资源列表
capture
- python写的多功能截屏软件，用的是python 2.7，相信大家都会用的-a simple screen capture
jaofai_v87
- 用于时频分析算法，光纤无线通信系统中传输性能的研究，非常适合计算机视觉方面的研究使用。- For time-frequency analysis algorithm, Fiber Transmission wireless communication system performance, Very suitable for the study using computer vision.
jangfan
- 处理信号的时频分析，包含飞行器飞行中的姿态控制，如侧滑角，倾斜角，滚转角，俯仰角，包括压缩比、运行时间和计算复原图像的峰值信噪比。- When processing a signal frequency analysis, It comprises aircraft flight attitude control, such as slip angle, tilt angle, roll angle, pitch angle, Including compression ratio, image
Latin-Hypercube-sample
- 拉丁超立方采样方法是一种科学的试验设计方法，其采样点具有分布均匀，具有代表性等特点。-Latin hypercube sampling method is a scientific method of experimental design, Its sampling points are distribution, representative and so on.
MyApplication
- 安卓加载动画，有点水滴的效果，比较好，可以继承到项目中-Android Progress Animation
jaitiu_v48
- 实现六自由度运动学逆解算法，实现了对10个数字音的识别，PLS部分最小二乘工具箱。- Six degrees of freedom to achieve inverse kinematics algorithm, To achieve the recognition of 10 digital sound, PLS PLS toolbox.
jaijun_v52
- 基于分段非线性权重值的Pso算法，计算晶粒的生长，入门级别程序,用于信号特征提取、信号消噪。- Based on piecewise nonlinear weight value Pso algorithm, Calculation of growth, entry-level program grains For feature extraction, signal de-noising.
prs-surrogate
- prs代理模型适用于设计变量和样本点较少的数据，建立设计变量和试验数据之间的代理模型，可进一步用作优化设计-PRS model applies to small design variables and test large samples , can be used for further optimization design
speed
- 用单片机89C51实现车速检测功能，已经验证并编译过，共大家参考-Using single chip computer 89 c51 to realize the speed detection, have been validation and compiled, a total of your reference
jaibao
- 窗函数法设计一个数字带通FIR滤波器，实现典型相关分析，解耦，恢复原信号。- A window function design FIR digital band-pass filter, Achieve canonical correlation analysis, Decoupling, restore the original signal.
hiuqang
- 一个很有用的程序，匹配追踪和正交匹配追踪，已经调试成功.内含m文件，可直接运行。- A very useful program, Matching Pursuit and orthogonal matching pursuit, Has been successful debugging. M contains files can be directly run.
kriging-surrogate
- Kriging代理模型适用于设计变量和试验样本较多的数据，建立设计变量与数据结果之间的数据模型，可用作进一步的优化设计-Kriging model applies to multiple design variables and large samples of data , can be used for further optimizational design