6,890 research outputs found
A Robust Method for Detecting Interdependences: Application to Intracranially Recorded EEG
We present a measure for characterizing statistical relationships between two
time sequences. In contrast to commonly used measures like cross-correlations,
coherence and mutual information, the proposed measure is non-symmetric and
provides information about the direction of interdependence. It is closely
related to recent attempts to detect generalized synchronization. However, we
do not assume a strict functional relationship between the two time sequences
and try to define the measure so as to be robust against noise, and to detect
also weak interdependences. We apply our measure to intracranially recorded
electroencephalograms of patients suffering from severe epilepsies.Comment: 29 pages, 5 figures, paper accepted for publication in Physica
Invariant template matching in systems with spatiotemporal coding: a vote for instability
We consider the design of a pattern recognition that matches templates to
images, both of which are spatially sampled and encoded as temporal sequences.
The image is subject to a combination of various perturbations. These include
ones that can be modeled as parameterized uncertainties such as image blur,
luminance, translation, and rotation as well as unmodeled ones. Biological and
neural systems require that these perturbations be processed through a minimal
number of channels by simple adaptation mechanisms. We found that the most
suitable mathematical framework to meet this requirement is that of weakly
attracting sets. This framework provides us with a normative and unifying
solution to the pattern recognition problem. We analyze the consequences of its
explicit implementation in neural systems. Several properties inherent to the
systems designed in accordance with our normative mathematical argument
coincide with known empirical facts. This is illustrated in mental rotation,
visual search and blur/intensity adaptation. We demonstrate how our results can
be applied to a range of practical problems in template matching and pattern
recognition.Comment: 52 pages, 12 figure
Protein Pattern Formation
Protein pattern formation is essential for the spatial organization of many
intracellular processes like cell division, flagellum positioning, and
chemotaxis. A prominent example of intracellular patterns are the oscillatory
pole-to-pole oscillations of Min proteins in \textit{E. coli} whose biological
function is to ensure precise cell division. Cell polarization, a prerequisite
for processes such as stem cell differentiation and cell polarity in yeast, is
also mediated by a diffusion-reaction process. More generally, these functional
modules of cells serve as model systems for self-organization, one of the core
principles of life. Under which conditions spatio-temporal patterns emerge, and
how these patterns are regulated by biochemical and geometrical factors are
major aspects of current research. Here we review recent theoretical and
experimental advances in the field of intracellular pattern formation, focusing
on general design principles and fundamental physical mechanisms.Comment: 17 pages, 14 figures, review articl
Progress in aeroelastic optimization - Analytical versus numerical approaches
Mathematical and structural analysis for optimal control of aeroelasticity in unswept wing
Dynamics of vorticity
Remarks are made about the status of research on the role of vorticity in fluid dynamics and some unsolved problems of current interest are described
Structural Identification and Damage Identification Using Output-Only Vibration Measurements
This dissertation studied the structural identification and damage detection of civil engineering structures. Several issues regarding structural health monitoring were addressed.
The data-driven subspace identification algorithm was investigated for modal identification of bridges using output-only data. This algorithm was tested through a numerical truss bridge with abrupt damage as well as a real concrete highway bridge with actual measurements. Stabilization diagrams were used to analyze the identified results and determine the modal characteristics. The identification results showed that this identification method is quite effective and accurate.
The influence of temperature fluctuation on the frequencies of a highway concrete bridge was investigated using ambient vibration data over a one-year period of a highway bridge under health monitoring. The data were fitted by nonlinear and linear regression models, which were then analyzed.
The substructure identification by using an adaptive Kalman filter was investigated by applying numerical studies of a shear building, a frame structure, and a truss structure. The stiffness and damping were identified successfully from limited acceleration responses, while the abrupt damages were identified as well. Wavelet analysis was also proposed for damage detection of substructures, and was shown to be able to approximately locate such damages.
Delamination detection of concrete slabs by modal identification from the output-only data was proposed and carried out through numerical studies and experimental modal testing. It was concluded that the changes in modal characteristics can indicate the presence and severity of delamination. Finite element models of concrete decks with different delamination sizes and locations were established and proven to be reasonable.
Pounding identification can provide useful early warning information regarding the potential damage of structures. This thesis proposed to use wavelet scalograms of dynamic response to identify the occurrence of pounding. Its applications in a numerical example as well as shaking table tests of a bridge showed that the scalograms can detect the occurrence of pounding very well.
These studies are very useful for vibration-based structural health monitoring
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