Our goal in writing this book has been to provide a comprehensive, mathematically rigorous,
but still accessible treatment of the interaction between information and control in multi …

We consider the generalized dirty-paper channel Y= X+ S+ N, E {X/sup 2/}/spl les/P/sub X/,
where N is not necessarily Gaussian, and the interference S is known causally or …

A rate-distortion-perception (RDP) tradeoff has recently been proposed by Blau and
Michaeli and also Matsumoto. Focusing on the case of perfect realism, which coincides with …

We consider lossy compression of an information source when the decoder has lossless
access to a correlated one. This setup, also known as the Wyner-Ziv problem, is a special …

This paper studies the optimization of observation channels (stochastic kernels) in partially
observed stochastic control problems. In particular, existence and continuity properties are …

To any discrete probability distribution P we can associate its entropy H (P)=-/spl
Sigma/p/sub i/ln p/sub i/and its index of coincidence IC (P)=/spl Sigma/p/sub i//sup 2/. The …

The principal goal of data compression (also known as source coding) is to replace data by
a compact representation in such a manner that from this representation the original data …

The nearest neighbor condition implies that when searching for a mean-square optimal fixed-
rate quantizer it is enough to consider the class of regular quantizers, ie, quantizers having …

Data originating from devices and sensors in Internet of Things scenarios can often be
modeled as sparse signals. In this paper, we provide new source compression schemes for …

Neural-network-based compressors have proven to be remarkably effective at compressing
sources, such as images, that are nominally high-dimensional but presumed to be …