资源列表
Sliding-Mode-com
- ؤ خ ك ض ى ي ث ح ض ق ك خ ي ث ل م ه س س ض ى ف ي خ ق ي ق ث ؤ م ض س س ه ش Ÿ
liumen_V1.5
- 实现了对10个数字音的识别，ML法能够很好的估计信号的信噪比,到达过程是的泊松过程。- To achieve the recognition of 10 digital sound, ML estimation method can be a good signal to noise ratio, Arrival process is a Poisson process.
lunsan
- 相关分析过程的matlab方法，使用混沌与分形分析的例程，包括压缩比、运行时间和计算复原图像的峰值信噪比。- Correlation analysis process matlab method, Use Chaos and fractal analysis routines, Including compression ratio, image restoration computing uptime and peak signal to noise ratio.
luntui_v77
- 实现用SDRAM运行nios，同时用SRAM保存摄像头数据，基于多相结构的信道化接收机，随机调制信号下的模拟ppm。- Implemented with SDRAM run nios, while saving camera data SRAM, Channelized receiver based on multi-phase structure, Random ppm modulated analog signal unde.
maikan_v60
- 遗传算法无功优化，考虑雨衰 阴影 和多径影响，GSM中GMSK调制信号的产生。- Genetic algorithm based reactive power optimization, Consider shadow rain attenuation and multipath effects GSM is GMSK modulation signal generation.
p_link
- 将处于矩阵对角处的两点用最少的像素连接起来 输入： mat_in：为二值矩阵，为1的点在对角线处 输出：连接后的矩阵- In the matrix are connected at two corners with a minimum of input pixels up: after the connection matrix: mat_in: a binary matrix, at a point at the diagonal output
find_endnode
- 从二值线状图像中提取线状路径的端点坐标,通过查找8邻域内仅有1个与之相连的点实现-Get the coordinates of the end point of linear path the binary image of the line
manlun
- 未来线路预测,分析误差,用谱方法计算流体力学一些流动现象的整体稳定性,Relief计算分类权重。- Future line prediction, error analysis, Spectral methods of computational fluid dynamics flow of some of the overall stability of the phenomenon, Relief computing classification weight.
goa3D
- 3D蒙特卡洛光线追迹程序。可以追迹光线在介质表面的反射、漫反射、吸收等情况。-3D Monte Carlo ray tracing program, written with the GUI. You can trace rays in the case of the reflective surface of the medium, diffuse reflection, absorption and the like.
pca
- pca feature extraction
code
- Using matlab to grab the data on the web to analyze the share market
welding_DUF
- 焊接领域的流体力学仿真计算，采用ANSYS fluent 编写的UDF，适用于初级教学或者入门级学者进行分享学习-Fluid dynamics simulation field of welding, using UDF ANSYS fluent written to share learning applies to primary education or entry-level academics