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The Fisher matrix formalism has in recent times become the standard method for predicting the precision with which various cosmological parameters can be extracted from future data. This approach is fast, and generally returns accurate estimates for the parameter errors when the individual parameter likelihoods approximate a Gaussian distribution. However, where Gaussianity is not respected (du...

Numerical solutions of the generalized Burgers-Fisher equation are presented based on a polynomial-based differential quadrature method with minimal computational effort. To achieve this, a combination of a polynomial-based differential quadrature method in space and a third-order strong stability preserving Runge-Kutta scheme in time have been used. The proposed technique successfully worked t...

The Locally Linear Embedding (LLE) algorithm is an unsupervised nonlinear dimensionality-reduction method, which reports a low recognition rate in classification because it gives no consideration to the label information of sample distribution. In this paper, a classification method of supervised LLE (SLLE) based on Linear Discriminant Analysis (LDA) is proposed. First, samples are classified a...

The problem of learning with both labeled and unlabeled examples arises frequently in Hyperspectral image (HSI) classification. While marginal Fisher analysis is a supervised method, which cannot be directly applied for Semi-supervised classification. In this paper, we proposed a novel method, called semi-supervised marginal Fisher analysis (SSMFA), to process HSI of natural scenes, which uses ...

New models for the formation of disk galaxies are presented. I discuss the constraints on galaxy formation that follow from fitting the model to the near-infrared Tully-Fisher (TF) relation, with an emphasis on reproducing the small amount of scatter observed. Once the parameters that describe the supernova feedback are tuned to fit the slope of the observed TF relation, the model reproduces th...

We propose a tracking algorithm based on image classification involving online feature weighting. The algorithm uses automatically produced general Haar-like features through feature extraction and feature selection using an online-built object model, and combines Principal Component Analysis (PCA, a generative method) and Fisher ́s Discriminative Analysis (FDA, a discriminative method). That is...

In the paper we propose a one dimensional client specific fisher face representation for personal identity verification. This novel LDA approach contrasts with the conventional LDA representation which involves multiple shared fisher faces. The method provides two measures for authentication: a distance to the client template, and a distance to the mean of impostors. These two decision scores a...

Data compression ideas can be extended to assess the data quality across multiple sensors to manage the network of sensors to optimize the location accuracy subject to communication constraints. From an unconstrained-resources viewpoint it is desirable to use the complete set of deployed sensors; however, that generally results in an excessive data volume. We have previously presented here resu...

Longitudinal allele frequency data are becoming increasingly prevalent. Such samples permit statistical inference of the population genetics parameters that influence the fate of mutant variants. To infer these parameters by maximum likelihood, the mutant frequency is often assumed to evolve according to the Wright-Fisher model. For computational reasons, this discrete model is commonly approxi...