Computational-Colour-Science-Using-MATLAB---Steph

使用Matlab语言完成《数值计算方法》中的Romberg（龙贝格）积分公式，程序可以根据用户输入的积分上下限、误差容限及表达式实现Romberg积分。(Using Matlab language to complete " numerical methods" in the Romberg (Romberg) integral formula, the program based on user input limits of integration, error tolerance and expression implementations Romberg integration.)

基于matlab的fir数字滤波器的模拟和仿真图形，源代码 程序 用matlab打开运行即可，希望大家喜欢，谢谢！(failed to translate)

说明：  本程序实现多模态故障检测与故障诊断，用的方法是LPP_GMM，GMM是用的FJ算法，效果很好(This procedure realize multimodal, fault detection and fault diagnosis method is LPP_GMM, GMM FJ algorithm is used, the effect is very good )

实现希尔伯特-黄变换的功能，并带有一段测试数据。希尔伯特-黄变换是使用EMD分解将信号分解为本征模态函数（IMF），然后求得IMF分量的瞬时频率。其对于非稳态和非线性信号具有优良的效果。(The function plot_hht is a realization of the Hilbert-Huang transform (HHT). The HHT decomposes a signal into intrinsic mode functions (or IMFs), and obtain the instantaneous frequency data. It is designed to work well for data that are nonstationary and nonlinear.)

93C66 application notes

合成孔径雷达，距离多普勒算法下的，简单点目标欺骗干扰,matlab仿真程序。(Range_Dopplor algorithm of deception jamming about Synthetic Aperture Radar. )

包括 MUSIC算法，ESPRIT算法 ROOT-MUSIC算法，IDW距离反比加权方法，ofdm系统仿真 含16qam调制 fft 加窗 加cp等模块。( Including the MUSIC algorithm, ESPRIT algorithm ROOT-MUSIC algorithm, IDW inverse distance weighting method, ofdm system simulation including 16qam modulation fft windowing modules plus cp.)

说明：  最速下降法是迭代法的一种,可以用于求解最小二乘问题(线性和非线性都可以)。在求解机器学习算法的模型参数，即无约束优化问题时，梯度下降（Gradient Descent）是最常采用的方法之一，另一种常用的方法是最小二乘法。在求解损失函数的最小值时，可以通过梯度下降法来一步步的迭代求解，得到最小化的损失函数和模型参数值。反过来，如果我们需要求解损失函数的最大值，这时就需要用梯度上升法来迭代了。在机器学习中，基于基本的梯度下降法发展了两种梯度下降方法，分别为随机梯度下降法和批量梯度下降法。(The steepest descent method is a kind of iterative method, which can be used to solve the least squares problem (both linear and nonlinear). In solving the model parameters of machine learning algorithm, that is, unconstrained optimization, gradient descent is one of the most commonly used methods, and the other is the least square method. When solving the minimum value of loss function, the gradient descent method can be used step by step to get the minimum value of loss function and model parameters. Conversely, if we need to solve the maximum value of the loss function, then we need to use the gradient rise method to iterate. In machine learning, two kinds of ladders are developed based on the basic gradient descent method)

GPSC/A信号捕获算法，matlab程序，没有别的说明了。(GPS signal acquisition algorithm, matlab program)

this is matlab based eee project