gmskmod

OFDM WITH RELAY SNR RATIO CALCULATION

该文件包含了8psk调制信号的产生，以及经过多径瑞利信道后，前后对比的星座图，经过CMA均衡算法后输出信号，能对均衡算法有更深的认识。(This file contains the generated 8psk modulation signal and multipath Rayleigh channel after, before and after the constellation, after CMA equalization algorithm output signal, capable of balancing algorithms have a better understanding.)

装配生产线任务平衡优化遗传算法通MATLAB源码，下面的源码实现了装配生产线任务平衡优化问题（ALB问题）的遗传算法，算法主要参考下面这篇文献，并对其进行了改进。(Task of assembly line balancing optimal genetic algorithm-pass MATLAB source code, the following source code to achieve the task of assembly line balancing optimization problem (ALB problem) of the genetic algorithm, this algorithm is the main reference the following documents, and its improvements.)

Heat transfer problem solved on L shaped solid body using MATLAB partial differential equation toolbox.

深度机器学习工具包，MATLAB，内容详尽，有兴趣的可以下载(Depth of machine learning toolkit, MATLAB, detailed, are interested can download)

用于Matlab 编程，计算diffusion limited aggregation (A Matlab program to perform the diffusion limited aggregation )

it s a package for load flow analysis by Newton Raphson method

实现把txt中的数据传到mdb数据库中保存起来(Txt data spread mdb database and to be saved)

使用MATLAB仿真，产生矩形脉冲，是超宽带传输信号的基本图形 (Simulation using MATLAB, resulting in the rectangular pulse, ultra-wideband transmission signal is the basic graphics)

将压缩感知用于谱估计中，根据论文谱压缩感知的一些程序(Compressive sensing (CS) is a new approach to simultaneous sensing and compression of sparse and compressible signals based on randomized dimensionality reduction. To recover a signal from its compressive measurements, standard CS algorithms seek the sparsest signal in some discrete basis or frame that agrees with the measurements. A great many applications feature smooth or modulated signals that are frequency sparse and can be modeled as a superposition of a small number of sinusoids. Unfortunately, such signals are only sparse in the discrete Fourier transform (DFT) domain when the sinusoid frequencies live precisely at the center of the DFT bins. When this is not the case, CS recovery performance degrades significantly. In this paper, we introduce a suite of spectral CS (SCS) recovery algorithms for arbitrary frequency sparse signals. The key ingredients are an over-sampled DFT frame, a signal model that inhibits closely spaced sinusoids, and classical sinusoid parameter e)