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现在广义的Turbo码是指采用级联或乘积编码方法并利用迭代译码方法的编译码方案。迭代译码的基本思想是将一个的复杂的长的译码步骤分解为多个相对简单的迭代译码步骤而且在迭代译码步骤之间信息概率的转移或者是软信息的传递确保几乎没有信息损失。
根据其成员码和级联的方法的不同，Turbo码的分类 .本设计论文提供了Turbo码matlab代码以及界面设计（版权所有，仅供参考！）
-now generalized Turbo code refers to the use of the product
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这是一个很好的关于turbo乘积码的matlab代码-This is a very good turbo product codes on the Matlab code
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文章详细介绍了TPC编码技术及信道容限， 是一篇不错的介绍TPC的文章-An important goal for a new communication system is to transfer information at a high rate while
keeping energy consumption low. Shannon s channel capacity sets a limit on the tradeoff between the rate
of infor
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turbo乘积码软译码核心算法，是针对turbo乘积码译码的汇编程序-turbo product codes decoding soft-core algorithm for decoding turbo product code assembler
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turbo乘积码，译码中的迭代译码核心算法-turbo product codes, decoding the core of the iterative decoding algorithm
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This book includes BCH codes, Reed–Solomon codes, convolutional codes, finite-geometry
codes, turbo codes, low-density parity-check (LDPC) codes, and product codes.
However, the title has a second interpretation. While the majority of this book
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Abstract—In this letter, we propose an efficient decoding algorithm
for turbo product codes as introduced by Pyndiah. The proposed
decoder has no performance degradation and reduces the
complexity of the original decoder by an order of magni
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A full-parallel architecture for turbo decoding, which achieves ultrahigh
data rates when using product codes as error correcting codes, is
proposed. This architecture is able to decode product codes using
binary BCH or m-ary Reed-Solomon compo
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Soft Incremental Redundancy for Distributed Turbo Product Codes
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This is a report of a type of Turbo Codes, namely product Turbo Codes. It can be helpful for those who wish to work in this area.
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Channel Codes
Channel coding lies at the heart of digital communication and data storage, and
this detailed introduction describes the core theory as well as decoding algorithms,
implementation details, and performance analyses.
Professors Ry
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Turbo product Codes (TPC) MATLAB CODE:his code is provided to help researchers explore the performance of TPCs under different scenarios
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