资源列表
IMF-Intrinsic-Mode-Function-
- IMF法用作轴承故障检测程序，含所需方程m文件及图像文件-Copyright (c) 2012, Santhana Raj All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * R
junhengqi
- 通信原理时域均衡部分的五抽头迫零均衡器，很有用-Five tap the communication domain equalization principle part of zero-forcing equalizer, useful
Athi_2048_Game_AI_Solver_01-05-2014
- 详细说明：包含alphaBeta剪枝智能算法的matlab源程序，能很好解决2048小游戏的搜索功能-alphaBeta Pruning intelligent algorithm matlab source code, can achieve a good search function and other games 2048
DDPMSG
- 发电机并网，机侧双闭环控制，网侧双闭环控制，控制很好，中间直流电压平稳-Generators and network-side double-loop control, network-side dual-loop control, control is very good, steady intermediate DC voltage
cs_ls_mse
- 此程序实现压缩感知方法与最小二乘方法在超宽带信道估计中实现信道估计的MSE对比。-This program is compressed sensing method with the least squares method is implemented in ultra-wideband channel estimation channel estimation MSE contrast.
vibra_yuchuli
- MATLAB实现振动信号预处理：最小二乘法消除多项式趋势项和五点滑动平均法平滑处理-MATLAB realize vibration signal preprocessing: least squares polynomial trend items and eliminate a five-point moving average smoothing
vibra_motaishiyu
- matlab实现振动信号试验模态参数时域识别：STD法和复指数法-matlan achieve vibration signals in time domain experimental modal parameters identification: STD modal parameter identification method and the complex exponential law modal parameter identification
IEEE 14bus
- Matlab implementation of IEEE 14 bus in Simulink PowerSim
Optimization-design-test
- 从数控机床能耗角度出发，以切削参数为变量，以降低数控机床能耗为目标，在实际加工经验公式的基础上，考虑机床性能和刀具约束条件，建立数控机床能耗模型，采用粒子群优化算法对目标函数寻优求解，利用优化后的切削参数进行加工，能明显地降低能耗。-Optimization design of numerical control tool energy base on cutting paramenters
Optimization-design-experiment1
- 从数控机床能耗角度出发，以切削参数为变量，以降低数控机床能耗为目标，在实际加工经验公式的基础上，考虑机床性能和刀具约束条件，建立数控机床能耗模型，采用粒子群优化算法对目标函数寻优求解，利用优化后的切削参数进行加工，能明显地降低能耗。-From the perspective of CNC machine tool consumption to cutting parameters as variables , in order to reduce the energy consumption o
MLE_Classifier
- 用最大似然估计训练分类器，用Train.txt里的数据进行训练，用Test.txt的数据进行性能检测-Use the maximum likelihood estimation training classifier, use the data in Train.txt to train the classifier and use the data in Test.txt to test the performance of the classifier
GMMaEM_Classifier
- 采用GMM模型并用EM算法训练分类器，用Train.txt里的数据进行训练，用Test.txt的数据进行性能检测-Using GMM classifier model and EM training algorithm to train the classifier, use the training data in Train.txt to train the classifier and use the data in the Test.txt to test the perform