Txt2Access

With 2 Hidden Layer Backpropagation Using Matlab

For using this code need to use signal toolbox and general toolbox in your matlab Inpainting using sparse regularization. Consider the pepper image with many missing pixels. Assume that the image is noisy-free. (a) Inpaint the image by using orthogonal wavelet sparsity. (b) Inpaint the image by using a different sparsity prior. Based on the outputs, it is clear that the inpainting result obtain by Sobolev is much better than other methods (i.e. Orthogonal wavelet sparsity and Invariant wavelet sparsity).

可以读取yuv文件，输入文件夹名字、图像尺寸、帧数等，为处理yuv文件的前提(Input: filename- YUV sequence file dims- dimensions of the frame [width height] numfrm- number of frames to read startfrm- [optional, default = 0] specifies from which frame to start reading with the convention that the first frame of the sequence is 0- numbered)

Blasius Equation for Boundary layer theory problems. For calculating the boundary layer thickness and the velocity profile in a free stream in a pipe.

三相全桥SPWM控制逆变电路的研究 1、输入电压： ； 2、输出电压：正弦波电压，其正幅值 ； 3、负载：纯电阻性负载， ； 4、结合仿真波形和数据分析调频调压的控制原理。(Research on Three-phase Full Bridge SPWM Controlled Inverter Circuit)

说明：  模拟退火算法在许多事例中的应用例程，希望对大多初学者有所帮助(mon itu ihu osu anf aza ilich engzhongd e yngy ong)

在屏幕上出现一个圆心沿正弦虚线轨迹移动的实心圆。(In the center of a circle appears on the screen a dotted line along the sinusoidal trajectory moving solid round.)

Introduction to Matlab: Basic Matlab Commands and Syntax for beginners and experts as well. enjoy

This code applies local histogram equalization on an input image with a view to improve its contrast ratio. The image is read, converted to grayscale and resized with the inbuilt function of MATLAB. The window size may be changed, however, the window shift is as per size of the window. The output is definitely a better contrast image as compared to the input but checkerboard effect is evident.

采用PCA提取人脸特征,先计算M个图像的平均值脸，再求出各特征值脸。(Using PCA for face feature extraction, first calculate the average face image of M, and then find the face value of each characteristic.)