rtrl

一个中科院博士生的关于粒子滤波的博士论文，对相关人员有重大参考价值(A Chinese Academy of Sciences doctoral dissertation on the particle filter, the relevant personnel have significant reference value)

有生物信息学编程实例，Matlab，欢迎学分子的战友可以学习使用(Bioinformation)

针对20个已知类别数据，前15个训练样本和带刺的5个样本，通过该程序可识别出待测的样本属于哪一类。(Data for the 20 known types, the first 15 training samples and barbed 5 samples can be identified by the program which type of samples tested.)

非线性调频信号的产生，画出了群延迟与调频曲线图，并做了脉冲压缩处理，比较了加窗处理与不加窗处理的区别(Nlfm signal generation, draw the group delay and frequency curve, and the pulse compression processing, compared with windows and window processing difference )

自己编程实现对通道里的细胞的跟踪，标注，计算，并计算细胞的面积、周长、个数、并能判断2种细胞(Their programming implementation of the cells in the channel tracking, tagging, computing, and calculate the cell area, perimeter, number, and can determine two kinds of cells)

　　　综合运用数字信号处理的理论知识进行生物医学信号分析与处理，实现ECG信号的频谱分析，基线漂移检测等，设计滤波器实现心电信号的滤波，滤去高频和低频干扰，加深理解信号预处理的原理、方法和步骤。本设计的主要内容是设计一个ECG信号频谱分析与处理系统，实现ECG信号的增强，得到相对纯净的ECG信号。(Integrated use of theoretical knowledge of digital signal processing in biomedical signal analysis and processing, implementation of ECG signal spectrum analysis, the baseline drift detection, design of filter realizes the ECG signal filtering, filter the high frequency and low frequency interference, deepen understanding, the principle of the signal preprocessing methods and steps. The main content of this design is to design a ECG signal spectrum analysis and processing system, realizes the ECG signal enhancement, get relatively pure ECG signal. )

详解MATLAB 数字信号处理[张德丰][程序源代码] 书<<MATLAB 数字信号处理[张德丰]>>全部采用了MATLAB语言编程实现，并结合实例对算法程序进行验证和分析。其中详细讲解了信号的分析基础、系统模型及数据采集分析、信号的变换、模拟滤波器、IIR滤波器设计、FIR滤波器、MATLAB的其他滤波器、随机信号及参数建模、信号在小波分析与处理中的应用等，绍MATLAB在数字信号中的具体应用。 数字信号处理的工程设计人员参考。 (MATLAB source code, from the book"Digital signal processing-using MATLAB" by the Zhang Defeng.)

data mining algorithm

说明：  io例程希望有帮助io例程希望有帮助io例程希望有帮助(io routines want to help io routines want to help io routines want to help)

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 )