Journal ArticleDOI
Optimal causal coding - decoding problems
Jean Walrand,Pravin Varaiya +1 more
TLDR
It is shown that encoding is useless for a class of symmetric channels and channel feedback information is shown to be useful in general.Abstract:
The symbols produced by a finite Markov source are causally encoded so as to be transmitted through a noisy memoryless channel. The encoder is assumed to have channel feedback information and the decoder to be causal. The feedback information is shown to be useful in general. Separation results are derived and used to prove that encoding is useless for a class of symmetric channels.read more
Citations
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Journal ArticleDOI
Quantization
Robert M. Gray,David L. Neuhoff +1 more
TL;DR: The key to a successful quantization is the selection of an error criterion – such as entropy and signal-to-noise ratio – and the development of optimal quantizers for this criterion.
Journal ArticleDOI
Decentralized Stochastic Control with Partial History Sharing: A Common Information Approach
TL;DR: A general model of decentralized stochastic control called partial history sharing information structure is presented and the optimal control problem at the coordinator is shown to be a partially observable Markov decision process (POMDP) which is solved using techniques fromMarkov decision theory.
BookDOI
Information and Communication Technologies
Robert Szabo,Attila Vidács +1 more
TL;DR: It is a government funded initiative to significantly raise the quality and availability of resources for the computational processing of Portuguese.
Proceedings ArticleDOI
Information structures in optimal decentralized control
TL;DR: A comprehensive characterization of information structures in team decision problems and their impact on the tractability of team optimization and norm-optimal control for linear plants under information constraints is provided.
Journal ArticleDOI
Optimal Strategies for Communication and Remote Estimation With an Energy Harvesting Sensor
TL;DR: In this paper, the authors considered a distributed estimation problem with an energy harvesting sensor and a remote estimator, where the sensor observes the state of a discrete-time source which may be a finite state Markov chain or a multidimensional linear Gaussian system.
References
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Journal ArticleDOI
A mathematical theory of communication
TL;DR: This final installment of the paper considers the case where the signals or the messages or both are continuously variable, in contrast with the discrete nature assumed until now.
Book ChapterDOI
Economic comparability of information systems.
Jacob Marschak,Koichi Miyasawa +1 more
TL;DR: An information system is a set of potential messages to be received by the decision maker and its value depends not only on the statistical relation between messages and events but also on the payoff function.
Journal ArticleDOI
Sufficient statistics in the optimum control of stochastic systems
TL;DR: Only certain formal properties of the loss function will be required, they will be kept to a minimum, and their significance will be discussed as they are introduced.
Journal ArticleDOI
On the structure of real-time source coders
TL;DR: The outputs of a discrete time source with memory are to be encoded (“quantized” or “compressed”) into a sequence of discrete variables, from which a receiver must attempt to approximate some features of the source sequence.
Journal ArticleDOI
A note on the observation of a Markov source through a noisy channel (Corresp.)
TL;DR: A generalization of the simple noise process given by Drake is presented, and analogous results are derived for the optimality of several decoding schemes, including the singlet decoding rule and the data-independent decoding rule.