polynomial

一个可图片中文字进行识别的matlab实例程序，具有很不错的识别率(A picture in the text to identify the matlab example programs, with very good recognition rate)

说明：  基于MATLAB的地震数据处理工具箱，包含对地震数据的读取、绘图、滤波、变换功能(semistic data processing toolbox based on matlab.It will help you to read su style semistic data and show to the screen,as well as do some transform and filtering.)

说明：  they are matlab code for evolutionary strategy (ES), (ES(1+1), ES(1,1),ES(mu,lambda),ES(mu+lambda), I hope they are useful for you

L4_1.m: SVD轉換(程式) L4_2.m: 影像轉換的能量集中能力(程式) L4_3a.m: 小波轉換之多重解析架構(程式) L4_3b.m: 小波轉換係數與影像的方向性(程式) energy.m: 能量集中(函式) L4_1.bmp: 影像檔 L4_2.bmp: 影像檔 L4_3b.bmp: 影像檔 woman.mat: Matlab的矩陣變數檔 (L4_1.m: SVD conversion (program) L4_2.m: image conversion of energy to focus capacity (program) L4_3a.m: the multi-resolution wavelet transform architecture (program) L4_3b.m: wavelet transform coefficient and the direction of the image (the program) energy.m: energy concentration (function) L4_1.bmp: image file L4_2.bmp: image file L4_3b.bmp: image file woman.mat: Matlab matrix variable file)

ZigBee network wireless sensor networks This document describes software examples for the CC2430 System-on-Chip solution for IEEE 802.15.4/ZigBee. It also describes the necessary hardware and software to run the examples, and how to get started. The software examples are able to run on the CC2430EM or CC2430-CC2591EM mounted on SmartRF04EB.

图像处理函数大全，包括图像增强、滤波、小波变换以及类型转换等。(Image processing function Daquan, including image enhancement, filtering, wavelet transform and type conversion.)

指纹识别预处理 matlab程序 包括 指纹增强 二值化 细化 等步骤(Fingerprint preprocessing including fingerprint enhancement matlab program binary refinement step, etc )

artificial bee colony algorithm

the MATLAB codes for the well-known modulation techniques.

首先用matlab实现了识别算法的仿真，因为只是对特定的数字组合的识别，所以非常的简单，放弃采用比较复杂的识别算法，采用最普通的像素比较的识别算法。(First, to achieve the recognition algorithm using matlab simulation, because the only identification of a specific combination of numbers, it is very simple, give up the use of more complex recognition algorithms compare the most common pixel identification algorithm.)