Maximum Standardized Cumulant Deconvolution of Non-Gaussian Linear Processes

Cumulant-based autocorrelation estimates of non-Gaussian linear processes

Maximum-likelihood blind deconvolution: non-white Bernoulli-Gaussian case

Bayesian deconvolution of Bernoulli-Gaussian processes

We present some Bayesian algorithms for the detection and estimation of Beruoulli-Gaussian processes, when just a filtered and noise-corrupted version of the original sequence is available. In a Bayesian framework, reconstruction is obtained from the posterior distribution of this sequence. Then, we conventionally define the likelihood of a Beruoulli~3aussian process and show that this prior de...

on the effect of linear & non-linear texts on students comprehension and recalling

چکیده ندارد.

On the unique representation of non-Gaussian multivariate linear processes

In contrast to the fact that Gaussian linear processes generally have nonunique moving-average representations, non-Gaussian univariate linear processes have been shown to admit essentially unique moving-average representation, under various regularity conditions. We extend the one-dimensional result to multivariate processes. Under various conditions on the intercomponent dependence structure ...