Improved matrix CFAR detector based on K-L divergence and divergence mean}{Improved matrix CFAR detector based on K-L divergence and divergence mean

Dating divergence of Polystigma and other Sordariomycetes

Studies on the evolutionary history of ascomycetes in terms of time scale will help to understand historical patterns that shape their biodiversity. Until now most of dating studies of ascomycetes have focused on major events in fungal evolution but not on divergence events within smaller groups of fungi e.g. within Sordariomycetes. We used molecular dating to estimate the time of separation of...

Model Confidence Set Based on Kullback-Leibler Divergence Distance

Consider the problem of estimating true density, h(.) based upon a random sample X1,…, Xn. In general, h(.)is approximated using an appropriate in some sense, see below) model fƟ(x). This article using Vuong's (1989) test along with a collection of k(> 2) non-nested models constructs a set of appropriate models, say model confidence set, for unknown model h(.).Application of such confide...

On Mean Divergence Measures

Abstract. Arithmetic, geometric and harmonic means are the three classical means famous in the literature. Another mean such as square-root mean is also known. In this paper, we have constructed divergence measures based on nonnegative differences among these means, and established an interesting inequality by use of properties of Csiszár’s f-divergence. An improvement over this inequality is a...

Projective Nonnegative Matrix Factorization based on α-Divergence

The well-known Nonnegative Matrix Factorization (NMF) method can be provided with more flexibility by generalizing the non-normalized Kullback-Leibler divergence to αdivergences. However, the resulting α-NMF method can only achieve mediocre sparsity for the factorizing matrices. We have earlier proposed a variant of NMF, called Projective NMF (PNMF) that has been shown to have superior sparsity...

Divergence measures based on Tinfinity