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Maximal avoidable sets of words(Algebraic Theory of Codes and Related Topics)

Maximal avoidable sets of words(Algebraic Theory of Codes and Related Topics)
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An Application of Set Theory to Coding Theory

Mathematics Magazine, 1989
"As high-speed electronic communication becomes commonplace, there is a tremendous need for better transmission schemes-ones that minimize the effect of inevitable transmission errors, ones that protect confidential or secret messages, ones that route messages most efficiently.
Noca Alon, Andy Liu
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Toward a Source Coding Theory for Sets

Data Compression Conference (DCC'06), 2006
The problem of communicating (unordered) sets, rather than (ordered) sequences is formulated. Elementary results in all major branches of source coding theory, including lossless coding, high-rate and low-rate quantization, and rate distortion theory are presented. In certain scenarios, rate savings of log n!
L.R. Varshney, V.K. Goyal
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Finding maximum independent sets in graphs arising from coding theory

Proceedings of the 2002 ACM symposium on Applied computing, 2002
New results are presented concerning binary correcting codes, such as deletion-correcting codes, transposition-correction codes, and codes for the Z-channel. These codes are important due to the possibility of packet loss and corruption on internet transmissions.
Sergiy Butenko, Panos Pardalos, Ivan Sergienko, Vladimir Shylo, Petro Stetsyuk   +4 more
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Probabilistic approach to attributes coding in the rough sets theory

Proceedings ICCI `92: Fourth International Conference on Computing and Information, 2003
Objects in an information system analyzed by the rough sets theory methods are characterized by attributes, which can take on a finite set of values only. In diagnostic experiments, condition attributes are usually treated as continuous variables, taking values from certain intervals.
A. Lenarcik, Z. Piasta, M. Masternak
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Application of coding theory to the construction of the Singer difference sets†

International Journal of Control, 1973
In this paper we give a new and simple construction for the cyclic [(q m − 1)/(q − 1), q m−1, q m−2(q− 1)]—difference sets (q = p γ is a prime power) using the methods of coding theory. The construction is such that, in the case q = 2, the 2-ranks of both the incidence matrix and its complementary matrix are easily determined.
HARRY T. HSU, JOHN E. OLSON
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Unknown Malicious Codes Detection Based on Rough Set Theory and Support Vector Machine

The 2006 IEEE International Joint Conference on Neural Network Proceedings, 2006
For detecting malicious codes, a classification method of support vector machine (SVM) based on rough set theory (RST) is proposed. The original sample data is preprocessed with the knowledge reduction algorithm of RST, and the redundant features and conflicting samples are eliminated from the working sample dataset to reduce space dimension of sample ...
null Boyun Zhang, null Jianping Yin, null Wensheng Tang, null Jinbo Hao, null Dingxing Zhang   +4 more
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Code Construction for Pliable Index Coding

International Symposium on Information Theory, 2019
A new variant of index coding problem termed as Pliable Index Coding Problem (PICOD) is formulated in [S. Brahma, C. Fragouli, "Pliable index coding", IEEE Transactions on Information Theory, vol. 61, no. 11, pp. 6192-6203, 2015]. In PICOD, we consider a
Shanuja Sasi, B. Rajan
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Sparse coding and rough set theory-based hybrid approach to the classificatory decomposition of cortical evoked potentials

Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02., 2002
This paper presents a novel approach to classification of decomposed cortical evoked potentials (EPs). The decomposition is based on learning of a sparse set of basis functions using an artificial neural network (ANN). The basis functions are generated according to a probabilistic model of the data.
G.M. Boratyn, T.G. Smolinski, M. Milanova, A. Wrobel   +3 more
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Code Profiling Analysis of Rough Set Theory on DSP and Embedded Processors for IoT Application

2020
Rough set theory is a powerful artificial intelligence based tool used for data analysis and mining inconsistent information systems. In the presence of inconsistent, incomplete, imprecise, or vague data, normal statistical based data analytic techniques lag behind. This paper discusses the code profiling for rough set theory on DSP and ARM processors.
Vanita Agarwal, Rajendrakumar A. Patil, Jyoti Adwani   +2 more
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