Clustering behaviors in networks of integrate-and-fire oscillators

Clustering behavior is studied in a model of integrate-and-fire oscillators with excitatory pulse coupling. When considering a population of identical oscillators, the main result is a proof of global convergence to a phase-locked clustered behavior. The robustness of this clustering behavior is then investigated in a population of nonidentical oscillators by studying the transition from total clustering to the absence of clustering as the group coherence decreases. A robust intermediate situation of partial clustering, characterized by few oscillators traveling among nearly phase-locked clusters, is of particular interest. The analysis complements earlier studies of synchronization in a closely related model. © 2008 American Institute of Physics.

Determinantal Clustering Processes - A Nonparametric Bayesian Approach to Kernel Based Semi-Supervised Clustering

Semi-supervised clustering is the task of clustering data points into clusters where only a fraction of the points are labelled. The true number of clusters in the data is often unknown and most models require this parameter as an input. Dirichlet process mixture models are appealing as they can infer the number of clusters from the data. However, these models do not deal with high dimensional data well and can encounter difficulties in inference. We present a novel nonparameteric Bayesian kernel based method to cluster data points without the need to prespecify the number of clusters or to model complicated densities from which data points are assumed to be generated from. The key insight is to use determinants of submatrices of a kernel matrix as a measure of how close together a set of points are. We explore some theoretical properties of the model and derive a natural Gibbs based algorithm with MCMC hyperparameter learning. The model is implemented on a variety of synthetic and real world data sets.

The influence of nitrogen clustering effect on optical transitions in GaInNAs/GaAs quantum wells

Photoluminescence (PL) spectra of GaInNAs/GaAs multiple quantum wells and GaInNAs epilayers grown on GaAs substrate show an apparent "S-shape" temperature-dependence of the of dominant luminescence peak. At low temperature and weak excitation conditions, a PL peak related to nitrogen cluster-induced bound states can be well resolved in the PL spectra. It displays a remarkable red shift of up to 60 meV and is thermally quenched below 100 K with increasing temperature, being attributed to N-cluster induced bound states. The indium incorporation exhibits significant effect on the cluster formation. The rapid thermal annealing treatment at 750 C can essentially remove the bound states-induced peak.

missing data imputation: a fuzzy k-means clustering algorithm over sliding window

Tianjin University of Technology