GauPydDec

插值算法，具体使用方向为高斯插值，Kriging插值可以参考(Interpolation algorithm, the specific direction of the Gaussian interpolation, Kriging interpolation can refer to)

OFDM正交子载波调制，一种为BPSK，一种为QPSK，都经历串并转换后IFFT，加高斯白噪声信道而后反向解调。(modulate by BPSK&QPSK then use OFDM)

产生一个有带内相位噪声，毛刺噪声，白噪声的LO信号。(creative a LO signal with in band phase noise， spurs and noise floor.)

matlab 的一些程序源码matlab 的一些程序源码matlab 的一些程序源码(Some source code matlab matlab some program source code of some program source code matlab)

lab3 : Spatial Filtering

对经典协议LEACH的改进版本，可以出图3个，对初学很有帮助，大家有兴趣的可以看看。(LEACH agreement on an improved version of the classic, you can plot three, very helpful for beginners, we are interested can look at.)

BP与GA-BP算法用于温度补偿函数拟合的比较(For the comparison of temperature compensation function fitting BP and GA-BP algorithm)

matlab code for lqrdmdfe algorithm in mimo ofdm systems for 4x4 and 8x8 systems.

【转】协同过滤代码，用于推荐系统，包括基于项目和基于用户两种情况。实现基于用户和基于项目的协同过滤算法。 实验所用数据为MovieLens – a web-based movies recommender system with 43,000 users & over 3500 movies. 保存在ga.mat文件用，由于ga.test测试集过于庞大，全部用来计算的话耗时庞大，所以每次计算时随机选择部分，具体函数的使用请参照probar.m。我所得到的实验结果保存在results1-results8.mat里面。([Turn] collaborative filtering code for the recommended system, including project-based and user-based two cases. User-based and project-based collaborative filtering algorithm. Experimental data for MovieLens- a web-based movies recommender system with 43,000 users & over 3500 movies. Saved in ga.mat file with Because ga.test test set is too large, all used to calculate the time-consuming massive, so every time The calculated random selection portion, the use of the specific function, please refer to probar.m. I obtained experimental results are saved inside results1-results8.mat.)

说明：  利用计算机仿真运算,将问题的求解过程转换成类似生物进化中的染色体基因的交叉、变异等过程。在求解较为复杂的组合优化问题时,相对一些常规的优化算法,通常能够较快地获得较好的优化结果。遗传算法已被人们广泛地应用于组合优化、机器学习、信号处理、自适应控制和人工生命等领域(Using computer simulation operations, the problem-solving process is transformed into a process similar to the crossover and mutation of chromosomal genes in biological evolution. When solving more complex combinatorial optimization problems, compared with some conventional optimization algorithms, better optimization results can usually be obtained faster. Genetic algorithm has been widely used in the fields of combinatorial optimization, machine learning, signal processing, adaptive control and artificial life)