sensorless_MRAS

Simple steganography code to hide text inside image The code include embedding and extracting procedure

对图像进行多级小波分解、重构。可用于提取图像的背景噪声(Multi-level image wavelet decomposition and reconstruction. Can be used to extract image background noise)

以matlab实作histgram equalizatuin(To implement histgram equalizatuin matlab)

本MATLAB是用来提取语音信号的MFCC特征，可对.wav文件进行特征提取(The MATLAB is used to extract the MFCC features of speech signals,.Wav files can be extracted)

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)

用matlab编写的用于转子动力学分析的有限元程序，可实现转子临界转速和振型分析、稳态响应和瞬态响应分析等功能。()

对信号进行傅里叶变换，并绘出频谱图，功率谱，对数谱等。然后对信号进行反傅里叶变换恢复出原始信号，并绘出其各种谱图(The Fourier transform of the signal, and plot the frequency spectrum, power spectrum, the number spectrum. And inverse Fourier transform to recover the original signal and plot its various spectrum signal)

粒子群优化算法代码，用于matlab优化计算(Particle swarm optimization algorithm code)

有限差分法的Matlab程序（椭圆型方程）(Finite difference method in Matlab (elliptic equations))

说明：   提供的文件包含matlab的多个图象处理程序,其中有图象分割,以及图象边缘提取的.(the document contains a number of Matlab image processing procedures, which are image segmentation, and Image Edge Extraction.)