相关论文: Comparison of subclustering frequency determined f…

We show the potential for classifying images of mixtures of aggregate, based themselves on varying, albeit well-defined, sizes and shapes, in order to provide a far more effective approach compared to the classification of individual sizes…

In this paper, we carry out a comparative study of the efficacy of wavelets belonging to Daubechies and Coiflet family in achieving image segmentation through a fast statistical algorithm.The fact that wavelets belonging to Daubechies…

The method of element analysis is proposed here as an alternative to traditional wavelet-based approaches to analyzing perturbations in financial signals by scale. In this method, the processes that generate oscillations in financial…

Mahdavi et al. find that the degree of agreement between weak lensing and X-ray mass measurements is a function of cluster radius. Numerical simulations also point out that X-ray mass proxies do not work equally well at all radii. The…

Consider a panel data setting where repeated observations on individuals are available. Often it is reasonable to assume that there exist groups of individuals that share similar effects of observed characteristics, but the grouping is…

We compare the predicted Abell/ACO cluster density and velocity fields, using linear theory, with that based on the MarkIII catalog and the POTENT machinery within 7000 km/sec. Both density & velocity fields are in good qualitative…

The distribution of Abell clusters of galaxies is analysed to study the regularity of the supercluster-void network. A new geometric method sensitive to the regularity of the location of clusters is applied. We find that the…

We study the evolution of satellite debris to establish the most suitable space to identify past merger events. We confirm that the space of orbital frequencies is very promising in this respect. In frequency space individual streams can be…

We study generalized density-based clustering in which sharply defined clusters such as clusters on lower-dimensional manifolds are allowed. We show that accurate clustering is possible even in high dimensions. We propose two data-based…

In a recent work Manimaran et al. [Manimaran et al., Phys. Rev. E 72, 046120 (2005)] propose to use multiresolution Daubechies (DB) wavelets to (detrend) remove the low frequency trends and subsequently to quantify the multifractal…

In this paper we propose a unified framework to simultaneously discover the number of clusters and group the data points into them using subspace clustering. Real data distributed in a high-dimensional space can be disentangled into a union…

Deep learning models extract, before a final classification layer, features or patterns which are key for their unprecedented advantageous performance. However, the process of complex nonlinear feature extraction is not well understood, a…

We study the morphology of a set of superclusters drawn from the SDSS DR7. We calculate the luminosity density field to determine superclusters from a flux- limited sample of galaxies from SDSS DR7, and select superclusters with 300 and…

Spectral clustering requires the time-consuming decomposition of the Laplacian matrix of the similarity graph, thus limiting its applicability to large datasets. To improve the efficiency of spectral clustering, a top-down approach was…

Motivated by applications in high-dimensional data analysis where strong signals often stand out easily and weak ones may be indistinguishable from the noise, we develop a statistical framework to provide a novel categorization of the data…

A simple formula for the scattering of wave packets from a square well at long times is derived. The expression shows that the phenomenon of wave packet diffraction in space and time exists in three dimensions also. An experiment for the…

We discuss lensing properties of the nearby cluster Abell 2152. Recent work shows that Abell 2152 is actually the projection of two different clusters, one of which is a Hercules supercluster member at z=0.043, while the other is more than…

Many materials, processes, and structures in science and engineering have important features at multiple scales of time and/or space; examples include biological tissues, active matter, oceans, networks, and images. Explicitly extracting,…

In this paper we analyze two-dimensional wavelet reconstructions from Fourier samples within the framework of generalized sampling. For this, we consider both separable compactly-supported wavelets and boundary wavelets. We prove that the…

Clustering has received much attention in Statistics and Machine learning with the aim of developing statistical models and autonomous algorithms which are capable of acquiring information from raw data in order to perform exploratory…