hw01_hcyang

在matlab开发环境下实现m-shift图像目标跟踪算法，其中还有一篇比较好的参照论文(Development environment in the matlab m-shift image to achieve target tracking algorithm, of which there are a good reference paper)

说明：  SVPWM仿真，在matlab里面画的仿真图，可以参考参考，学习学习。(SVPWM simulation, the simulation in matlab figure inside the painting, see reference, learning to learn.)

说明：   系统模型转换(System Model Conversions)

近红外光谱标准正态变量变换处理方法，主要是消除固体颗粒大小，表面散射以及光程变化对漫反射光谱的影响。(Near infrared spectrum standard normal variable transform processing method, mainly eliminate the solid particle size, surface scattering and the change of optical path of diffuse reflection spectra. )

C++大作业，编写一个account类实现基类派生类之间的各种关系。主要用于初学者对于类的理解。(C++ big job, write a class that implements account the various relationships between the base class derived class. The main class for beginners to understand.)

说明：  基于ISO532A计算响度；播放声音；倍频程声压级计算(Calculation of loudness, playing sound, octave sound pressure level based on iso532a)

FTF自适应算法 求：自适应滤波器的两个权值ω0 (n)和ω1(n)分别收敛于0.2和0.7的收敛轨迹，并与LMS算法进行对比。(FTF adaptive algorithm Requirements: two weights ω0 is (n) of the adaptive filter and ω1 (n) converges to 0.2 and 0.7, convergence trajectory, and compared with the LMS algorithm.)

heat equation mixte parameters matlab file

BP（Back Propagation）网络是一种按误差逆传播算法训练的多层前馈网络，是目前应用最广泛的神经网络模型之一。 BP网络能学习和存贮大量的输入-输出模式映射关系，而无需事前揭示描述这种映射关系的数学方程。 它的学习规则是使用最速下降法，通过反向传播来不断调整网络的权值和阈值，使网络的误差平方和最小。BP神经网络模型拓扑结构包括输入层（input）、隐层(hide layer)和输出层(output layer)。 通过对信息的提取以及记忆，用作分类、聚类、预测等。 (BP (Back Propagation) network is a pre-press error back propagation algorithm Multilayer feedforward network, is one of the most widely used neural network model. BP network can learn and store a large amount of input- output mode mapping without prior reveal mathematical equations that describe the mapping relationship. It s learning rule is to use the steepest descent method, by reverse spread to constantly adjust the network weights and thresholds and the minimum sum of squared error of the network. BP neural network topology comprises an input layer (input), hidden layer (hide layer) and an output layer (output layer). By extracting information and memory, it is used as classification, clustering, prediction.)

企鹅动画，实现企鹅向前向上运动，并且有月亮和枫叶动(Penguin animation, penguins move forward to achieve upward movement, and has the moon and the Maple Leaf movement)