资源列表
Kyle
- It's a pass filter that based on matlab platform can remove noise from orignal signal
CS_SAR
- 合成孔径雷达仿真程序，包括回波仿真，使用调频变标算法(Synthetic aperture radar simulation program, including echo simulation, the use of FM scaling algorithm)
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)
RD_SAR_large_squint
- 大斜视条带合成孔径雷达仿真程序，包括回波仿真(Large squint synthetic aperture radar simulation program, including echo simulation)
kongjianpinghua
- 阵列信号处理，空间平滑解相干，估计空间中相干与非相干混合信号。(Array signal processing, spatial smoothing decorrelation, estimation of coherent and incoherent mixed signals in space.)
machine-learning-ex8
- 吴恩达老师Cousera上机器学习课程ex8关于协同滤波(Collaborative filtering learning algorithm)的向量化实现以及相关测试数据。(Teacher Andrew Ng Cousera machine learning courses, ex8 Collaborative filtering learning algorithm on the vector implementation and related test data.)
二维数据画图程序
- 二维数据画图Matlab程序，运行非常方便，适合于科研人员对数据的处理。 (Dimensional data drawing Matlab program, run very convenient, suitable for researchers to deal with the data.)
复化Simpson公式法----matlab
- 复化Simpson公式法----matlab，勇于离散积分方程，助于勇于工程反问题的计算，适合于算例仿真。 (Complex Simpson formula ---- matlab, the courage to discrete integral equation, help to the courage to reverse the calculation of the project, suitable for example simulation.)
machine-learning-ex4
- Andrew Ng Cousera 机器学习课程神经网络手写字符识别，源代码以及说明文档(Andrew Ng Cousera 's Machine learning courses, Neural Network handwritten character recognition, source code and documentation)
machine-learning-ex5
- Andrew Ng Cousera 机器学习线性回归，并用它来研究不同偏置方差性能模型，源代码以及说明文档。(Andrew Ng Cousera's machine learning linear regression and use it to study models with different bias-variance properties and source code and document.)
machine-learning-ex6
- Andrew Ng Cousera 机器学习支持向量机SVM，源代码以及说明文档。(Andrew Ng Cousera's machine learning SVM source code and document.)
machine-learning-ex7
- Andrew Ng Cousera 机器学习K-means勇于图像压缩 以及主成分分析PCA用在人脸识别，源代码以及说明文档。(Andrew Ng Cousera machine learning , the K-means clustering algorithm and apply it to compress an image. In the second part, you will use principal component analysis to find a low-dime