Compression Limits for Random Vectors with Linearly Parameterized Second-Order Statistics

Autoregressive Gaussian Random Vectors of First Order

Optimal Non-Parametric Prediction Intervals for Order Statistics with Random Sample Size

‎ In many experiments, such as biology and quality control problems, sample size cannot always be considered as a constant value. Therefore, the problem of predicting future data when the sample size is an integer-valued random variable can be an important issue. This paper describes the prediction problem of future order statistics based on upper and lower records. Two different cases for the ...

Second-order complex random vectors and normal distributions

We formulate as a deconvolution problem thecausalhoncausal non-Gaussian multichannel autoregressive (AR)parameter estimation problem. The super exponential aljporithmpresented in a recent paper by Shalvi and Weinstein is generalizedto the vector case. We present an adaptive implementation that isvery attractive since it is higher order statistics (HOS) based b u t doesno...

Monadic Second-order Logic for Parameterized Verification

Much work in automatic verification considers families of similar finite-state systems. But an often overlooked property is that sometimes a single finite-state system can be used to describe a parameterized, infinite family of systems. Thus verification of unbounded state spaces can take place by reduction to finite ones. The purpose of this article is to introduce Monadic Second-order Logic a...

Augmented second-order statistics of quaternion random signals

Second order statistics of quaternion random variables and signals are revisited in order to exploit the complete second order statistical information available. The conditions for Q-proper (second order circular) random processes are presented, and to cater for the non-vanishing pseudocovariance of such processes, the use of ı-E-k-covariances is investigated. Next, the augmented statistics and...