Spectral-clustering approach to Lagrangian vortex detection
نویسندگان
چکیده
منابع مشابه
Spectral-clustering approach to Lagrangian vortex detection.
One of the ubiquitous features of real-life turbulent flows is the existence and persistence of coherent vortices. Here we show that such coherent vortices can be extracted as clusters of Lagrangian trajectories. We carry out the clustering on a weighted graph, with the weights measuring pairwise distances of fluid trajectories in the extended phase space of positions and time. We then extract ...
متن کاملA Lagrangian approach to identifying vortex pinch-off.
A criterion for identifying vortex ring pinch-off based on the Lagrangian coherent structures (LCSs) in the flow is proposed and demonstrated for a piston-cylinder arrangement with a piston stroke to diameter (L/D) ratio of approximately 12. It is found that the appearance of a new disconnected LCS and the termination of the original LCS are indicative of the initiation of vortex pinch-off. The...
متن کاملA spectral clustering approach to speaker diarization
In this paper, we present a spectral clustering approach to explore the possibility of discovering structure from audio data. To apply the Ng-Jordan-Weiss (NJW) spectral clustering algorithm to speaker diarization, we propose some domain specific solutions to the open issues of this algorithm: choice of metric; selection of scaling parameter; estimation of the number of clusters. Then, a postpr...
متن کاملA Topological Approach to Spectral Clustering
We propose a clustering algorithm which, for input, takes data assumed to be sampled from a uniform distribution supported on a metric space X, and outputs a clustering of the data based on a topological estimate of the connected components of X. The algorithm works by choosing a weighted graph on the samples from a natural one-parameter family of graphs using an error based on the heat operato...
متن کاملDeveloping Additive Spectral Approach to Fuzzy Clustering
An additive spectral method for fuzzy clustering is presented. The method operates on a clustering model which is an extension of the spectral decomposition of a square matrix. The computation proceeds by extracting clusters one by one, which allows us to draw several stopping rules to the procedure. We experimentally test the performance of our method and show its competitiveness. In spite of ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Physical Review E
سال: 2016
ISSN: 2470-0045,2470-0053
DOI: 10.1103/physreve.93.063107