Algebraic decoding of the (23,12,7) Golay code
IEEE Transactions on Information Theory
Fast, prime factor, discrete Fourier transform algorithms over GF(2m) for 8≤m≤10
Information Sciences: an International Journal
Algebraic decoding of the (32, 16, 8) quadratic residue code
IEEE Transactions on Information Theory
Decoding the Golay code with Venn diagrams
IEEE Transactions on Information Theory
Decoding the (47,24,11) quadratic residue code
IEEE Transactions on Information Theory
A decoding procedure for multiple-error-correcting cyclic codes
IEEE Transactions on Information Theory
Shift-register synthesis and BCH decoding
IEEE Transactions on Information Theory
A permutation decoding of the (24, 12, 8) Golay code (Corresp.)
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
A performance comparison of the binary quadratic residue codes with the 1/2-rate convolutional codes
IEEE Transactions on Information Theory
Use of Grobner bases to decode binary cyclic codes up to the true minimum distance
IEEE Transactions on Information Theory
The Leech lattice and the Golay code: bounded-distance decoding and multilevel constructions
IEEE Transactions on Information Theory
High speed decoding of the binary (47,24,11) quadratic residue code
Information Sciences: an International Journal
On the decoding of the (24,12,8) Golay code
Information Sciences: an International Journal
A cyclic weight algorithm of decoding the (47,24,11) quadratic residue code
Information Sciences: an International Journal
Hi-index | 0.07 |
A new decoding algorithm for the binary systematic (47,24,11) quadratic residue (QR) code, a code that allows error-correction of up to five errors, is presented in this paper. The key idea behind this decoding technique is based on the existence of a one-to-one mapping between the syndromes ''S"1'' and correctable error patterns. By looking up a pre-calculated table, this algorithm determines the locations of errors directly, thus requires no multiplication operations over a finite field. Moreover, the algorithm dramatically reduces the memory required by approximately 89%. A full search confirms that when five or less errors occur, this algorithm decodes these errors perfectly. Since the implementation is written in the C-language, it is readily adaptable for use in Digital Signal Processing (DSP) applications.