Over a perfect field k of characteristic p > 0, we construct a “Witt vector cohomology with compact supports” for separated k-schemes of finite type, extending (after tensorisation with Q) the classical theory for proper k-schemes. We define a canonical morphism from rigid cohomology with compact supports to Witt vector cohomology with compact supports, and we prove that it provides an identifi...

We perform a non-asymptotic analysis on the singular vector distribution under Gaussian noise. In particular, we provide sufficient conditions on a matrix for its first few singular vectors to have near normal distribution. Our result can be used to facilitate the error analysis in linear dimension reduction.

We present a new globally smooth parameterization method for surfaces of arbitrary topology. Our method does not require any prior partition into charts nor any cutting. The chart layout (i.e., the topology of the base complex) and the parameterization emerge simultaneously from a global numerical optimization process. Given two orthogonal piecewise linear vector fields, our method computes two...

Motion estimation in video sequences is a classical intensive computational task that is required for a wide range of applications. Many different methods have been proposed to reduce the computational complexity, but the achieved reduction is not enough to allow real time operation in a non-specialized hardware. In this paper an efficient selection of singular points for fast matching between ...

Epilepsy is a brain dysfunction that is characterized by recurrent seizures. An important analysing tool in detection of epilepsy is Electroencephalogram (EEG). The random and non-linear nature of the EEG imposes great difficulty in understanding the pathological process. In this work a multichannel epilepsy detection system is proposed. A feature vector is formed by performing Higher Order Sta...

The dynamics of the growth of linear disturbances to a chaotic basic state is analyzed in an asymptotic model of weakly nonlinear, baroclinic wave-mean interaction. In this model, an ordinary differential equation for the wave amplitude is coupled to a partial differential equation for the zonal flow correction. The leading Lyapunov vector is nearly parallel to the leading Floquet vector φ1 of ...

A novel stochastic technique is presented to directly model singular vectors and singular values of a multiple input multiple output (MIMO) channel. Thus the components modeled directly in the eigen domain can be adapted to exhibit realistic physical domain behavior when assembled. The model exploits natural paths of eigenmodes, such that a simple Doppler filter generator process can be used. F...

Learning to predict signiicant events from sequences of data with categorical features is an important problem in many application areas. We focus on events for system management, and formulate the problem of prediction as a classiication problem. We perform co-occurrence analysis of events by means of Singular Value Decomposition (SVD) of the examples constructed from the data. This process is...

This article presents a new subspace-based technique for reducing the noise of signals in time-series. In the proposed approach, the signal is initially represented as a data matrix. Then using Singular Value Decomposition (SVD), noisy data matrix is divided into signal subspace and noise subspace. In this subspace division, each derivative of the singular values with respect to rank order is u...

Neutrosophy is a new branch of philosophy that studies the origin, nature, and scope of neutralities, as well as their interactions with different ideational spectra. Aim of this article is to find the maximum and minimum solution of the fuzzy neutrosophic soft relational equations xA=b and Ax=b, where x and b are fuzzy neutrosophic soft vector and A is a fuzzy neutrosophic soft matrix. Wheneve...