diplomsko delo
Gregor Kralj (Avtor), Arjana Žitnik (Mentor)

Povzetek

Paritetne kode z nizko gostoto

Ključne besede

kodi za popravljanje napak;paritetne kode z nizko gostoto;iterativni dekodirni algoritem z izročanjem sporočil;Gaussov kanal z belim šumom;računalništvo;univerzitetni študij;diplomske naloge;

Podatki

Jezik: Slovenski jezik
Leto izida:
Tipologija: 2.11 - Diplomsko delo
Organizacija: UL FRI - Fakulteta za računalništvo in informatiko
Založnik: [G. Kralj]
UDK: 004(043.2)
COBISS: 7671892 Povezava se bo odprla v novem oknu
Št. ogledov: 839
Št. prenosov: 241
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

Sekundarni jezik: Angleški jezik
Sekundarni naslov: [Low-density parity-check codes]
Sekundarni povzetek: Transmition of data over various communication systems is lossy, because of all the noise affecting the communication channel. One of the most useful ways to achieve reliable transmision are error correcting codes. Recently, low-density parity-check codes became very popular. These codes can come arbitrarily close to the Shannon limit and because of the technology development their coding and decoding algorithms are reasonably fast. In this graduation thesis, low density parity check (LDPC) codes are studied. The progressive edge growth (PEG) algorithm for generating such codes is presented and iterative decoding algorithm (SPA) is described. For the communication channel model, additive white Gaussian noise channel is used. In the last section of the thesis, efficiency of the presented decoding algorithm is examined for matrices of various dimensions, that were generated with algorithm PEG. The rate of bit errors or the number of iterations for correct decoding was counted for different levels of noise. Results show that in the tested cases, parity check codes of larger dimensions perform better than the parity check codes of lower dimensions.
Sekundarne ključne besede: error correcting codes;low-density parity-check codes;sum-product algorithm;additive white Gaussian noise;computer science;diploma;
Vrsta datoteke: application/pdf
Vrsta dela (COBISS): Diplomsko delo
Komentar na gradivo: Univerza v Ljubljani, Fakulteta za računalništvo in informatiko
Strani: 60 str.
ID: 23890621
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