YAFPU

说明：  MIDAS实现（混频数据模型），例如用日度数据预测月度数据(Midas implementation (mixing data model), such as forecasting monthly data with daily data)

Wskaź niki, led ATMEGA

关于迁移学习的所有资料，包括：介绍、综述文章、最新文章、代表工作及其代码、常用数据集、硕博士论文(All information about transfer learning includes: introduction, review articles, latest articles, representative work and its code, commonly used datasets, doctoral dissertations.)

Labview Chart Time Display

一个小游戏-a little game

说明：  二值目标图象质心的计算 二值目标图象质心的计算(Second, the value of the target image centroid calculation of the target binary image centroid calculation)

介绍鼠笼式交流异步电动机在正弦电压下的工作情况，异步电动机连接正弦电压工作。(Asynchronous motors work with sinusoidal voltage.)

AT80S52 blink led example

说明：  cohen大神的OM-LSA仿真代码 MATLAB software for speech enhancement based on optimally modified LSA (OM-LSA) speech estimator and improved minima controlled recursive averaging (IMCRA) noise estimation approach for robust speech enhancement.(MATLAB software for speech enhancement based on optimally modified LSA (OM-LSA) speech estimator and improved minima controlled recursive averaging (IMCRA) noise estimation approach for robust speech enhancement. The algorithms are described in: I. Cohen and B. Berdugo, Speech Enhancement for Non-Stationary Noise Environments, Signal Processing, Vol. 81, No. 11, Nov. 2001, pp. 2403-2418. I. Cohen, Noise Spectrum Estimation in Adverse Environments: Improved Minima Controlled Recursive Averaging, IEEE Trans. Speech and Audio Processing, Vol. 11, No. 5, Sep. 2003, pp. 466-475. I. Cohen and S. Gannot, Spectral Enhancement Methods, in Jacob Benesty, M. Mohan Sondhi and Yiteng (Arden) Huang (Eds.), Springer Handbook of Speech Processing, Springer, 2008, Part H, Ch. 44, pp. 873-901)

计算效率，数据保罗分析的经典模型可以用来计算多投入和多产出的效率(calculate efficiency)