Facial-feature-detection

说明：  自适应共振理论网络 用来进行模式分类联想记忆效果很好，误差率极低，能正确识别(Adaptive Resonance Theory networks used for pattern classification associative memory with good results, the error rate is very low, able to correctly identify)

ini kode yang bagus..coba anda bayangkan.sebuah kode bisa anda dapatkan secara gratis..coba saja ,,akan keluar gambar yang bgus di kode ini

比较全面的介绍matlab处理图像图形的命令，以及相关的说明和实例(More comprehensive introduction matlab image processing graphics commands, and related instructions and examples...)

说明：  conjugate gradient for solving system of equations

ARROW (5/20/2009) Draw a line with an arrowhead. ARROW(Start,Stop) draws a line with an arrow from Start to Stop (points should be vectors of length 2 or 3, or matrices with 2 or 3 columns), and returns the graphics handle of the arrow(s). By itself, ARROW will use the mouse to allow selection.

一个粒子滤波的程序，包含了三种采样策略，可以根据自己的需要选择采样策略。(a particle filter process, contains three sampling strategy, according to their own needs select sampling strategy.)

please give me a code for this ieee paper

基于神经网络观测器的单关节机械手反演控制。将估计速度代替实际速度，可实现无需实际速度信号检测的控制(Single-joint robot based on neural network observer inversion control. Instead of the actual speed of the estimated velocity can be achieved without the control of the actual speed signal detection)

Algo3-5.c C program for implementing Algorithm 3.5 Algorithm translated to C by: Dr. Norman Fahrer IBM and Macintosh verification by: Daniel Mathews NUMERICAL METHODS: C Programs, (c) John H. Mathews 1995 To accompany the text: NUMERICAL METHODS for Mathematics, Science and Engineering, 2nd Ed, 1992 Prentice Hall, Englewood Cliffs, New Jersey, 07632, U.S.A. Prentice Hall, Inc. USA, Canada, Mexico ISBN 0-13-624990-6 Prentice Hall, International Editions: ISBN 0-13-625047-5 This free software is compliments of the author. E-mail address: in "mathews@fullerton.edu" Algorithm 3.5 (Gauss-Seidel Iteration). Section 3.7, Iterative Methods for Linear Systems, Page 187

matlab图像处理实例详解chap7——图像分割技术(matlab image processing examples explain chap7- Image Segmentation)