资源列表
DnCNN-master
- 卷积神经网络进行图像去噪，比较经典的一篇文章代码。(The convolutional neural network performs image denoising and compares the classic article code.)
dlib-19.16
- 编译人脸识别dlib库，能够在Linux，Windows，IOS，Android等平台运行(compile dlib for face recognition)
SIMPLE算法求解方腔内粘性不可压流动
- 采用离散网格，基于SIMPLE算法的基本思想求解方腔不可压缩驱动流(Using discrete grids and based on the basic idea of SIMPLE algorithm, the incompressible driving flow in square cavity is solved.)
海龟交易者
- 适用于海龟交易法指标，包括下单指示。两套原版系统。(Indicators applicable to Turtle Trading)
《神经网络与深度学习》邱锡鹏
- 复旦大学深度学习课程资料，适合研究生及本科生作为深度学习的入门资料(Fudan University deep learning course materials, suitable for graduate and undergraduate students as an introduction to in-depth learning materials)
speech emotion recognition
- 这是一款采用Matlab编写的语音识别界面，对情感语音进行模板培训。运行main.m，在界面选择待测试音频文件，运行后即可在界面看到检测结果。(This is a speech recognition interface written in matlab, which trains emotional speech template. Run main.m and select the audio files to be tested in the interface. After runni
ELM分类
- 内含两个数据集---iris_data和classsim，分别为艾瑞斯花和红酒的分类训练数据。分别用这两个数据集对极限学习机（ELM）进行训练，并测试ELM的分类效果。(It contains two data sets, iris_data and classsim, which are classified training data of Iris Flower and Red Wine respectively. The two data sets are used to train t
DP_P2
- 使用动态规划算法（DP）对并联混合动力汽车P2极限油耗求解，并附带后处理程序，通过使用hev_main.m程序直接可运行(The dynamic programming algorithm (DP) is used to solve the P2 limit fuel consumption of the parallel hybrid electric vehicle, with a post-processing program, which can be run directly by u
n_1_zilishi_MCR_500kV
- 画出JA模型的微分方程，用于模型对BH曲线拟合。(Used to fit B-H curve with JA model)
小波包能量可视化和GUI设计
- 特色：1.借用小波包分解和小波能量熵函数；2.GUI界面导入西储大学轴承故障数据；3：对提取小波能量方便快捷(Features: 1. Use wavelet packet decomposition and wavelet energy entropy function; 2. GUI interface to import bearing fault data of Xichu University; 3. It is convenient and fast to extract wavel
nsga2
- 多目标优化算法NSGA-II的python实现(Python implementation of NSGA-II)
基于径向基神经网络的预测地下水位
- 采用径向基神经网络搭建地下水预测模型，进行地下水预测。(The radial basis function neural network is used to build groundwater prediction model.)