搜索资源列表
SMI_FDL_NCCB_BF
- 对于声矢量圆阵，比较固定对角加载法（FDL）和双重范数约束法（NCCB）和常规（SMI）的自适应波束形成器的性能。-For acoustic vector circular array, relatively fixed diagonal loading method (FDL) and double norm constraint method (NCCB) and conventional (SMI) adaptive beamformer performance.
SINR_N
- 对于声矢量圆阵，比较固定对角加载法（FDL）、加权向量范数约束法（NCCB）两种算法输出信干噪比随快拍数变化。-For acoustic vector circular array, relatively fixed diagonal loading method (FDL), weighted vector norm constraint method (NCCB) two algorithms output SINR with snapshots change.
SRC
- 源码实现了使用基于稀疏表示的人脸识别算法。使用GPSR作为l1模最小化方法。-Source code to achieve the use of sparse representation based on the face recognition algorithm. Using GPSR as a method for minimizing the L1 norm.
time_fractional-Eq
- 数值求解时间分数阶微分方程，空间部分采用有限元离散，最后可以验证误差的L2范数达到最优收敛阶-Numerical Solution of the Time Fractional differential equations, finite element discrete space segment, the last error can verify the L2 norm of optimal order of convergence
LRR-and-WNNM-LRR
- 该程序可实现低秩子空间聚类和加权核范数最小化低秩子空间聚类。参考文献：Guangcan Liu, Zhouchen Lin, Shuicheng Yan, Ju Sun, Yong Yu, Yi Ma, Robust recovery of subspace structures by low-rank representation, IEEE T. Pattern Anal. 35(1) (2013) 171-184.-This program can realize subspace clu
norm_Optimal-ILC
- 范数优化迭代学习代码，可以运行，效果非常好-norm-optimal iterative learning control
OMPmatlab-compression-0075_www.matlabsite.com
- l1 norm minimization
SolveAMP
- L1范最小化算法，匹配追踪算法，MATLAB语言实现，可以直接用(L1 norm Minimization Algorithm)
5
- 在进行反演时所用到的1范数约束解法程序，其中用到了共轭梯度算法。(In the process of inversion, the 1 norm constraint solution is used, in which conjugate gradient algorithm is used.)
107215789BP
- 一范数的求解方法，非常经典，在图像重建和压缩感知有广泛应用(The solution of one norm is very classic, a wide range of applications in image reconstruction and compression)
cs
- 压缩感知的例子。重建是用在稀疏域上求最小零范数的方法。首先把零范数凸松弛为一范数，然后变成线性规划问题，从而求得最优解。(An example of the compressive sensing. Its reconstruction is based on L0-norm minimization.)
Parafac codes
- PARAFAC源程序，可以用于平行因子分析处理的算法，很全很好用(unction [A,B,C,LLF,I,J,K] = parafac(XPK,I,N,epsilon) % PARAFAC Parallel factor analysis for an three-way data array % The iterative process is continued until that m > 300 or ABS((LF(m)-LF(m-1)) % /LF(m-1)) is l
Tensor Sensing
- 对tenor张量进行补全并最小化范数，得到tensor的分解形式(ADMM Complementing the tenor tensors and minimizing the norm, we get the decomposition form of tensor.)
L1SRACV
- 压缩感知DOA算法，利用1范数方法进行优化重构，进行方位角估计(Compressed Sensing DOA algorithm, using 1-norm method to optimize reconstruction and azimuth estimation)
l范数问题
- 此文件应用于稀疏分离求解约束问题l范数问题。This file is applied to solve the l-norm problem of constraint problem by sparse separation