kftool_matlab10

FPEXTRACTDEMO 指纹特征提取演示程序 一个完整的指纹特征提取程序。包括常用的所有算法... 选项： - Centralize: 二值化图像，计算中心点 - Crop: 图像修剪 - Sectorize: 可视化扇形 - Normalize: 归一化输入图像 - Gabor filters: 可视化Gabor滤波器 - Convolute: 计算输入图像和Gabor滤波器的convolution - Features: 特征可视化 - FingerCode: 在数据库中加入该指纹 - Check: 指纹匹配(Fingerprint Feature Extraction FPEXTRACTDEMO demo program a complete fingerprint feature extraction procedures. Including all the algorithms commonly used options ...:- Centralize: binary image, Center Point- Crop: image pruning- Sectorize: Visualization fan- Normalize: normalized input image- Gabor filters: Visualization Gabor Filter- Convolute: Calculation of the input image and Gabor filter convolution- Features: Characteristics of visualization- FingerCode: in the database to join the fingerprint- Check: Fingerprint matching)

matlab6.5辅助小波分析与应用，主要介绍小波变化与在matlab下的实现。一本很不错的书。(Auxiliary matlab6.5 and application of wavelet analysis, wavelet introduce major changes and implementation at the matlab. A very good book.)

现在通信系统仿真中的锁相环技术，给出仿真程序以及后处理(Communication system simulation is now PLL technology, the simulation process and post-processing)

遗传算法和神经网络很重要的程序 有关这个的内容 希望你不要错过(Genetic algorithms and neural networks are very important program hope you do not miss on this content)

Algorithm/Flowchart for C

车速估计的重要参考文献，包括人工智能法、卡尔曼滤波、观测器法等(Important Chinese references of velocity estimation, like artificial intelligence, observer, Kalman)

本文件是DTMF信号采用卷积法进行解码的源程序，可以解码到DTMF信号的原始频率。(This document is a DTMF signal is decoded by convolution of the source, you can decode the DTMF signal to the original frequency.)

MATLAB开发的常用的数值分析代码,用以解决常用的数值分析组合，集成设计(MATLAB Athoritic )

说明：  基于MATLAB的FIR带阻数字滤波器的设计 由于生物医学信号处理过程中易混入50Hz噪声的特点，本文利用程序设计法和FDATool设计法(Based on the MATLAB FIR digital filters with resistance of biomedical signal processing design due process characteristics of noise, with isolator using the program design method and FDATool design method)

这是一份关于matlab曲线拟合的文章，供大家学习~~180K(This is an article on the matlab curve fitting for them to learn ~ ~ 180K)