Vector autoregressive stochastic models are proposed for the synthesis of multiple Rayleigh fading processes with specified autocorrelation and cross-correlation functions. This capability is desirable, for example, to permit realistic performance assessments of space-time modem designs by enabling the simulation of space-time-selective mobile radio channel models. The utility of the simulation...

-This paper proposes a method for line matching based on invariance of feature points. Firstly, feature points are roughly matched by Normalized Cross Correlation (NNC) and Average of Square Difference (ASD). Additionally, feature points obtained from the two views are grouped into matched point pairs. Finally, curve segments between matched point pairs are matched by dynamic programming algori...

In order to meet the requirements of long range obstacle measurement of tower crane safety warning system and accurately estimate time of flight (TOF), an ultrasonic long range measurement system is designed and a mathematical model of echo envelope is established in this paper. Experimental data of long range obstacle measurement were collected and analyzed by using traditional threshold metho...

The product-moment correlation coefficient is often viewed as a natural measure of dependence. However, this equivalence applies only in the context of elliptical distributions, most commonly the multivariate gaussian, where linear correlation indeed sufficiently describes the underlying dependence structure. Should the true probability distributions deviate from those with elliptical contours,...

Within the semiparametric framework introduced by Pendakur (1999) we introduce a new loss function to estimate equivalence scales. This loss function uses all available information from the total expenditures of both the reference and nonreference households and as such it produces more reliable estimates. We also use the correlation coefficient to directly test the hypothesis of shape invarian...

Doctors’ survival predictions for terminally ill patients have been shown to be inaccurate and there has been an argument for less guesswork and more use of carefully constructed statistical indices. As statisticians, the authors are less confident in the predictive value of statistical models and indices for individual survival times. This paper discusses and illustrates a variety of measures ...

Spatial lag dependence in a regression model is similar to the inclusion of a serially autoregressive term for the dependent variable in time-series context. However, unlike in the time series model, the implied covariance structure matrix from the spatial autoregressive model can have a very counterintuitive and improbable structure. A single value of spatial auto correlation parameter can imp...

Encoding temporal information from the recent past as spatially distributed activations is essential in order for the entire recent past to be simultaneously accessible. Any biological or synthetic agent that relies on the past to predict/plan the future, would be endowed with such a spatially distributed temporal memory. Simplistically, we would expect that resource limitations would demand th...

Understanding and quantifying dependence is at the core of all modelling efforts in financial econometrics. The linear correlation coefficient, which is the far most used measure to test dependence in the financial community and also elsewhere, is only a measure of linear dependence. This means that it is a meaningful measure of dependence if asset returns are well represented by an elliptical ...

Remote, automated cognitive impairment (CI) diagnosis has the potential to facilitate care for the elderly. Speech is easily collected over the phone and already some common cognitive tests are administered remotely, resulting in regular audio data collections. Speech-based CI diagnosis leveraging existing audio is therefore an attractive approach for remote elderly cognitive health monitoring....