cannysuanzi

agglomorative clustering

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. )

singnal processing useful for electronics

fusion code .. matlab

光反馈产生混沌激光，并画出混沌激光的时序图、自相关曲线和相位图，并计算出混沌的带宽(Optical feedback chaotic lasers, laser chaos and draw a timing diagram, autocorrelation curves and phase diagram, and calculates the bandwidth of Chaos)

这是我自己收藏的两个源代码程序，比较有用，希望对大家有所帮助(This is my own collection of two source code procedures, more useful, I hope all of you to help)

阵列信号处理，波达方向估计算法对比，包括beamforming算法，capon算法和MUSIC算法(Array signal processing, direction of arrival estimation algorithm comparison, including beamforming algorithm, capon algorithm and the MUSIC algorithm)

哈夫曼树：利用哈夫曼编码进行通信可以大大提高信道利用率，缩短信息传输时间，降低传输成本(Huffman tree)

说明：  本程序主要是为初学者提供，里面介绍了怎样用MATlab观察一个信号的波形 星座图 频谱 等(this program is to provide beginners. on the inside with what MATlab observation of a signal waveform constellation spectrum)

北京历年降水量线性模型分析——matlab，跟新到2012年(Calendar Beijing precipitation linear model analysis- matlab, with the New 2012)