搜索资源列表
LFM1_mp_1
- 信号与信息处理——阵列信号处理DOA估计的matlab算法,这是线性调频信号的稀疏分解算法,很有用
LFM1_mp_2
- 信号与信息处理——阵列信号处理DOA估计的matlab算法,这是线性调频信号的稀疏分解的另一种算法源码
LFM1_mp_f_1
- 信号与信息处理——阵列信号处理DOA估计的matlab算法,这是线性调频信号的稀疏分解算法,很有用
LFM2_mp_1
- 信号与信息处理——阵列信号处理DOA估计的matlab算法,这是线性调频信号的稀疏分解算法,针对频率的变化性能
LFM2_mp_snr_1
- 信号与信息处理——阵列信号处理DOA估计的matlab算法,这是线性调频信号的稀疏分解算法,对信噪比的变化
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
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
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.)
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)
data_SVD
- 阵列信号处理方面,基于相关矩阵的稀疏重构,利用cvx工具箱求解;DOA估计(In array signal processing, sparse reconstruction based on correlation matrix is solved by CVX toolbox, and DOA estimation is used)
sparse_decomposition
- 利用匹配追踪对信号进行稀疏分解,得到其稀疏表示形式(The use of matching pursuit for sparse decomposition of the signals, by their sparse representation)
GMC_software
- 用于稀疏优化的最新非凸函数GMC算法,可用于信号处理以及图像处理。(The latest non convex function GMC algorithm for sparse optimization, can be used for signal processing and image processing.)
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
omp
- 正交匹配追踪(OMP)在稀疏分解与压缩感知重构,稀疏分解先于压缩感知提出,信号稀疏表示的目的就是在给定的超完备字典中用尽可能少的原子来表示信号,可以获得信号更为简洁的表示方式,从而使我们更容易地获取信号中所蕴含的信息,更方便进一步对信号进行加工处理,如压缩、编码等。(Orthogonal Matching Pursuit (OMP) is used in sparse decomposition and compressive sensing reconstruction. Sparse dec
GroupSparseBox
- 组稀疏表达Matlab代码,同时里面包含了压缩感知信号稀疏表征的几种典型算法。(G r o u p S p a r s e B o x, the matlab codes for group sparse representation, some classical algorithms such as BMP, BOMP, StGOMP etc. also included.)
BOMP
- 用于图像处理和信号DOA估计,是基于块稀疏的正交匹配追踪算法(This is an algorithm based on signal block sparsity, which can be used in image processing and signal DOA estimation)
MSBL_code
- 块稀疏贝叶斯方法,使用块稀疏贝叶斯求解稀疏信号(Block Sparse Bayesian Method)