The subject here is generalized (ie, non-Gaussian) noise models, and specifically their first-
order probability density functions (PDFs). Attention is focused primarily on the author's …

The paper considers interference in a wireless communication network caused by users that
share the same propagation medium. Under the assumption that the interfering users are …

We have some time ago noticed that finding a book dealing with topics in the advanced
theory and applications of signal detection is not quite an easy matter. This is contrasted with …

A locally optimal detection algorithm for random signals in dependent noise is derived and
applied to independent identically distributed complex-valued Gaussian mixture noise. The …

We introduce Noise Recycling, a method that enhances decoding performance of channels
subject to correlated noise without joint decoding. The method can be used with any …

The purpose of this paper is to extend the recent formulation of locally optimum Bayes (LOB)
detection in nonadditive non-Gaussian noise with independent sampling to the case where …

In most previously reported studies on locally optimum detection of signals, independent
observations have been assumed in various noise environments. The use of an …

Classical threshold detection theory for arbitrary noise and signals, based on independent
noise samples, ie, using only the first-order probability density of the noise, is generalized to …

A stationary first-order Markov transition density is constructed from the truncated version of
the first-and the second-order probability densities of the Class A noise model, where the …

The locally optimum Bayes theory of signal detection in additive non-Gaussian
noise/interference is extended to independent observations of the received data without the …