资源列表
omp cosamp sp
- 压缩感知 重构算法源代码：主要包括OMP，CoSamp，SP等重构算法，算法还需要根据不同的应用场景适当修改。(compressive sensing reconstruction algorithms source code)
SIMPLEt-2D
- 利用simple算法进行流动与传热传质过程的数值计算的主程序(Simple algorithm for flow and heat and mass transfer process of numerical calculation of the main program)
新建文件夹
- 层次聚类（hierarchical clustering）matlab算法实现：包括图，代码，数据集。(the matlab implementation of Hierarchical clustering algorithm,)
bcs_ver0.1
- 贝叶斯压缩感知源代码，可以实用无线传感器网络、图像处理等应用领域。感兴趣的朋友可以下载哦。(Bayes compressive sensing is applied in wirless sensor networks, image processing and so on. If you are interested, you can dowload them.)
OFDM
- OFDM的matlab仿真实现，可以参考这看一看(OFDM Simulation Implementation)
代码
- 典型LFM信号实部波形、虚部波形和信号额的频谱图及菲涅耳积分(Typical LFM signal real part waveform, imaginary part waveform and signal quantity spectrum)
adaboost
- adaboost算法的训练和测试代码，简单的实例(The aim of the project is to provide a source of the meta-learning algorithm known as AdaBoost to improve the performance of the user-defined classifiers.)
PSO
- 实现PSO优化算法的程序，对学习PSO的学者提供一定的帮助。(PSO optimization algorithm to achieve the program, PSO scholars to learn to provide some help.)
模式识别第一次作业
- 1． 用 dataset1.txt 作为训练样本，用dataset2.txt 作为测试样本，采用身高和体重数据为特征，在正态分布假设下估计概率密度（只用训练样本），建立最小错误率贝叶斯分类器，写出所用的密度估计方法和得到的决策规则，将该分类器分别应用到训练集和测试集，考察训练错误率和测试错误率。将分类器应用到dataset3 上，考察测试错误率的情况。(1. using dataset1.txt as training samples as test samples by dataset2.tx
leaveout
- 用留一法对数据进行训练，假设有N个样本，将每一个样本作为测试样本，其它N-1个样本作为训练样本。(The data were trained by leaving one method. Assuming N samples were used, each sample was used as a test sample and the other N-1 samples were used as training samples.)
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.)
PVMicroInverter220V_DesignPackage
- 单相光伏电流双环控制模型，电流内环加电压外环，测试通过直接运行(Single phase photovoltaic current dual loop control model)