Abstract Sample designs are typically developed to estimate summary statistics such as means, proportions and prevalences. Analytical outputs may also be a priority but there fewer methods results on how efficiently design samples for the fitting estimation of statistical models. This paper develops general approach determining efficient sampling probability-weighted maximum likelihood estimato...

When mechanical equipment breaks down under actual working conditions, time domain waveform is blurred by noise, which leads difficulty to acquire useful information. Aiming at this problem, an approach vibration signal analysis using quantum probability proposed process of signal. By use superior information processing properties theory, different states hidden in sampled points are expressed....

Wavelength assignment algorithm is one of the important components of routing and wavelength assignments problem in WDM networks. This problem helps in the minimization of the blocking probability of the network. In this paper we have reviewed the wavelength assignment problem and discussed the history of this problem with a good literature review. Depending upon the literature and history of t...

A new method to quantify changes in El Niño–Southern Oscillation (ENSO) variability is presented, using the overlap between probability distributions of the wavelet spectrum as measured by the wavelet probability index (WPI). Examples are provided using long integrations of three coupled climate models. When subsets of Niño-3.4 time series are compared, the width of the confidence interval on W...

| The wideband code-division multiple access (CDMA) concept (FMA2) developed in the European FRAMES AC090 project supports variable data rate transmission. The data rate can be altered by changing either the spreading factor or by using multiple spreading codes in parallel. In order to facilitate exible changing of data rate, orthogonal Walsh codes are used for channel separation, followed by s...

One of the key problems in non-parametric data analysis is to infer good models of probability distributions, assuming we are given as data a finite sample from that distribution. This problem is ill-posed for continuous distributions, even when they are low-dimensional: with finite data, there is no way to distinguish between (or exclude) distributions that are not regularized a priori, for ex...

In his world-famous paper of 1948, Shannon defined channel capacity as the ultimate rate at which information can be transmitted over a communication channel with an error probability that will vanish if we allow the blocklength to get infinitely large. While this result is of tremendous theoretical importance, the reality of practical systems looks quite different: no communication system will...