Matlab_BPNN

本文主要讨论在MATLAB软件中如何实现C程序源代码的移植。结合"道路平整度指数(IRI)预测问题"的实例,将C语言编写自仿射变换分形插值函数,移植(或改写)到MATLAB中,绘制出宁波机场道路平整度的预测图象,为解决预测问题可视化提供帮助。(This paper mainly discusses the MATLAB software, how to achieve C source code of the transplant. Conjunction with the road roughness index (IRI) a projection of the example of C language to self-affine fractal interpolation function transformation, transplantation (or rewritten) to MATLAB, the mapping out of Ningbo airport road roughness prediction image, To address the issue of visual projections to help.)

MATLAB程序设计电子指南Electronic Programming Guide MATLAB(MATLAB Programming Guide Electronic Programming Guide MATLAB e)

本程序基于Cauthy约束稀疏反演方法，实现地震反射系数的反演工作。(The this program constrained sparse inversion method based Cauthy inversion of seismic reflection coefficient.)

电力系统经济负荷分配的matlab代码实现(Power system economic load allocation matlab code)

It is a program for Maximum likelihood equalization for space time block codes in MIMO systems

文章对几种常用的基于循环前缀(CP)的最大似然同步算法进行了分析，并对其频偏估计方差进行了比较；同 时针对基于CP 的同步算法在多径衰落信道下性能较差的情况，提出了一种改进的CP 同步算法并进行了仿真，结果表明相比 于原ML 算法，文中算法在多径信道下可有效提高频偏估计性能。(】This paper does some research on multiple maximum-likelihood (ML) algorithms based on cyclic prefix (CP) and compares variances of frequency-offset estimation After the analysis of the bad performance of CP based algorithms in multi-path fading channels, an improved CP algorithm is proposed and the simulation shows that this algorithm can improve its performance effectively in multi-path fading channels.)

对舰船在航行时遇到的特殊情况引起的挠曲变形进行补偿提高对准精度(Special case of deflection when sailing ship encountered due to improved alignment accuracy to compensate)

L1范数正则化最小二乘问题求解器，stanford大学Boyd教授出品。(Simple Matlab Solver for l1-regularized Least Squares Problems)

一篇关于Insar相位展开的文章，对面分析和各种经典算法和最前沿的算法比较(An article on the Insar phase of the article, the opposite analysis and a variety of classical algorithms and the most cutting-edge algorithm)

基于MATLAB的时域采样以及频谱分析，对初学者很有用(MATLAB-based time domain sampling and spectral analysis, is useful for beginners)