Aliazam Abbasfar: Turbo-like Codes : Design for High Speed Decoding - nieuw boek
ISBN: 9781402063916
The common property among turbo-like code is that they consist of very simple constituent codes that are connected to each other with random or pseudorandom interleavers.The crucial novel… Meer...
The common property among turbo-like code is that they consist of very simple constituent codes that are connected to each other with random or pseudorandom interleavers.The crucial novelty in these codes is the iterative decoding.This means that the constituent codes are decoded separately, which is ef?cient and practically feasible since they are very simple codes.Then, they pass new information to each other in a course of a few iterations.It has been shown that iterative decoding is a generalization of the well-known probability or belief propagation algorithm.The belief propagation algorithm that has been essential for development of new ideas throughout this work is described in the context of coding.The basic theorems for this algorithm are explained and proven in the following paragraphs.Thisis then followed by a description of the computational algorithm.The probability propagation algorithm is proven in c- junctionwithatree-structuredgraph-graphswithoutanycycle.Infact,thegraphical representation of any problem solved by this algorithm is the centerpiece of the algorithm.The generalization of the algorithm for graphs with cycles is presented later on.Representation of codes on graph is the next step towards characterization of the iterative decoding as an example of the probability propagation algorithm.The graph representations are presented for a few codes that are commonly used in turbo-like codes.; PDF; Reference > Research & information: general > Coding theory & cryptology, Springer Netherlands<
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The common property among turbo-like code is that they consist of very simple constituent codes that are connected to each other with random or pseudorandom interleavers. The crucial nove… Meer...
The common property among turbo-like code is that they consist of very simple constituent codes that are connected to each other with random or pseudorandom interleavers. The crucial novelty in these codes is the iterative decoding. This means that the constituent codes are decoded separately, which is ef?cient and practically feasible since they are very simple codes. Then, they pass new information to each other in a course of a few iterations. It has been shown that iterative decoding is a generalization of the well-known probability or belief propagation algorithm. The belief propagation algorithm that has been essential for development of new ideas throughout this work is described in the context of coding. The basic theorems for this algorithm are explained and proven in the following paragraphs. Thisis then followed by a description of the computational algorithm. The probability propagation algorithm is proven in c- junctionwithatree-structuredgraphâ??graphswithoutanycycle.Infact,thegraphical representation of any problem solved by this algorithm is the centerpiece of the algorithm. The generalization of the algorithm for graphs with cycles is presented later on. Representation of codes on graph is the next step towards characterization of the iterative decoding as an example of the probability propagation algorithm. The graph representations are presented for a few codes that are commonly used in turbo-like codes. Books > Engineering eBook, Springer Shop<
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The common property among turbo-like code is that they consist of very simple constituent codes that are connected to each other with random or pseudorandom interleavers. The crucial nove… Meer...
The common property among turbo-like code is that they consist of very simple constituent codes that are connected to each other with random or pseudorandom interleavers. The crucial novelty in these codes is the iterative decoding. This means that the constituent codes are decoded separately, which is ef?cient and practically feasible since they are very simple codes. Then, they pass new information to each other in a course of a few iterations. It has been shown that iterative decoding is a generalization of the well-known probability or belief propagation algorithm. The belief propagation algorithm that has been essential for development of new ideas throughout this work is described in the context of coding. The basic theorems for this algorithm are explained and proven in the following paragraphs. Thisis then followed by a description of the computational algorithm. The probability propagation algorithm is proven in c- junctionwithatree-structuredgraph–graphswithoutanycycle.Infact,thegraphical representation of any problem solved by this algorithm is the centerpiece of the algorithm. The generalization of the algorithm for graphs with cycles is presented later on. Representation of codes on graph is the next step towards characterization of the iterative decoding as an example of the probability propagation algorithm. The graph representations are presented for a few codes that are commonly used in turbo-like codes. Books > Engineering eBook, Springer Shop<
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new in stock. Verzendingskosten:zzgl. Versandkosten., exclusief verzendingskosten Details...
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Turbo-like Codes : Design for High Speed Decoding - nieuw boek
ISBN: 9781402063916
The common property among turbo-like code is that they consist of very simple constituent codes that are connected to each other with random or pseudorandom interleavers.The crucial novel… Meer...
The common property among turbo-like code is that they consist of very simple constituent codes that are connected to each other with random or pseudorandom interleavers.The crucial novelty in these codes is the iterative decoding.This means that the constituent codes are decoded separately, which is ef?cient and practically feasible since they are very simple codes.Then, they pass new information to each other in a course of a few iterations.It has been shown that iterative decoding is a generalization of the well-known probability or belief propagation algorithm.The belief propagation algorithm that has been essential for development of new ideas throughout this work is described in the context of coding.The basic theorems for this algorithm are explained and proven in the following paragraphs.Thisis then followed by a description of the computational algorithm.The probability propagation algorithm is proven in c- junctionwithatree-structuredgraph-graphswithoutanycycle.Infact,thegraphical representation of any problem solved by this algorithm is the centerpiece of the algorithm.The generalization of the algorithm for graphs with cycles is presented later on.Representation of codes on graph is the next step towards characterization of the iterative decoding as an example of the probability propagation algorithm.The graph representations are presented for a few codes that are commonly used in turbo-like codes.; PDF; Reference > Research & information: general > Coding theory & cryptology, Springer Netherlands<
No. 9781402063916. Verzendingskosten:Instock, Despatched same working day before 3pm, zzgl. Versandkosten., exclusief verzendingskosten
The common property among turbo-like code is that they consist of very simple constituent codes that are connected to each other with random or pseudorandom interleavers. The crucial nove… Meer...
The common property among turbo-like code is that they consist of very simple constituent codes that are connected to each other with random or pseudorandom interleavers. The crucial novelty in these codes is the iterative decoding. This means that the constituent codes are decoded separately, which is ef?cient and practically feasible since they are very simple codes. Then, they pass new information to each other in a course of a few iterations. It has been shown that iterative decoding is a generalization of the well-known probability or belief propagation algorithm. The belief propagation algorithm that has been essential for development of new ideas throughout this work is described in the context of coding. The basic theorems for this algorithm are explained and proven in the following paragraphs. Thisis then followed by a description of the computational algorithm. The probability propagation algorithm is proven in c- junctionwithatree-structuredgraphâ??graphswithoutanycycle.Infact,thegraphical representation of any problem solved by this algorithm is the centerpiece of the algorithm. The generalization of the algorithm for graphs with cycles is presented later on. Representation of codes on graph is the next step towards characterization of the iterative decoding as an example of the probability propagation algorithm. The graph representations are presented for a few codes that are commonly used in turbo-like codes. Books > Engineering eBook, Springer Shop<
new in stock. Verzendingskosten:zzgl. Versandkosten. (EUR 0.00)
The common property among turbo-like code is that they consist of very simple constituent codes that are connected to each other with random or pseudorandom interleavers. The crucial nove… Meer...
The common property among turbo-like code is that they consist of very simple constituent codes that are connected to each other with random or pseudorandom interleavers. The crucial novelty in these codes is the iterative decoding. This means that the constituent codes are decoded separately, which is ef?cient and practically feasible since they are very simple codes. Then, they pass new information to each other in a course of a few iterations. It has been shown that iterative decoding is a generalization of the well-known probability or belief propagation algorithm. The belief propagation algorithm that has been essential for development of new ideas throughout this work is described in the context of coding. The basic theorems for this algorithm are explained and proven in the following paragraphs. Thisis then followed by a description of the computational algorithm. The probability propagation algorithm is proven in c- junctionwithatree-structuredgraph–graphswithoutanycycle.Infact,thegraphical representation of any problem solved by this algorithm is the centerpiece of the algorithm. The generalization of the algorithm for graphs with cycles is presented later on. Representation of codes on graph is the next step towards characterization of the iterative decoding as an example of the probability propagation algorithm. The graph representations are presented for a few codes that are commonly used in turbo-like codes. Books > Engineering eBook, Springer Shop<
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Bibliografische gegevens van het best passende boek
Boek bevindt zich in het datenbestand sinds 2008-01-09T08:35:49+01:00 (Amsterdam) Detailpagina laatst gewijzigd op 2023-06-27T19:01:00+02:00 (Amsterdam) ISBN/EAN: 9781402063916
ISBN - alternatieve schrijfwijzen: 978-1-4020-6391-6 alternatieve schrijfwijzen en verwante zoekwoorden: Titel van het boek: codes, turbo reh, decoding
Gegevens van de uitgever
Auteur: Aliazam Abbasfar Titel: Turbo-like Codes - Design for High Speed Decoding Uitgeverij: Springer; Springer Netherland 84 Bladzijden Verschijningsjaar: 2007-09-09 Dordrecht; NL Taal: Engels 96,29 € (DE) 99,00 € (AT) 118,00 CHF (CH) Available XVIII, 84 p.
EA; E107; eBook; Nonbooks, PBS / Technik/Elektronik, Elektrotechnik, Nachrichtentechnik; Nachrichtententechnik, Telekommunikation; Verstehen; Channel coding/Error correcting codes; Code; High speed turbo decoding; LDPC codes; RA/ARA codes; Turbo codes; algorithms; complexity; C; Communications Engineering, Networks; Microwaves, RF Engineering and Optical Communications; Signal, Speech and Image Processing; Coding and Information Theory; Engineering; Elektronik; Digitale Signalverarbeitung (DSP); Kodierungstheorie und Verschlüsselung (Kryptologie); Informationstheorie; BB
Turbo Concept.- High-speed Turbo Decoders.- Very Simple Turbo-like Codes.- High Speed Turbo-like Decoders. Turbo code concepts are explained in simple language Turbo codes and LDPC codes are viewed in a unified manner as turbo-like codes Implementation and hardware complexity is a major focus Presents a novel class of powerful and practical turbo-like codes Includes advanced theoretical framework for professionals
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