In Lagrangian dynamics, the detection of coherent clusters can help understand organization transport by identifying regions with trajectory patterns. Many clustering algorithms, however, rely on user-input parameters, requiring a priori knowledge about flow and making outcome subjective. Building conventional spectral method Hadjighasem et al. (2016), new optimized-parameter approach is develo...

We study some properties of the $SU(1,1)$ Perelomov number coherent states. The Schr\"odinger's uncertainty relationship is evaluated for a position and momentum-like operators (constructed from Lie algebra generators) in these It shown that this minimized standard obtain time evolution states by supposing Hamiltonian proportional to third generator $K_0$ $su(1,1)$ algebra. Analogous results $S...

With steadily increasing interest in enhancing large power systems’ transient stability, generator coherency identification has become critical for the dynamic equivalents, controlled-islanding, and wide-area control of these systems. This paper presents an approach based on two classical powerful techniques. The proposed method comprises slow followed by time-domain-based simulation stability ...

Synthetic graph generators facilitate research in graph algorithms and processing systems by providing access to data, for instance, graphs resembling social networks, while circumventing privacy and security concerns. Nevertheless, their practical value lies in their ability to capture important metrics of real graphs, such as degree distribution and clustering properties. Graph generators mus...

Recently one of us proposed a new formalism for modeling electromagnetic wave transformations for coherent communication using a real, four-vector description instead of the conventionally used Jones calculus or the Mueller matrices. The four-vector can then handle all superpositions of two orthogonal polarization basis and two orthogonal time bases (e.g., the inphase and quadrature phase). In ...

A novel clustering method mslng an artificial neural network (ANN) is presented to identify the coherent gekcrators for dynamic equivabnts of power systems. Flrst, a new fFpqueRcy measure ie dexlsad to Sndhte the degree of coherency rmong syaSem gemratom. Incarprating with $he frequency measure, a ncural network impkmearP;tion of the K-means algsrithni is then proposed to identify clusters of c...

In this work we describe a novel statistical video representation and modeling scheme. Unsupervised clustering via Gaussian mixture modeling extracts coherent spacetime regions in feature space, and corresponding coherent segments (video-regions) in the video content. A key feature of the system is the analysis of video input as a single entity as opposed to a sequence of separate frames. Space...