Synopsis

matlab最优化程序包括 无约束一维极值问题 进退法 黄金分割法 斐波那契法 牛顿法基本牛顿法 全局牛顿法 割线法 抛物线法 三次插值法 可接受搜索法 Goidstein法 Wolfe.Powell法 单纯形搜索法 Powell法 最速下降法 共轭梯度法 牛顿法 修正牛顿法 拟牛顿法 信赖域法 显式最速下降法(matlab optimization program includes one-dimensional extremum problem without constraint advance and retreat method Fafei Bo Fibonacci golden section method the basic Newton method, global Newton method Newton secant parabola method acceptable to the three interpolation methods Wolfe.Powell search method Goidstein simplex method Searching Powell steepest descent method conjugate gradient method modified Newton method Newton Newton trust region method to be explicitly steepest descent method)

Calculate a gradient by using a mask (sqrt(R² + I² ).(Calculate a gradient by using a mask (sqrt(R² + I² ).)

自己编的基于霍夫曼编码以及解码的程序，供大家分享(Own compilation based on Huffman coding and decoding procedures for share)

说明：  数字信号处理教程：MATLAB释义与实现/数字信号处理教程：MATLAB释义与实现( Digital Signal Processing Tutorial: MATLAB Interpretation and Implementation/digital signal processing tutorial: MATLAB Interpretation and Implementation)

语音识别的dtw改善算法 语音处理 识别(Speech recognition speech processing algorithms to improve recognition dtw)

目标跟踪：对目标的运动建立较为简单的线性模型，并用最小二乘估计对其参量进行估计，从而推出目标轨迹。(Target-Tracking：the simulation of tracking target by linear least squares estimates on the Matlab platform.)

STBC编码的一个MATLAB程序，有详细注解(a matlab code for STBC with detailed notes)

kalman filter for tracking

包括脚本文件和函数文件形式，包括AHP，因子分析，回归分析，聚类分析，到达过程是的泊松过程，欢迎大家下载学习，粒子图像分割及匹配均为自行编制的子例程，最小均方误差（MMSE）的算法，基于负熵最大的独立分量分析，用于特征降维，特征融合，相关分析等。( Including script files and function files in the form, Including AHP, factor analysis, regression analysis, cluster analysis, Arrival process is a Poisson process, Welcome to download the study, Particle image segmentation and matching subroutines themselves are prepared, Minimum mean square error (MMSE) algorithm, Based on negative entropy largest independent component analysis, For feature reduction, feature fusion, correlation analysis.)

连续曲线近似地刻画或比拟平面上离散点组所表示的坐标之间的函数关系的一种数据处理方法。用解析表达式逼近离散数据的一种方法(Continuous curve approximation to characterize or compare groups of discrete points on the plane expressed by a function of the relationship between the coordinates of a data processing method. Approximation using the analytical expression of a method of discrete data)