In this paper, we introduce a new class of bivariate distributions by compounding the bivariate generalized exponential and power-series distributions. This new class contains the bivariate generalized exponential-Poisson, bivariate generalized exponential-logarithmic, bivariate generalized exponential-binomial and bivariate generalized exponential-negative binomial distributions as specia...

A real square matrix is said to be essentially non-negative if all of its off-diagonal entries are non-negative. It has recently been shown that the exponential of an essentially non-negative matrix is determined entrywise to high relative accuracy by its entries up to a condition number intrinsic to the exponential function (Numer. Math., 110 (2008), pp. 393-403). Thus the smaller entries of t...

We say that Γ has uniform exponential growth if Ent Γ > 0. In [11], remarque 5.12, M. Gromov raised the question whether exponential growth always implies uniform exponential growth. The answer is negative, indeed, in [14] J.S. Wilson gave examples of finitely generated groups of exponential growth and non uniform exponential growth. Nevertheless, exponential growth implies uniform exponential ...

This paper introduces a new bivariate exponential distribution, called the Bivariate Affine-Linear Exponential distribution, to model moderately negative dependent data. The construction and characteristics of the proposed bivariate distribution are presented along with estimation procedures for the model parameters based on maximum likelihood and objective Bayesian analysis. We derive Jeffreys...

Non-negative matrix factorization (NMF) is a fundamental theory that has received much attention and widely used in image engineering, pattern recognition other fields. However, the classical NMF limitations such as only focusing on local information, sensitivity to noise small sample size (SSS) problems. Therefore, how develop improve performance robustness of algorithm worthy challenge. Based...

Graph regularized non-negative matrix factorization (GNMF) is widely used in feature extraction. In the process of dimensionality reduction, GNMF can retain internal manifold structure data by adding a regularizer to (NMF). Because Ga NMF implemented local preserving projections (LPP), there are small sample size problems (SSS). view above problems, new algorithm named robust exponential graph ...

Recently, a mechanical crack-based strain sensor with high sensitivity was proposed by producing free cracks via bending metal coated film with a known curvature. To further enhance sensitivity and controllability, a guided crack formation is needed. Herein, we demonstrate such a ultra-sensitive sensor based on the guided formation of straight mechanical cracks. The sensor has patterned holes o...