MatLab

光伏mppt 算法 s函数的使用 采用干扰法 有一定的参考价值(Solar mppt algorithm using the the Suntech STP200-18/Ub panels power 200W maximum power 200W open circuit voltage of 33.4V open circuit voltage 33.4V short-circuit current of 8.12A Short Circuit Current 8.12A working voltage 26.2V maximum power voltage 26.2V operating current of 7.63A maximum power current 7.63A Maximum system voltage 1000V maximum system voltage 1000V current temperature coefficient (A/K) 0.045 /° C voltage temperature coefficient (V/K)-0.34 /℃)

该代码是lte 子块交织仿真源代码，交织在通信中起到提高传输可靠性的作用(The code is a sub-block interleaving lte simulation source code, intertwined in the communication role to play to improve transmission reliability)

ssa,用于在matlab中的noise analysis(ssa, used in matlab noise analysis)

说明：  通过分析交通流量时间序列的特点，引入BP神经网络进行短时交通流预测。首先，分析了短时交通流量预测的意义及研究背景；然后，介绍了BP神经网络的结构模型、学习规则以及BP算法的改进算法；最后，通过BP神经网络对短时交通流进行预测，并分析了在各种不同条件下的预测情况。(through the analysis of the characteristics of traffic flow time series, introduces BP neural network for short-term traffic flow prediction. First of all, it analyzes the significance of short-term traffic flow prediction and research background. And then, it has discussed the model and structure, the study rule and the improved algorithm of BP neural network. Finally, by BP neural network to forecast the short-term traffic flow, it analyzes under different conditions of the neural network prediction.)

用matlab进行排队论仿真的经典论文，有兴趣的同学可以参考一下。(Matlab simulation carried out with the classic queuing theory papers, students who are interested can refer to.)

Discrete Fourier Transform in MATLAB

静基座下的SINS初始对准kalman滤波程序(The static base SINS initial alignment kalman filtering procedures)

说明：  GA-BP神经网络，包含数据和代码，绝对好用，亲测有效(GA-BP neural network, including data and code)

说明：  改进的信号匹配追踪稀疏分解代码，基于gabor时频原子，对语音信号重构效果好(The improved signal matching pursuit sparse decomposition code is based on Gabor time-frequency atom, and has good effect on speech signal reconstruction)

Matlab R2009b与MSVC 2008混合编程的源代码！(Matlab R2009b with MSVC 2008 Mixed programming source code!)