New Annex B - Use of data signal detection and silence insertion in voiceband data, and new Annex C on use of V.21 preamble for echo canceller control in a V.152 gateway

A team of researchers developed a technique, ACE, to improve the ability to study low-abundance proteins using mass cytometry.

When thinking about the concept of a “micro aggression”, what we’re really doing is subscribing to signal detection theory. What is the theory and how does it come into play when we’re dissecting the behaviors of others? In the first episode of this two-part conversation on Two Guys on Your Head, Dr. Art Markman and Dr. Bob Duke discuss...

We’ve covered what signal detection theory is, so how does it come up when we assign labels to behaviors that could be considered “micro aggressions”? Are there significant benefits to these labels? In the second episode of this two-part conversation on Two Guys on Your Head, Dr. Art Markman and Dr. Bob Duke continue their discussion on signal detection....

Clément Marteau, Theofanis Sapatinas.

Source: Statistics Surveys, Volume 9, 253--297.

Abstract:
We are concerned with minimax signal detection. In this setting, we discuss non-asymptotic and asymptotic approaches through a unified treatment. In particular, we consider a Gaussian sequence model that contains classical models as special cases, such as, direct, well-posed inverse and ill-posed inverse problems. Working with certain ellipsoids in the space of squared-summable sequences of real numbers, with a ball of positive radius removed, we compare the construction of lower and upper bounds for the minimax separation radius (non-asymptotic approach) and the minimax separation rate (asymptotic approach) that have been proposed in the literature. Some additional contributions, bringing to light links between non-asymptotic and asymptotic approaches to minimax signal, are also presented. An example of a mildly ill-posed inverse problem is used for illustrative purposes. In particular, it is shown that tools used to derive ‘asymptotic’ results can be exploited to draw ‘non-asymptotic’ conclusions, and vice-versa. In order to enhance our understanding of these two minimax signal detection paradigms, we bring into light hitherto unknown similarities and links between non-asymptotic and asymptotic approaches.