搜索资源列表
CurveLab-2.1.3.tar
- 最新曲波变换工具箱，用于信号稀疏分解重构-Last curvelet transform toolbox for signal sparse decomposition and reconstruction
MP
- 基于MP的信号稀疏分解参考程序的matlab仿真代码-Matlab simulation code of the reference procedure based on the MP signal sparse decomposition
l1magic-1.11
- 实现信号稀疏重构的l1算法程序代码，实现信号稀疏重构的l1算法程序代码，-the matlab code of the method l1
sparse_MP
- 信号稀疏表示的小程序，适合初学者入门。采用匹配追踪算法-Signal sparse representation of small procedures, suitable for beginners.
ksvdbox
- 用于信号稀疏表示中冗余字典训练的KSVD算法，采用matlab与c的混合编程，具有更高的计算效率-KSVD algorithm for sparse signal representation in a redundant dictionary training
4-chapter
- 信号稀疏度检测的matlab仿真程序。该方法能够检测出宽带信号的稀疏度，保证Compressive Sensing在宽带频谱检测中的准确运用。-Signal sparsity detection matlab simulation program. The method can detect the wideband signal sparsity ensure Compressive Sensing wideband spectrum sensing in the exact use.
SolveBP
- BP，基追踪，同MP一样，是实现信号稀疏分解的方法-BP, basis pursuit, as with the MP, is to achieve sparse signal decomposition method
SolveBP
- BP，基追踪，同MP一样，是实现信号稀疏分解的方法-BP, basis pursuit, as with the MP, is to achieve sparse signal decomposition method
CS_BP
- 基追踪稀疏重构算法matlab实现，包含信号稀疏过程和重构过程-Based tracking sparse reconstruction algorithm matlab realize, including the process and the sparse signal reconstruction process
TestSparsify
- 压缩感知中用于检测信号稀疏度的代码，有些重构算法需要已知稀疏度所以很有用，可以-compressive sensing
mp
- 基于GA和MP的信号稀疏分解matlab程序来自于信号与图像的稀疏分解及初步应用-Sparse signal sparse decomposition of MP GA and matlab program signal and image decomposition and its application based on
xishubiaoshi
- 信号稀疏表示，去噪处理，稀疏分解后重构性能非常好-Signal sparse representation, de-noising, sparse decomposition and reconstruction after the performance is very good
WaveletOMP
- 冗余字典用于处理图像恢复 以及用于处理信号稀疏性-Redundant dictionary for processing image restoration and means for processing signals sparsity
3
- 信号稀疏度K与重构成功概率关系曲线绘制例程代码-K signal sparsity and Reconstruction success probability plots draw sample code
xinhaoxishubiaoshi
- 信号稀疏表示是一种新兴的信号分析和综合方法，其目的就是在过完备字典中用尽可能少的原子来表示信号。采用时频原子字典的信号稀疏表示能够有效地揭示非平稳信号的时变特征。信号稀疏表示吸引了研究者的大量关注，这种方法已经被应用到信号处理的许多方面，例如非平稳信号分析，信号编码、识别与信号去噪等。-Signal sparse representation is a new method of signal analysis and synthesis, and its purpose is in over-
twoweightniose2
- 加权l1-极小恢复k块稀疏信号恢复，加的权重是多个，并且不相等。(Sparse signals recovered by the weighted l1-minination.)
yin
- 基因检测 合成语音信号，能够准确检测出输入信号的基频，并以稀疏矩阵的形式输出检测到的数值(Fundamental Frequency Component Detecting)
l1_ls
- l1范数约束的使用最小二乘法计算观测信号的稀疏编码，(L1 norm constraint using the least squares method to calculate the observed signal sparse coding,)
SPAMS
- 先输入数据生成相应的字典，再输入检测信号后得到用字典稀疏表示的结果(First input data, generate the corresponding dictionary, and then input the detection signal to obtain sparse dictionary results)
MP_decomposition
- 基于MP的稀疏分解算法，信号的去燥，重构，应用的是cabor原子(MP based sparse decomposition algorithm, signal drying, reconstruction, the application of Cabor atoms)