threelevelhyster0108

本程序包中涵盖了GSM整个通信链路的仿真，对于学习如何搭建通信链路有帮助(This package covers the GSM communication link throughout the simulation, for learning how to build communication links help)

说明：  一个PN序列发生器，大M序列，供参考学习，(A PN sequence generator, the M series, for reference study,)

航空飞行器6自由度动力学模型，用于飞行力学和飞机控制仿真(Aviation aircraft 6 DOF dynamics model for flight mechanics and aircraft control simulation)

实现洗衣机基本功能，有洗衣选项，计时，洗衣故障时报警，洗衣结束提醒。(Realization of the basic functions of a washing machine, laundry options, timing, fault alarm when the laundry, laundry ending reminder)

Article published in ICIC about traveling waves

利用MUSIC算法估计TOA，是一个比较简单的例子。(Use MUSIC method to estimate TOA)

说明：  本算法为adaboost集成算法，可用来做房价的预测(This algorithm is an AdaBoost integrated algorithm, which can be used to predict the house price)

Lorenz_MatlabCode,分形几何中提出的洛仑兹分形，生成图，matlab源代码(Lorenz_MatlabCode, fractal geometry of the Lorentz proposed fractal, generated map, matlab source code)

本文研究了多幅图像和单幅图像超分辨率方法。在多幅图像超分重建方面， 研究了基于凸集投影和基于正则化的超分辨率方法；在单幅图像超分重建方面， 研究了基于压缩感知的超分辨率方法。(This paper studies on the image and the image super resolution method. In the multiple image super-resolution reconstruction, Based on the projection onto convex sets and super resolution based on regularization method in a single image super-resolution reconstruction, Research on super resolution method based on compressed sensing.)

梯度下降法是一個一階最佳化算法，通常也稱為最速下降法。 要使用梯度下降法找到一個函數的局部極小值，必須向函數上當前點對應梯度（或者是近似梯度）的反方向的規定步長距離點進行疊代搜索。如果相反地向梯度正方向疊代進行搜索，則會接近函數的局部極大值點；這個過程則被稱為梯度上升法。(The gradient descent method is a first-order optimization algorithm, also commonly referred to as the steepest descent method. To find the local minimum of a function using the gradient descent method, an iterative search must be performed to the specified step distance point in the opposite direction of the gradient (or approximate gradient) of the current point on the function. If the search is reversed in the opposite direction to the positive direction of the gradient, it will approach the local maximum point of the function; this process is called the gradient ascent method.)