measure gives the number of sequences with given complexity measure value and it is useful to determine the expected value and variance of a given complexity measure of a family of sequences. Fu et al. ...

The analysis of symbolic dynamics applied to physiological time series retrieves dynamical properties of the underlying regulation which are robust against the symbolic transformation. In this study, three different transformations to produce a symbolic series were applied to fetal RR interval series to test whether they reflect individual changes of fetal heart rate variability in the course o...

We present a method to reduce the [FORMULA: SEE TEXT] dynamics of coupled map lattices (CMLs) of N invertibly coupled unimodal maps to a sequence of N-bit symbols. We claim that the symbolic description is complete and provides for the identification of all fixed points, periodic orbits, and dense orbits as well as an efficient representation for studying pattern formation in CMLs. We give our ...

Metastable attractors and heteroclinic orbits are present in the dynamics of various complex systems. Although their occurrence is well-known, their identification and modeling is a challenging task. The present work reviews briefly the literature and proposes a novel combination of their identification in experimental data and their modeling by dynamical systems. This combination applies recur...

We describe a method for introducing variations into predeened dance sequences using a chaotic mapping. A symbol sequence representing a dance piece is mapped onto a chaotic trajectory, establishing a symbolic dynamics that links the dance sequence and the attractor structure. A choreographic variation on the original piece is created by generating a trajectory with slightly diierent initial co...

What are the characteristics of long-term learning? We investigated the characteristics of long-term, symbolic learning using the Soar and ACT-R cognitive architectures running cognitive models of two simple tasks. Long sequences of problems were run collecting data to answer fundamental questions about long-term, symbolic learning. We examined whether symbolic learning continues indefinitely, ...

Two symbolic indexes, the percentage of sequences characterized by three heart periods with no significant variations (0V%) and that with two significant unlike variations (2UV%), have been found to reflect changes in sympathetic and vagal modulations, respectively. We tested the hypothesis that symbolic indexes may track the gradual shift of the cardiac autonomic modulation during an increment...

Graphs can be represented symbolically by the Ordered Binary Decision Diagram (OBDD) of their characteristic Boolean function. The latter is said to have bounded width b if its minimal-size complete OBDD has bounded width b. Bounded-width functions have small OBDDs and allow efficient functional operations. Therefore, they are of interest in the analysis of symbolic graph algorithms. In this pa...

In this paper, we explore the differences between direct and symbolic sequential modeling of prosody. We use sequential models to characterize speech in two tasks, classifying speaking-style and distinguishing native from non-native speech. We explore the use of a spike-and-slab model to directly model pitch contour data. We find in both of these tasks that sequences of symbolic prosodic events...

Interest in modular satellites has increased recently. In this paper, we present our approach for planing an OnOrbit-Servicing (OOS) task for a robotic servicer. One key challenge is the gap between the symbolic planing of action sequences and their execution in the continuous space. To bridge this gap, we propose a sampling based workspace description. It is queried by an Hierarchical Task Net...