资源列表
工程中的有限元方法 (中文版+英文版+源程序)
- 本书比较详细地介绍了有限元方法基本原理及其在工程中的应用(This book describes in more detail the basic principles of finite element method and its application in Engineering)
sensorless_pmsm
- 系统以PMSM做为控制对像，以模型参考自适应算法实现PMSM的转子速度与位置的辨识，采用矢量控制，构建出PMSM的无传感器控制系统。(The system uses PMSM as control image, and uses model reference adaptive algorithm to realize the identification of rotor speed and position of PMSM. Vector control is used to constru
emd
- 基于EMD滚动轴承故障诊断的编程，将振动信号进行分解得到特征频率(Based on EMD programming of rolling bearing fault diagnosis, the vibration signal is decomposed to obtain characteristic frequency)
To calculate loudness and sharpness
- 计算声品质客观参量：响度和尖锐度等，为声品质主客观评价模型的建立提供基础(Calculate the objective parameters of the sound quality: loudness and sharpness, etc., to provide the basis for the establishment of the subjective and objective evaluation model of sound quality)
LSTM-MATLAB-master
- LSTM作为经典的回归神经网络类型，可以用于实现时序数据的预测。(It is used for prediction of time series data)
SOURCE-UDF
- 在fluent中对一个固体应用udf加载了双椭球热源（生热率）(For a solid,using a udf to add a heat source to the double ellipsoid)
convolution_network_on_FPGA-master
- 在FPGA平台上运行的CNN模型，可以完成相关的功能(The CNN model that runs on the FPGA platform can complete the related functions)
rcwa-1d_5_3_2014
- 严格耦合波计算麦克斯韦方程数值解的源代码，可以进行周期性的结构的数值求解，可以对一维所有类光栅结构进行求解。(Rigorous coupling wave is used to calculate the source code of the numerical solution of Maxwell equation, which can be used for numerical solution of periodic structure, and it can solve all kin
twodimentional rubber cavity
- 计算声波由空气经过周期性圆柱空腔的带有钢背衬的橡胶板，出射介质为水的透射和吸声系数。并对比了分别将橡胶和钢板作为压力声学以及都作为压力声学情况下的效果。(A rubber plate with a steel back lined with air through a periodic cylindrical cavity is calculated. The transmission medium is the transmission and sound absorption coeffic
一维激波管
- 本程序源码为用C语言编写的一维激波管问题计算程序(1d sod shock tube problem)
EWT20161130
- matlab-ewt工具箱，2016最新版本。经验小波变换(Empirical wavelet transform (EWT) is a new self adaptive signal decomposition method.)
竞争网络实现2维数据聚类
- 利用竞争神经网络实现2维10类数据的聚类。产生[0 1]之间的10类聚类数据（每类15个样本），用竞争神经网络实现所产生数据的聚类，并在同一图上显示聚类结果。(2 dimensional and 10 dimensional data clustering is realized by competitive neural network. 10 classes of cluster data (15 samples per class) between [0 1] are generated,