搜索资源列表
OMP
- 正交匹配追踪算法，用于稀疏信号恢复，包括算法与实验-sparse signal recovery orthogonal matching pursuit
Linearized-Bregman
- linearized bregman 用于压缩感知中的稀疏信号恢复-linearized bregman
k_svd1
- K-SVD同MOD一样也分为Sparse Coding和Dictionary Update两个步骤，Sparse Coding没有什么特殊的，也是固定过完备字典D，使用各种迭代算法求信号在字典上的稀疏系数。-K-SVD Sparse Coding and Dictionary Update is also divided into two steps, like MOD, Sparse Coding is not anything special, also fixed overcomplete
generate_graphs
- MIT稀疏傅里叶变换 小组的SFFT 源码： 运行的SFFT和FFTW参数和重复的范围内，两者的运行时间 诗句信号的大小（n）或稀疏（ K ） 。重新创建图表的文件： 稀疏傅里叶变换， SODA 12简单和实用的算法。 -Runs sFFT and FFTW for a range of parameters and plots the runtime of both verse the signal size (n) or the sparsity (k). Recreat
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
random
- 压缩感知，观测矩阵采用随机观测矩阵，解码采用OMP算法，信号采用频域稀疏度为7的信号，可以直接运行。-Compressed sensing, observation matrix using random observation matrix decoding using OMP algorithm signal using frequency-domain signal sparsity 7, it can be run directly.
main1
- 直接贝叶斯方法进行压缩感知中的稀疏信号的重构-direct Beiyasian method for CS reconstruction
main2
- 变分贝叶斯方法进行压缩感知中的稀疏信号的重构-Variational Bayesian method for CS reconstruction
PSO
- 用智能算法的粒子群算法进行压缩感知稀疏信号的重构-PSO is used for signal reconstruction
sfft-code
- 稀疏快速傅里叶变换作为传统FFT的改进版，它充分利用输入信号频域稀疏特性，实现序列的快速傅里叶变换。(As an improved version of the traditional FFT, sparse fast Fourier transform takes full advantage of the sparse characteristics of the input signal frequency domain to achieve fast Fourier transform