SUI-JI-GONG-ZHENG

matalb经典算法，包括代数方程组的解法，微分方程实验，优化问题实验(matalb classical algorithms, including the solution of algebraic equations, differential equations experiment, experimental optimization)

波浪中船舶运动的仿真及预报研究 船舶运动数学模型(Wave the ship motion simulation and forecasting of ship motion mathematical model)

opamp simulink in matlab

计算机视觉structure from motion的代码文件(Computer vision structure from motion code file)

带多个检测函数,引力算法源代码,解决函数的极值问题。(With multiple detection function, gravitation algorithm source code, to solve the function extreme value)

DSP有限字长效应分析，对系数量化给系统带来的部稳定因素进行分析

（一）时域采样及其频谱 一．实验目的:1.熟悉Matable的实验环境,并学会 如何利用其进行对信号处理进行图形分析. 2.编程计算于模拟信号的连续频谱和离散采样信号的连续频谱,实现时域采样及其频谱分析,充分理解时域采样的特点及定理,并在实验过程中体会奈奎斯定理. 二．实验环境: MATABE软件平台 ((1) domain and a spectrum. Experimental purposes : 1. Matable familiar with the experimental environment, and learn how to use their right for signal processing graphics for analysis. 2. Programming from the calculation of continuous analog signal spectrum and from the San continuous sampling signal spectrum to achieve sampling and time-domain analysis of the spectrum, the time-domain fully understand the characteristics and sampling theorem. and the experimental process Experience Naikuishi theorem. 2. Experimental environment : MATABE software platform)

现代数字信号处理，本章主要介绍滤波器相关内容(advance digital signal processing)

坐标转换（四参数） [row col]=size(source) for i=1:row u(i)=source(i,2) v(i)=source(i,3) x(i)=source(i,4) y(i)=source(i,5) B(2*i-1,1)=1 B(2*i-1,2)=0 B(2*i-1,3)=u(i) B(2*i-1,4)=-v(i) B(2*i,1)=0 B(2*i,2)=1 B(2*i,3)=v(i) B(2*i,4)=u(i) L(2*i-1,1)=x(i) L(2*i,1)=y(i) end X=inv(B *B)*(B *L) Txy=[X(1) X(2)] xzjz(1,1)=X(3) xzjz(1,2)=-X(4) xzjz(2,1)=X(4) xzjz(2,2)=X(3) [row1 col1]=size(target) for i=1:row1 u1(i)=target(i,2) v1(i)=target(i,3) d=[u1(i) v1(i)] md=Txy+xzjz*d end end (Coordinate conversion： [row col]=size(source) for i=1:row u(i)=source(i,2) v(i)=source(i,3) x(i)=source(i,4) y(i)=source(i,5) B(2*i-1,1)=1 B(2*i-1,2)=0 B(2*i-1,3)=u(i) B(2*i-1,4)=-v(i) B(2*i,1)=0 B(2*i,2)=1 B(2*i,3)=v(i) B(2*i,4)=u(i) L(2*i-1,1)=x(i) L(2*i,1)=y(i) end X=inv(B *B)*(B *L) Txy=[X(1) X(2)] xzjz(1,1)=X(3) xzjz(1,2)=-X(4) xzjz(2,1)=X(4) xzjz(2,2)=X(3) [row1 col1]=size(target) for i=1:row1 u1(i)=target(i,2) v1(i)=target(i,3) d=[u1(i) v1(i)] md=Txy+xzjz*d end end )

Its a matlab code for object detection, it does back-projection and morphology filtering to get ROI and use blob detection technique for BBox