On the detection of deterministic structures in irregular signals

1992 ◽  
Vol 55 (2) ◽  
pp. 121-125 ◽  
Author(s):  
M. D�mmig ◽  
C. Boden ◽  
F. Mitschke
Keyword(s):  
Deterministic Structures

Small-scale transition in a plane mixing layer

1990 ◽  
Vol 210 ◽  
pp. 475-500 ◽  
Author(s):  
Lein-Saing Huang ◽  
Chih-Ming Ho
Keyword(s):  
Mixing Layer ◽  
Transition Process ◽  
Small Scale ◽  
Generation Process ◽  
Streamwise Vortices ◽  
Vortex Merging ◽  
Laminar Mixing ◽  
Scale Turbulence ◽  
Deterministic Structures ◽  
Streamwise Distance

An experimental study was conducted to investigate the’ generation process of random small-scale turbulence in an originally laminar mixing layer. The evolutions of the two types of deterministic structures, the spanwise and streamwise vortices, were first clarified in order to determine their roles in the transition process. A scaling rule for the streamwise distance from the trailing edge of the splitter plate to the vortex merging position was found for various velocity ratios. After this streamwise lengthscale was determined, it became clear that the spanwise wavelength of the streamwise vortices doubled after the merging of the spanwise structures which nominally doubled streamwise wavelengths. The most interesting finding was that the random small-scale eddies were produced by the interactions between the merging spanwise structures and the streamwise vortices.

Non-deterministic structures of computation

2014 ◽  
Vol 25 (6) ◽  
pp. 1295-1338 ◽  
Author(s):  
YUXI FU
Keyword(s):  
Point Of View ◽  
Process Models ◽  
Theory Of Computation ◽  
Recursively Enumerable Set ◽  
Recursively Enumerable ◽  
Abstract Representations ◽  
Finite State ◽  
Model Independent ◽  
Infinite State ◽  
Deterministic Structures

Divergence and non-determinism play a fundamental role in the theory of computation, and their combined effect on computational equality deserves further study. By looking at the issue from the point of view of both computation and interaction, we are led to a canonical equality for non-deterministic computation, revealing its rich algebraic structure. We study this structure in three ways. First, we construct a complete equational system for finite-state non-deterministic computation. The challenge with such a system is to find an equational alternative to fixpoint inductionà laMilner. We establish a negative result in the form of the non-existence of a finite equational system for the canonical equality of non-deterministic computation to support our approach. We then investigate infinite-state non-deterministic computation in the light of definability and show that every recursively enumerable set is generated by an unobservable process. Finally, we prove that, as far as computation is concerned, the effect produced jointly by divergence and non-determinism is model independent for a large class of process models.We use C-graphs, which are interesting in their own right, as abstract representations of the computational objects throughout the paper.

SYNCHRONIZATION AND DECODING INTERSPIKE INTERVALS

2002 ◽  
Vol 12 (05) ◽  
pp. 983-999 ◽  
Author(s):  
SEUNG KEE HAN ◽  
WON SUP KIM ◽  
HYUNGTAE KOOK
Keyword(s):  
Prediction Error ◽  
Neuron Model ◽  
Estimation Error ◽  
Temporal Coding ◽  
Reconstruction Method ◽  
Interspike Intervals ◽  
Model Driven ◽  
Attractor Reconstruction ◽  
Parameter Values ◽  
Deterministic Structures

Decoding of a sequence of interspike intervals (ISIs) of a neuron model driven by a chaotic stimulus is performed based on the attractor reconstruction method. As stimulus strength increases, both the stimulus estimation error and the prediction error in predicting stimulus crosswise by exploiting ISIs information tend to decrease with transitional drops at certain parameter values. It is analyzed that such behaviors are well explained in the context of synchronization between two chaotic patterns of stimulus and ISI sequence. The result implies that a new scheme of temporal coding at low firing rate regime can be achieved which exploits the preservation of nonlinear deterministic structures in stimulus.

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