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Journal ArticleDOI

The theory of information and coding: A mathematical framework for communication

G. Longo
- Vol. 67, Iss: 10, pp 1467-1468
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TLDR
The stochastic integral with respect to processes with values in a reflexive Banach space, Theor.
Abstract
14. M. Metivier, The stochastic integral with respect to processes with values in a reflexive Banach space, Theor. Probability 19 (1974), 758-787. 15. M. Metivier and G. Pistone, Une formule d'isométrie pour r intégrale stochastique Hilbertienne et équations d'évolution linéaires stochastiques, Z. Wahrscheinlicnkeitstheorie und Verw. Gebiete 33 (1975), 1-18. 16. P. A. Meyer, A decomposition theorem for supermartingales, Illinois J. Math. 6 (1962), 193-205. 17. , Intégrales stochastiques. IV, Lecture Notes in Math., vol. 39, Springer-Verlag, Berlin and New York, 1967, pp. 142-162. 18. , Un cours sur les intégrales stochastiques, Lecture Notes in Math., vol. 511, Springer-Verlag, Berlin and New York, 1976, pp. 245-400. 19. , Intégrales Hilbertiennes, Lecture Notes in Math., vol. 581, Springer-Verlag, Berlin and New York, 1977, pp. 446-461. 20. R. E. A. C. Paley, N. Wiener and A. Zygmund, Notes on random functions, Math. Z. 37 (1933), 647-668. 21. J. Pellaumail, Sur lintégrale stochastique et la décomposition de Doob-Meyer, Asterique 9 (1973), 1-125. 22. P. E. Protter, Markov solutions of stochastic differential equations, TL Wahrscheinlichkeitstheorie und Verw. Gebiete 41 (1977), 39-58. 23. , A comparison of stochastic integrals, Ann. Probability (to appear). 24. R. L. Stratonovich, A new representation for stochastic integrals and equations, SIAM. J. Control 4 (1966), 362-371. 25. N. Wiener, Differential-space, J. Math, and Physics 2 (1923), 131-174.

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Partitions and Objective Indefiniteness in Quantum Mechanics

TL;DR: In this paper, the authors show how the mathematics of set partitions can be transported in a natural way to complex vector spaces where it yields the mathematical machinery of quantum mechanics, and then the machinery of QM can be transferred the other way down to set-like vector spaces over ℤ₂ yielding a rather fulsome "toy" or pedagogical model of "quantum mechanics over sets."
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The Quantum Logic of Direct-Sum Decompositions

TL;DR: In this article, the quantum logic of direct-sum decompositions of a finite-dimensional vector space is studied in the context of quantum mechanics over sets (QM/Sets).
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Quantum Mechanics Over Sets

TL;DR: In this article, a theory of quantum mechanics over sets is proposed, which is based on the notion of "objective indefiniteness", a program that grew out the recent development of the logic of partitions mathematically dual to the usual Boolean logic of subsets.
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The capacity-cost function of discrete additive noise channels with and without feedback

TL;DR: It is shown that for a particular feedback encoding strategy and a class of Markov noise sources, the lower bound to C/sub FB/(/spl beta/) is strictly greater than C( /spl beta/), demonstrating that feedback can increase the capacity-cost function of discrete channels with memory.
References
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Book

Elements of information theory

TL;DR: The author examines the role of entropy, inequality, and randomness in the design of codes and the construction of codes in the rapidly changing environment.
Journal ArticleDOI

Good error-correcting codes based on very sparse matrices

TL;DR: It is proved that sequences of codes exist which, when optimally decoded, achieve information rates up to the Shannon limit, and experimental results for binary-symmetric channels and Gaussian channels demonstrate that practical performance substantially better than that of standard convolutional and concatenated codes can be achieved.
Journal ArticleDOI

Vector quantization in speech coding

TL;DR: This tutorial review presents the basic concepts employed in vector quantization and gives a realistic assessment of its benefits and costs when compared to scalar quantization, and focuses primarily on the coding of speech signals and parameters.
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Finding the Number of Clusters in a Dataset

TL;DR: A simple, yet powerful nonparametric method for choosing the number of clusters based on distortion, a quantity that measures the average distance, per dimension, between each observation and its closest cluster center, is developed.
Journal ArticleDOI

On channel capacity per unit cost

TL;DR: It is shown that, if the input alphabet contains a zero-cost symbol, then the capacity per unit cost admits a simple expression as the maximum normalized divergence between two conditional output distributions.