MPC

L3_1.m: 純量量化器的設計(程式) L3_2.m: 量化造成的假輪廓(程式) L3_3.m: 向量量化器之碼簿的產生(程式) L3_4.m: 利用LBG訓練三個不同大小與維度的碼簿並分別進行VQ(程式) gau.m: ML量化器設計中分母的計算式(函式) gau1.m: ML量化器設計中分子的計算式(函式) LBG.m: LBG訓練法(函式) quantize.m:高斯機率密度函數的非均勻量化(函式) VQ.m: 向量量化(函式) L3_2.bmp: 影像檔 lena.mat: Matlab的矩陣變數檔 (L3_1.m: scalar quantizer design (the program) L3_2.m: quantitative result of the false contour (the program) L3_3.m: Vector quantizer code book of the generation (the program) L3_4.m: training in the use of LBG three different size and dimension of the code book and separate VQ (program) gau.m: ML quantizer design in the denominator of the calculation formula (function) gau1.m: ML quantizer design in the calculation of molecule-type ( function) LBG.m: LBG training method (function) quantize.m: Gaussian probability density function of the non-uniform quantization (function) VQ.m: vector quantization (function) L3_2.bmp: image file lena.mat: Matlab matrix variable file)

说明：  本文介绍了控制系统中的经典问题— — —倒立摆及其基本原理, 简要介绍了 Ma tlab中倒立摆控制的实现方法。由于倒立摆的研究具 有重要的工程背景,本文结合了二级倒立摆的 ma tlab仿真,实现二自 由度机器人 PD控制的 ma tlab仿真 ,取得了较好的效果。(This article describes the classic problem of the control system--- inverted pendulum and its basic principles, a brief introduction Ma tlab the inverted pendulum control method. The inverted pendulum has important engineering background, this paper combines the ma tlab double inverted pendulum simulation, to achieve two degrees of freedom robot ma tlab PD control simulation, and achieved good results.)

MRS Water Suppression.

Code for Content based image retrieval

用遗传算法和模拟退火算法解决TSP问题，希望能够帮到你(Solve TSP using genetic algorithms and simulated annealing algorithm)

Leach-c , Sensor network routing protocol.

雷达系统设计matlab仿真，包括雷达模糊函数，脉冲压缩，面杂波和体杂波，动目标显示和杂波抑制，相控阵，目标跟踪，电子对抗，雷达截面积，高分辨率合成孔径雷达。(Matlab Simulations for Radar Systems Design)

This function Simulates the swing equation of a one-machine system and returns the critical clearing time for stability.

经典的MUSIC算法，由特征值分解得到噪声子空间，再进行谱峰搜索(Classic MUSIC algorithm, the eigenvalue decomposition noise subspace, then the peak search)

An implementation of AVL tree very useful for understanding searching in graph.