Control_IMP

说明：  人工神经网络BP算法的MATLAB实现--源代码(Artificial neural network BP algorithm MATLAB implementation- the source code)

QR码作为一种可高速、全方位识别的二维条码,已经在各行各业中得到了应用,并具有很大发展潜力.本文针对QR码图像的识别过程中可能遇到的图像噪声干扰、QR码占实际拍摄图像的一部分、倾斜、几何失真等问题进行了研究,提出了通过改进型中值滤波去除噪声,使用QR码符号特性定位并对倾斜图像进行旋转,对失真不严重的图像采用控制点变换和双线性插值方法进行几何校正.实验证明, 本文的方法简单有效, 可以用于提高条码的正确识别率.(As a high-speed, full identification of the two-dimensional bar code, QR code has been applied in all walks of life, and also has great potential for development. In this paper, aiming at QR code image recognition process may be encountered in noise interference, QR code accounting for the actual captured image just a part, slant, geometric distortion, and other issues have been studied, put forward through improved median filter to remove noise, use QR code symbol characteristics to locate and rotate the tilted image, distortion which is not serious use control-point transform and spatial bilinear interpolation method for geometric correction. The results show that this method is simple and effective, can be used to improve the QR code correct recognition rate.)

This Source Code for Image Segmentation and applying the threshold at image

：主要介绍m序列、Gold序列、Kasami序列和JPL序列的生成原理及其MATLAB的实现，并介绍如何用MATLAB中 Simullnk对其进行硬件仿真，给出了相应自相关和互相关结果。(: The main introduction m sequence, Gold sequences, Kasami sequences and sequences generated JPL principle and the realization of MATLAB, and introduce how to use MATLAB in their Simullnk hardware simulation, the corresponding auto-correlation and cross-correlation results.)

学习用matlab求解最优化问题，提高matlab实际应用能力(Learn to use matlab to solve the optimization problem, the ability to improve the practical application of matlab)

it will compute the echo cancellation using thew subadaptive filter with main filter length 256 and sub adaptive filter length 64

BP神经网络：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)。(BP neural network: a Press the front back propagation algorithm to train multilayer feedforward network is one of the most widely used neural network model. BP network can learn and store large amounts of input- output mode mappings without prior reveal mathematical equations that describe this map. It' s learning rule is to use the steepest descent method, through a reverse spread to constantly adjust the network weights and thresholds, so that the minimum squared error of the network. BP neural network topology, including the input layer (input), hidden layer (hide layer) and output layer (output layer).)

说明：  基于RFE-SVM进行两类的特征提取算法，能够提取出最佳的变量，已经经过测试，绝好的算法(two kinds of feature extraction algorithm based on RFE-SVM, it can extract the best variables,it has been tested,it is the best algorithm)

基于偏微分框架的全局快速活动轮廓分割模型(Framework based on partial differential global fast active contour segmentation model)

Level Set Based Image Segmentation