资源列表
signal-spectrum-estimation-
- 特征空间方法是现代谱估计的重要方法之一。针对噪声中的复正弦信号的模型，通过特征矢量的方法进行信号空间的分解。通过将信号空间分解为谐波信号空间和噪声信号空间这两个相互正交的空间的方法进行谱估计。Pisarenko,Music,ESPRIT算法都是这一类方法的重要算法。我们通过对不同算法进行比较分析不同算法在各种状况下的表现性能。并针对ESPRIT算法的各种改性和提升进行对比和测试。-Feature space is one of the modern spectral estimation met
Sudoku
- Player fills a number from 1 to 9 into given empty space with a rule that no number is appear twice in a single row, column, and minigrid. To play a game of Sudoku, click PlayGame button and an incomplete board of Sudoku will be created in the grid b
pls
- 最小二乘回归法（PLSR：partial least squares regression)：是一种新型的多元统计数据分析方法，它主要研究的是多因变量对多自变量的回归建模，特别当各变量内部高度线性相关时，用偏最小二乘回归法更有效。另外，偏最小二乘回归较好地解决了样本个数少于变量个数等问题。-Least squares regression (PLSR: partial least squares regression): a new type of multivariate statistica
06
- DOA估计与角度差的关系的MUSIC算法，MATLAB仿真源代码，可完成绘图。-DOA Estimation poor relationship with the angle of the MUSIC algorithm, MATLAB simulation source code, to be completed by the drawing.
Digital-baseband-signal
- 数字信号的基带传输 PAM的功率谱密度 数字基带的接收 匹配滤波器 升余弦滚降系统 基带信号眼图-Digital baseband digital signal baseband transmission power spectral density of the PAM receiver matched filter raised cosine the system baseband signal eye diagram
static3d20
- 三维有限元静力问题分析程序，用Matlab编写，采用20节点3维单元，可绘制应力云图。-Three dimensions finite element programs
MLS2D-(1)
- 二维的移动最小二乘法，包含其中权函数，形函数程序以及高斯函数等-Two-dimensional moving least squares method, which includes the weight function, Gaussian shape function procedures and functions, etc.
m-u0
- 应用matlab编程计算钢筋混凝土截面弯矩曲率关系曲线-Application matlab programming and calculation of reinforced concrete sectional moment curvature curve
BPGA
- 本程序为：以遗传算法主程序优化神经网络结构 建立BP神经网络的主程序 mybpnet.m 以BP神经网络模型为基础的适应度函数fitnessBP.m 以BP神经网络模型为基础的映射函数fcnBP.m-the combination of bp network and genetic algorithm
code-link-pred
- 给出了基本的有监督的基于矩阵分解的链路预测的代码。-Supervised link prediction based on matrix decomposition
fwdcdmafinal
- CDMA transceiver Code in MATLAB
nmpc
- matlab非线性预测控制nmpc，源代码程序，很经典-matlab nonlinear model predictive control nmpc, source code, very classic