juanjijiaozhi

Signal models, echo cancelations adaptive filtering

为了解决二进制CS而编写的算法，使用了用l2范数最小化(an algorithm for binary CS,using l2 norm)

利用FAST-ICA进行谐波分解，过程简单，数据可靠(FAST-ICA harmonic decomposition, the process is simple, reliable data)

软件程序按照发射端所掌握的各用户信道状态信息的程度共分为两部分：即完整信道状态信息(CSIT)和部分信道状态信息(CSIP)。其中，每一部分都包括预编码(precoding)和用户调度(scheduling) 在CSIT中，precoding又按照各用户的数据流数分为单数据流和多数据流两种情况。在每种情况下，首先考察了不同预编码算法的性能表现，包括两种ZF、MMSE、SINR、SLNR。之后又考察了功率分配算法的性能表现（文件名中含有PD表明其含有功率分配的过程）。按照不同指标进行功率分配的，在文件名中进行了区分，如PD_CN代表以信道范数为参考指标进行功率分配。Scheduling部分首先观察了RoundRobin、MaxH和MMSLNR三种算法的性能对比。之后在Kc和Round部分分别观察了不同预选用户数和不同最大替换轮数下MMSLNR算法的表现。 在CSIP中，只对各用户单数据流的情况进行了仿真。采用的预编码算法主要有DSLNR（即直接运用CSIT下的预编码算法）、ESLNR（即对SLNR进行均值计算的，在CSIP中，引入均值计算的与SLNR有关的算法，其文件名中都有modified以示区别）、EMMSE（即陈明老师那边的那篇文章中的预编码算法）。Scheduling中也只是简单的观察了RoundRobin、MaxH、DMMSLNR和EMMSLNR（前者没有均值计算，后者有）的性能对比。(The degree of channel state information for each user software program in accordance with the master transmitter consists of two parts : the complete channel state information (CSIT) and partial channel state information (CSIP). Wherein , each of which comprises a pre- coding (precoding) and the user scheduling (scheduling) In CSIT in , precoding and each user according to the number of data streams into a single data stream and multiple data streams in both cases . In each case , first examine the performance of different pre- coding algorithm, including two ZF, MMSE, SINR, SLNR. After they inspected the power allocation algorithm performance ( file name contains PD showed that it contained power allocation process ) . According to different indicators for power distribution , make a distinction in the file name , such as PD_CN representative channel norm-referenced index for power distribution . Scheduling section first observed the performance comparison RoundRobin, MaxH and MMSL)

我设计的遗传算法代码，希望大家能够喜欢，谢谢啊(I design the genetic algorithm code, we want to like, thank ah)

针对均匀线形阵列的阵列波束综合问题，并把这一问题描述成一个凸优化问题。针对更普适的情况。 (For array pattern synthesis problem, and describe it as a convex optimization problem.)

D-S证据理论在数据融合上matlab仿真程序 (DS evidence theory data fusion matlab simulation program)

通过恢复低秩矩阵得到显著性图，其中详细的运用了mean-shift算法，可以很好的了解mean-shift算法的使用，同时还包含了RPCA算法。(Significantly through the recovery of low rank matrix diagram, which detailed the use of mean-shift algorithm, can be a very good understanding of the use of the mean-shift algorithm, also contains RPCA algorithm.)

Matlab source code for interpolation 5

This is the first matlab code of chuck