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Basu-2008-10-02
- Implementing Tabu Search to Exploit Sparsity in ATSP Instances
A-Bayesian-Approach
- In this paper, we propose a Bayesian methodology for receiver function analysis, a key tool in determining the deep structure of the Earth’s crust.We exploit the assumption of sparsity for receiver functions to develop a Bayesian deconvolution
LASSOaLARSa-SPCA
- Abstract There a number of interesting variable selection methods available beside the regular forward selection and stepwise selection methods. Such approaches include LASSO (Least Absolute Shrinkage and Selection Operator), least angle regression (
SAMP1
- 能对压缩感知中的稀疏度未知的信号精确的重建，重建误差小，经本人调试，完全正确-Capable of compressed sensing signals unknown sparsity accurate reconstruction, reconstruction error is small, after I debug, completely correct
User_Guide_v1.0b
- TVAL3算法的使用手册。TVAL3是一种利用梯度模稀疏性的压缩感知重构算法，恢复平滑图像效果不错。-User_Guide for TVAL3. TVAL3 is s compressed sensing reconstruction algorithm using gradient model sparsity. It can restore smooth image with good result.
URSI_GASS_2011_short
- Compressed sensing, a method which relies on sparsity to reconstruct signals with relatively few measurements, has the potential to greatly improve observation of distributed radar targets. We extend the theoretical work of others by investigatin
Sparsity-Inducing-DOA
- 基于稀疏分解的宽带信号DOA估计方法，使用了基于贝叶斯的方法具有良好的估计精度和分辨率-Wideband signal sparse decomposition DOA estimation method based on the use of a method based on Bayesian estimation has good accuracy and resolution
paper2
- Sparsity Enhanced Decision Feedback Equalization
SVR
- 基于支持向量机的短波信号盲均衡算法，该算法稀疏性好，性能稳定。-SVM shortwave signal blind equalization algorithm based on the algorithm sparsity, and stable performance.
B--speech-enhancement
- 本文章主要是研究在压缩传感语音增强稀疏问题。一些算法以及对比。-On sparsity issues in compressive sensing based speech enhancement
Mod-CS-chann-track
- We propose a compressive method for tracking doubly selective channels within multicarrier systems, including OFDMsystems. Using the recently introduced concept of modified compressed sensing (MOD-CS), the sequential delay-Doppler sparsity of t
COOMP
- Cooperative Greedy Pursuit Strategies are considered for approximating a signal partition subjected to a global constraint on sparsity. The approach aims at producing a high quality sparse approximation of the whole signal, using highly coherent
02-sparsity-overview
- SPARSE REPRESENTATON IN TIME DOMAIN AND FREQUENCY DOMAIN
Compressive-Sensing-for-Signal-Ensembles
- Compressive sensing (CS) is a new approach to simultaneous sensing and compression that enables a potentially large reduction in the sampling and computation costs for acquisition of signals having a sparse or compressible representation in some
Structured-Sparsity-Models
- 用于混响背景语音分离的结构稀疏模型(Strutured sparisty model)方法-To further tackle the ambiguity of the reflection ratios, we propose a novel formulation of the reverberation model and estimate the absorption coefficients through a convex optimization exploiting