the infimum is with respect to all auxiliary random variables Z (which take values in a finite set 3) that satisfy: i) Y,Z conditiofally independent given X; ii) there exists a functionf: “Y x E +.%, such that E[D(X,f(Y,Z))] 5 d. Let Rx, y(d) be the rate-distortion function which results when the encoder

Distorted measures have been used in pricing of insurance contracts for a long time. This paper reviews properties of related acceptability functionals in risk management, called distortion functionals. These functionals may be characterized by being mixtures of average values-at-risk. We give a

A&r&-By defining mutual information as a maximum over an appropriate space, channel capacities can be defined as double maxima and rate-distortion functions as double minima. This approach yields valuable new insights regarding the computation of channel capacities and rate-distortion

The high-pressure phase transitions of silicon and gallium

Motivated by questions in lossy data compression and by theoretical considerations, this paper examines the problem of estimating the rate-distortion function of an unknown (not necessarily discretevalued) source from empirical data. The main focus is the behavior of the so-called “plug

Modular equations occur in number theory, but it is less known that such equations also occur in the study of deformation properties of quasiconformal mappings. The authors study two important plane quasiconformal distortion functions, obtaining monotonicity and convexity properties, and finding

matching cost function. Our implementation on a transputer network successfully achieves recognition of human faces and office objects from gray level camera images. The performance of the program is evaluated by a statistical analysis of recognition results from a portrait gallery comprising images of 87

Abstract — We develop rate-distortion theory in the Kolmogorov complexity setting. This is a theory of lossy compression of individual data objects, using the computable regularities of the data. I.

Abstract—Motivated by questions in lossy data compression and by theoretical considerations, the problem of estimating the rate-distortion function of an unknown (not necessarily discrete-valued) source from empirical data is examined. The focus is the behavior of the so-called “plug-in ” estimator

This work is concerned with calculating (Chapters III and IV) and bounding (Chapter V) rate distortion functions and with some of their properties (Chapter II). A review of the basic notions and results in the rate distortion theory is included in Chapter I. In Chapter II, we consider a memoryless