moshishibie-Matlab

先进PID控制matlab仿真源代码，典型实例具体分析说明，通俗易懂。（第四章）(Advanced PID control matlab simulation source code, more typical examples of specific instructions, clear and easy to understand.（Chapter 4）)

显示一张图，point spread function of 1 scatter，需要matlab安装Filed II simulation(show a picture of point spread function of 1 scatter )

A 10th order FIR system, excited by a sum of 5 sinusoids. Assume any numeric values for system coefficients and input signal parameters. The output of the system is corrupted by Gaussian observation noise with zero mean and variance 2 σ v (consider 2 σ v = 0.1 and 1). The estimator has access to the input and noise corrupted output of the system. However, the estimator has no knowledge about the system order, its coefficient values and observation noise variance.

说明：  边缘特征的匹配算法改进研究一篇不错的论文(Edge Feature Matching Algorithm of a good paper)

VC调用matlab画图，需要安装matlab(VC call matlab to draw fig)

三种DOA估计的仿真图，分别是常规波束形成、MVDR和MUSIC。(Simulation Diagrams of Three DOA Estimations)

说明：  模糊PID即自适应PID，通过本程序可实现对平衡车模糊PID的优化控制，针对二阶的传递函数(This procedure can realize the optimal control of fuzzy PID)

说明：  SUSAN边缘检测的Matlab实现代码，用于静态图象的边缘检测，效果要视具体图象来定(SUSAN Edge Detection Matlab code for static images of edge detection, the effect would depend on the specific images to determine)

MATLAB implementation of SPIHT (without Arithmatic coding stage). ％ Performance evaluation : this toolbox VS. SPIHT ％ Test image: lena512.raw ％ bpp SPIHT(dB) This code(dB) ％ 0.1000 29.8107 29.3202 ％ 0.2000 32.7202 32.2514 ％ 0.3000 34.5479 34.0331 ％ 0.4000 35.8422 35.4857 ％ 0.5000 36.8623 36.5939 ％ 0.6000 37.6650 37.3759 ％ 0.7000 38.2581 38.0491 ％ 0.8000 38.9390 38.7058 ％ 0.9000 39.5218 39.3437 (MATLAB implementation of SPIHT (without A rithmatic coding stage). Performance evalua% tion : this toolbox VS. SPIHT%% Test image : lena512.raw%% bpp SPIHT (dB) This code (dB)% 0. 1000 29.8107 32.7202 0.2000 29.3202% 32.2514% 0.3000 0.4000 34.5479 34.0331% 35.8422 35.485 7% 0.5000 0.6000 36.8623 36.5939% 37.6650 37.3 759% 38.0491% 0.7000 0.8000 38.2581 38.9390 38 .7058 0.9000 39.5218 39.3437%)

HMM,DBN Function matlab tool box