Titlebook: Coding Theory; Jacobus H. Lint Book 1973Latest edition Springer-Verlag Berlin Heidelberg 1973 Finite.algebra.coding.coding theory.error-co

渐强

J.-M. Jaquet,E. Davaud,F. Rapin,J.-P. Vernet the theory of communication. In mentioning communication we think of many different things e.g. human speech, telephone conversations, storage devices like magnetic tape units for computers, high frequency radio, space communication links (e.g. telemetry systems in satellites), digital communicatio

Antigen

W. A. Poplawski,J. Piorewicz,M. R. Gourlayr of a prime, q = p.. In this case we can identify these alphabets with the elements of GF(q). We are going to construct ., i.e. codes in which all code words have the same length n which is called the . or ..

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Nani G. Bhowmik,J. Rodger Adamsls with coefficients in GF(q), i.e. (GF(q)[x],+, ). Let S be the principal ideal in R generated by the polynomial x.-1, i.e. S := (({x.-1}),+, ). R/S is the residue class ring R mod S, i.e. (GF(q)[x] mod ({x.-1},+, ). The elements of this ring can be represented by polynomials of degree < n with coe

maverick

Wilbert Lick,James Lick,C. Kirk Zieglercodes qm 1 were defined as follows: Let H be the m by n := . matrix consisting of all the different nonzero columns with elements from GF(q) such that the first nonzero entry in each column is 1. Since no linear combination of two columns can be . we see that H is the parity check matrix of a linear

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Introduction, the theory of communication. In mentioning communication we think of many different things e.g. human speech, telephone conversations, storage devices like magnetic tape units for computers, high frequency radio, space communication links (e.g. telemetry systems in satellites), digital communicatio

CLAN

Herd-Immunity

ALOFT

Perfect codes,codes qm 1 were defined as follows: Let H be the m by n := . matrix consisting of all the different nonzero columns with elements from GF(q) such that the first nonzero entry in each column is 1. Since no linear combination of two columns can be . we see that H is the parity check matrix of a linear

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