Signal Classification and parameter estimation of cyclostationary signal is an vital issue for various security applications like civil and military applications such as LTE, spectrum detection, and spectrum maintaining in cognitive radio systems. Cyclostationary signals is one, that exhibits a statistical property to categories whether the signal is belong to be a probabilistic approach or a d...

In some statistical process control applications, quality of a process or product can be characterized by a relationship between a response and one or more independent variables, which is typically referred to a profile. In this paper, polynomial profiles are considered to monitor processes in which there is a first order autoregressive relation between the error terms in each profile. A remedi...

The most widely used task functional magnetic resonance imaging (fMRI) analyses use parametric statistical methods that depend on a variety of assumptions. In this work, we use real resting-state data and a total of 3 million random task group analyses to compute empirical familywise error rates for the fMRI software packages SPM, FSL, and AFNI, as well as a nonparametric permutation method. Fo...

Human immunodeficiency virus (HIV) infection and the acquired immune deficiency syndrome (AIDS) exhibit variable patterns among the provinces of China. Knowledge of the geographical distribution of the HIV/AIDS epidemic is needed for the prevention and control of AIDS. Thus, the cumulative number of reported cases of HIV/AIDS from the period 1985-2013, and the incidence rate of AIDS in 2013 wer...

Ecological variables often fluctuate synchronously over wide geographical areas, a phenomenon known as spatial autocorrelation or spatial synchrony. Development of statistical approaches designed to test for spatial autocorrelation combined with the increasing accessibility of long-term, large-scale ecological datasets are now making it possible to document the patterns and understand the cause...

In this paper, a new approach for linear prediction (LP) analysis is proposed. This approach makes the assumption that the speech signal is cyclostationary and uses cyclic autocorrelation function for computing LP parameters. Since the cyclic autocorrelation function of a stationary random signal is zero, independent of its statistical description, this analysis is robust to additive noise, whi...

We present a parametric statistical characterization of texture images in the context of an overcomplete complex wavelet frame. The characterization consists of the local autocorrelation of the coefficients in each subband, the local autocorrelation of the cofficent magnitudes, and the crosscorrelation of coefficient magnitudes at all orientations and adjacent spatial scales. We develop an effi...

By the method of recurrence relations, the time evolution in a local variable in a harmonic chain is obtained. In particular, the autocorrelation function is obtained analytically. Using this result, a number of important dynamical quantities are obtained, including the memory function of the generalized Langevin equation. Also studied are the ergodicity and chaos in a local dynamical variable.