搜索资源列表
SpareMatrix
- 稀疏矩阵的抽象数据结构的算法的实现，首先声明一个类，在该类的基础上实现数据的存储与矩阵的转置-sparse matrix of the abstract data structure of the algorithm to achieve and be the first to declare a class, In such on the basis of data storage and matrix transpose
super--resolution
- 超分辨率研究中的ppt资料，有稀疏表示，流形学习框架下的邻域嵌入，对超分辨率研究很有帮助-Ppt super-resolution study of the data, there is sparse, said manifold learning embedded within the framework of the neighborhood, useful for the study of super-resolution
When_is_missing_data_recoverable
- 详细介绍了图像稀疏分解思想在数据修复方面的应用。给出了较为详细的理论依据，以及简单的实例介绍-Details of the image sparse decomposition ideas in the application of data recovery. Gives a more detailed theoretical basis, as well as a simple example to illustrate
1
- 数据结构 课程设计 稀疏多项式乘法的实现 -Data structure the curriculum design to achieve sparse polynomial multiplication
xishujuzhen
- 实现稀疏矩阵的各种运算，能给我们的数据结构学习带来很多好处-To achieve a variety of sparse matrix operations, can give us many advantages to learn data structures
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
Sparse-Matrix
- 在处理数据时经常需要处理稀疏矩阵，本文件包含了部分处理稀疏矩阵对角化、行列重拍等Matlab函数。-In the processing of data often need to deal with sparse matrices, this document contains some sparse matrix diagonalization, ranks remake Matlab functions.
DataMining3rd
- 评测数据在去掉停用词的 分类过程开放测试中,引入Good-Turing算法的分类性能比Laplace原则提高了3·05 ,比Lidstone方法提高 1·00 .而在交叉熵选择特征词的算法中,增加Good-Turing的贝叶斯分类方法可比最大熵分类性能高95 .通过这种数据平滑的算法,有助于克服因数据稀疏而引发的特征词缺失问题 -Evaluation data in the open test of the classification process to remove stop
propose
- The ideas proposed in this paper have been developed and tested using distributed databases containing information patients undergoing dialysis. The databases were residing at four different locations. They contained over 500 parameters for hundreds
s
- Sparse Partial Least Squares Regression for On-Line Variable Selection with Multivariate Data Streams
juzhen
- 数据结构]利用三元组表对稀疏矩阵实现加法、减法及转置运算-Data Structures] use triples table for sparse matrix realization of addition, subtraction, and transpose operation
Introduction-Compressed-Sensing
- 压缩感知（CS）理论是在已知信号具有稀疏性或可压缩性的条件下，对信号数据进行采集、 编解码的新理论。主要阐述了CS理论框架以及信号稀疏表示、CS编解码模型，并举例说明基于压缩感知理论的编解码理论在一维信号、二维图像处理上的应用。 -Compressed Sensing(CS) theory is a novel data collection and coding theory under the condition that signal is sparse or compress
Compressed-Sensing-Theory
- 用压缩感知理论对信号数据进行采集、编解码,进行数据恢复。主要阐述了CS理论框架以及信号稀疏表示、CS编解码模型.-Compressed Sensing(CS) theory is a novel data collection and coding theory under the condition that signal is sparse or compressible.
icml09-deepbeliefnetwork
- 相比DeconvNet写得比较简洁易懂。但是原来代码里面给的数据似乎没法跑。所幸同作者还有一些代码用到了TCNN，比如action recognition，可以一起下载下来参考。这个代码主要特色就是tiled结构，可以用来参考，然后把里面ICA的优化函数换成RICA，Sparse Coding等等。总之，在这个代码里也了解了不少(比如line search等)。-DeconvNet well written and easy to understand compared to relativel
SPP-master
- 稀疏投影保持降维算法，用于高维度数据降维分类和回归的算法-Projections remain sparse dimension reduction algorithm for high-dimensional data dimensionality reduction classification and regression algorithm
Feature-Denoising
- joint sparse representation (JSR)方法用于车内语音增强的特征降噪算法-address reducing the mismatch between training and testing conditions for hands-free in-car speech recognition. It is well known that the distortions caused by background noise, channel effec
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
A-Swarm-Intelligence-Algorithm
- 联合稀疏恢复的Swarm算法，在基本particle swarm optimization (PSO)算法基础上进行改进-Inspired by particle swarm optimization (PSO) algorithm and some sparse recovery algorithms, a novel swarm intelligence algorithm called M-SISR is proposed to solve the problem. In M-