搜索资源列表
addline
- ADALINE的字符识别，有图形界面。可以方便使用并了解ADALINE的LMS算法-ADALINE Character Recognition, a graphical interface. Easy to use and understand ADALINE LMS algorithm
extract_yellow_region
- 车牌识别技术422 10.1 系统简介422 10.1.1 车牌定位技术综述423 10.1.2 车牌字符 识别技术综述423 10.2 车牌图像定位与分割算法424 10.2.1 车牌图像的-Vehicle Identification Technology System 422 10.1 422 10.1.1 plates positioning technology on 423 10.1.2 License Plate Recognition Technology 423 10.2 pl
nnd10lc
- Windrow-Hoff学习算法的源程序，实现ADALINE机器的自适应学习，功能用于字符识别，完全界面显示。-Windrow-Hoff learning algorithm source, the realization ADALINE machines adaptive learning, for character recognition function, the interface shows entirely.
AllNeuralNetworkCompute
- 包含6个*.m文件，分别是adline网络，bp网络，hopfiled网络，字符识别，学习速度自适应，和增强型lms算法的六个仿真算法程序，真是我的珍藏，这次全抖出来了。-contains 6 m *. documents were adline network bp network hopfiled network, character recognition, adaptive learning speed, lms and enhanced algorithm simulation alg
zifushibie
- 基于matlab的免疫算法，并实现字符识别功能
car
- 汽车车牌的图像识别。 根据车牌凸角轮廓特征，采用MPP算法进行车牌倾斜校正；采用彩色图像分割方法，最大限度的去除图像噪声干扰；设计了基于神经网络的多种彩色背景车牌字符识别方法，取得了良好的效果。-Image recognition of vehicle license plates. According to plate convex contour feature, the use of MPP plate tilt correction algorithm using color imag
MATLABzifushibei
- 基于MATLAB的车牌识别的设计算法，实现的有车牌定位，车牌字符分割和识别等算法。- In this thesis，the main contents include: First, copes with positioning process of the captured vehicle license plate and then preprocess the positioned license plate Second, based on comparison of gray l
recognition-of-characters
- 采用MATLAB神经网络中的BP网络进行26个英语字母的仿真识别。采用了改进型的BP算法设计了26个字符的模式识别系统。并对该系统进行了训练和测试。-MATLAB neural network in the BP network for 26 English letters of the simulation. The pattern recognition system based on the improved BP algorithm is designed. And training a
TGF
- 在 Windows 环境中用MATLAB实现LMS学习算法，解决T-G-F字符识别问题。-Windows environment using the MATLAB realize LMS learning algorithm to solve the problem of TGF character recognition.
1
- 实验一：基于LMS算法的“苹果-橘子”分类问题 实验二：基于LMS算法的T-G-F字符识别问题 通过以上两个实验，了解ADALINE网络的结构及计算机制，掌握LMS算法，并会利用该算法来解决简单的模式分类问题。1， 学习ADALINE网络的基本结构及其学习机制，并在Matlab中实现 2， 分别对上述两类分类问题进行实现，并根据实验结果完成实验报告 -Experiment 1: Based on LMS Algorithm Apple- Orange classificati
BP神经网络数字识别（matlab2014a）
- 利用BP神经网络识别易拉罐底字符识别，运行前注意阅读算法说明和代码中相对路径的设置。(The BP neural network is used to identify the character recognition of the bottom of the can, and the pre operation attention to the reading algorithm and the setting of the relative path in the code.)