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Dialog for opening fingerprint files Honors Project bwuzhili comp sci HKBU last update 19/April/2002

一个实现卷积的简单程序，使用分段卷积，使用格式为convII(h，b)(Achieve convolution)

smith预估器添加到PID的控制器当中，解决了控制对象有延迟的影响(Smith predictor is added to the PID controller, solves the influence of time delay control object)

Matlab做的数值计算实验，使用迭代法求解方程的根，算法经典，其中有详细的实验报告和数据，对数值计算课程学习及MATLAB编程有较大帮助。(Matlab done numerical experiments, using iterative ways root, the classical algorithm. including a detailed report and experimental data, the numerical calculation courses and MATLAB programming be helpful.)

通信原理课程设计，包括各种调制，信道编码等。有解释，图形，源码。(Communication theory course design, including modulation, channel coding. Have explained, graphics, source code.)

确定圆形目标：读取图像并转化为二值图像，(Determine the circular target: read image and converting it into binary image,)

It calculates tha Bit Error Rate of the QPSK modulation scheme with Viterbi code K=5

根据直扩原理，首先有随机数发生器产生一系列二进制信息数据（+1，-1），每个信息比特重复Lc次，Lc对应每个信息比特所包含的伪码片数，包含每一比特Lc次重复的序列与另一个随机数发生器产生的PN序列c(n)相乘。然后在该序列上叠加高斯白噪声和形式为i(n)=Acosw0n余弦干扰下次信号，切余弦干扰信号的振幅满足条件A<Lc。在解调器中进行与PN序列的互相关运算，并且将组成各信息比特的Lc个样本进行求和。加法器的输出送到判决器，将信号与门限值0进行比较，确定传送的数据为+1还是-1，计数器用来记录判决器的错判数目。(According to the principle, first some straight expansion random number generator produces a series of binary data (+ 1-1), each information bit repetitive Lc times, Lc for each information bit contains PN code piece count, embraces each bit Lc times repeated sequence and another random number generator produces PN sequence c (n) multiplication. Then in the sequence superimposed on gaussian white noise and forms as I (n) = Acosw0n cosine interference next time signal, cut cosine interfering signal amplitude satisfy conditions A < Lc. In the modem with the cross-correlation operation PN sequence, and the information will comprise the Lc a sample bits peace. The output of the adder judgment device, will signal to compare with threshold 0 data transmitted, determine for+ 1 or-1, counter is used to record the number victimised judgment. )

机器学习中的垃圾邮件分类程序，用matlab做的。从以下链接下载垃圾邮件数据（spam data）：(数据已下载，放在spambase.zip) http://www-stat.stanford.edu/~tibs/ElemStatLearn/index.html 该数据包含57个邮件信息相关的变量，每条邮件可以被分类为垃圾邮件（Y=1）和非垃圾邮件（Y=0）。输出Y的值在文件中每一列的末尾。练习的目标是要预测电子邮件是否为垃圾邮件。 (Machine Learning spam classification procedures, using matlab to do. Data (spam data) from the following link to download the junk mail: (data has been downloaded, put spambase.zip) http://www-stat.stanford.edu/ ~ tibs/ElemStatLearn/index.html The data includes 57 e-mail messages related variables, each message can be classified as spam (Y = 1) and non-spam (Y = 0). Y value of the output end of each column in the file. The goal is to predict exercise email is spam.)

总结了matlab中常用的函数，几乎概括了所有常用函数，共47页(Summarizes the commonly used functions in matlab, almost summarizes all of the usual functions, a total of 47)