The Fisher matrix formalism is a method of error forecasting and the method has been widely used in cosmological data analysis because of its convenience and effectiveness. It is based on the second-order expansion of the logarithm of the likelihood function in the parameter space, and the estimated error contours are ellipsoids in the parameter space. With real-world data, the error contours a...

In this paper we study one-dimensional Fisher-Kolmogorov equation with density dependent non-linear diffusion. We choose the diffusion as a function of cell density such that it is high in highly cell populated areas and it is small in the regions of fewer cells. The Fisher equation with non-linear diffusion is known as modified Fisher equation. We study the travelling wave solution of modified...

In this paper, we present a novel two-stage metric learning algorithm. We first map each learning instance to a probability distribution by computing its similarities to a set of fixed anchor points. Then, we define the distance in the input data space as the Fisher information distance on the associated statistical manifold. This induces in the input data space a new family of distance metric ...

Face recognition is an active research work since its use is widespread in many applications. The proposed work is to develop a hybrid illumination pre-processing method for face recognition by combining two-dimensional Discrete Wavelet Transform (2D DWT) and Contrast Limited Adaptive Histogram Equalization (CLAHE). 2D DWT is applied on the original image and the LL sub-band of DWT coefficients...

A new theoretical solution to the Behrens-Fisher (BF) problem is developed using the maximum empirical likelihood method. The sampling properties of the empirical likelihood ratio (ELR) test for the BF problem are derived using Monte Carlo simulation for a wide range of situations. A comparison of the sizes and powers of the ELR test and the Welch-Aspin test is conducted for a special case of s...

Segmentation of brain from magnetic resonance (MR) images has important applications in neuroimaging, in particular it facilitates in extracting different brain tissues such as cerebrospinal fluids, white matter and gray matter. That helps in determining the volume of the tissues in three-dimensional brain MR images, which yields in analyzing many neural disorders such as epilepsy and Alzheimer...

Fisher kernels combine the powers of discriminative and generative classifiers by mapping the variable-length sequences to a new fixed length feature space, called the Fisher score space. The mapping is based on a single generative model and the classifier is intrinsically binary. We propose a strategy that applies a multiclass classification on each Fisher score space and combines the decision...