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数据结构好冬冬
- 哈夫曼编码译码,克鲁斯卡尔算法,魔王语言的解释,一元稀疏多项式相乘，C-Huffman encoding decoding, Kelushikaer algorithm, fiendish language interpretation, one yuan sparse polynomial multiplication, C
LDPC
- LDPC码编解码仿真程序，BSC、AWGN信道，sparse编码-LDPC code decoding simulation program, BSC, AWGN channel, sparse coding
communications_2
- 用vhdl代码描述的通信系统仿真程序。包括信源（20位m序列），crc编码（采用串行算法），加噪（用22位m序列产生稀疏的1，然后和编码后的数据异或），crc解码，数据串行输出。 -Vhdl code with the simulation program described in the communication system. Including the source (20 m sequence), crc code (using the serial algorithm), no
AnalgorithmusingtheSchurcomple-
- LDPC(Low-density-parity-check，低密度奇偶校验)码是一类具有稀疏校验矩阵的线性分组码，不仅有逼近Shannon限的良好性能，而且译码复杂度较低，结构灵活，是近年信道编码领域的研究热点-LDPC (Low-density-parity-check, low-density parity check) codes are a class of sparse check matrix of linear block codes, is not only good perfo
CSzhongsu
- 该文对压缩感知理论进行了综述，对压缩感知的稀疏表示、观测矩阵、编码、解码和有待研究的关键问题进行了综述-This paper summarizes the theory of compressed sensing, sparse representation of compressed sensing, observation matrix, encoding, decoding and the key issues to be examined were reviewed
ldpc
- LDPC编码描述，译码描述，稀疏H矩阵描述，基于概率运算的译码方式-LDPC coded descr iptions, decoding descr iption, sparse matrix H described decoding methods based on probability calculation
BP-decoding-with-Sparse-Matrix
- 主要讲的BP的译码算法，通过各种比较，突出他的译码性能比较好-Mainly about BP decoding algorithm, through a variety of comparison, highlighting his decoding performance is better
LDPC
- Parity check bits is computed using sparse LU decomposition, utilizing sparse matrix properties of H. LDPC code decoding is done using iterative belief propagation or sum-product algorithm (SPA). Four versions of SPA decoder are presented.
code
- 稀疏傅立叶算法，matlab实现仿真，对于算法重构用到了混叠同余法和相位解码法，并对SFFT和FFT算法对同一数据的处理时间进行了对比。(Sparse Fourier algorithm, matlab to achieve the simulation, the algorithm used for aliasing congruence and phase decoding method, and the SFFT and FFT algorithm for the same data pr
Deterministic Message Passing Algorithm SCMA in NOMA 5G
- Being an effective non-orthogonal multiple access (NOMA) technique, sparse code multiple access (SCMA) is promising for future wireless communication. Compared with orthogonal techniques, SCMA enjoys higher overloading tolerance and lower complexity