Single-photon avalanche diode (SPAD) is a promising photosensor because of its high sensitivity to optical signals in weak illuminance environment. Recently, it has drawn much attention from researchers in visible light communications (VLC). However, existing literature only deals with the simplified channel model, which only considers the effects of Poisson noise introduced by SPAD, but neglec...

This paper presents a new classification method for single subject’s motion. We employ R transform descriptor and Linear-chain Conditional Random Fields for representation and classification. What it solves is that global features are described and adjacent states are independent. We extract binary silhouettes from a video sequence and segment them into groups by cycle after building the backgr...

The multifactor version of copula models has the ability to generate complex correlation structure among defaults that is useful in fitting the base correlation skew. However, multifactor models have often been dismissed for their intractability. Even the semianalytical approach using Laplace transforms is computationally challenging, because although the model is tractable upon conditioning on...

A spatial lattice model for binary data is constructed from two spatial scales linked through conditional probabilities. A coarse grid of lattice locations is specified and all remaining locations (which we call the background) capture fine-scale spatial dependence. Binary data on the coarse grid are modelled with an autologistic distribution, conditional on the binary process on the background...

The computational cost of Gaussian process regression grows cubically with respect to the number of variables due to the inversion of the covariance matrix, which is impractical for data sets with more than a few thousand nodes. Furthermore, Gaussian processes lack the ability to represent conditional independence assertions between variables. We describe iterative proportional scaling for dire...