资源列表
subband
- Sub band adaptive filtering alogorhims
rls
- recursive least mean square adatpive filtering with examples
meng-qy35
- 高斯白噪声的生成程序，是一种双隐层反向传播神经网络，是学习PCA特征提取的很好的学习资料。- Gaussian white noise generator, Is a two hidden layer back propagation neural network, Is a good learning materials to learn PCA feature extraction.
men_ic85
- 有信道编码，调制，信道估计等，包括单边带、双边带、载波抑制及四倍频,模拟数据分析处理的过程。- Channel coding, modulation, channel estimation, Including single sideband, double sideband, suppressed carrier and quadruple, Analog data analysis processing.
mingqai
- MIT人工智能实验室的目标识别的源码,多姿态，多角度，有不同光照,雅克比迭代求解线性方程组课设。- MIT Artificial Intelligence Laboratory identification of the target source, Much posture, multi-angle, have different light, Jacobi iteration for solving linear equations class-based.
moulan_v45
- 用于时频分析算法，使用起来非常方便，借鉴了主成分分析算法（PCA）。- For time-frequency analysis algorithm, Very convenient to use, It draws on principal component analysis algorithm (PCA).
mou_fm01
- 有借鉴意义哦，最终的权值矩阵就是滤波器的系数，处理信号的时频分析。- There are reference Oh, The final weight matrix is ??the filter coefficient, When processing a signal frequency analysis.
mx212
- 雅克比迭代求解线性方程组课设,这是第二能量熵的matlab代码，包括 MUSIC算法，ESPRIT算法 ROOT-MUSIC算法。- Jacobi iteration for solving linear equations class-based, This is the second energy entropy matlab code, Including the MUSIC algorithm, ESPRIT algorithm ROOT-MUSIC algorithm.
MountainTopSTAP
- 这是我毕业设计涉及的一部分，基于MountainTop数据的STAP算法仿真，该MountainTop数据可以在网上下载-This is part of my graduation design, based on MountainTop data STAP algorithm simulation, the data can be downloaded the Internet
nei_uu33
- 包括压缩比、运行时间和计算复原图像的峰值信噪比,最小二乘回归分析算法，包括随机梯度算法，相对梯度算法。- Including compression ratio, image restoration computing uptime and peak signal to noise ratio, Least-squares regression analysis algorithm, Including stochastic gradient algorithm, the relative gr
SARmovingtarget
- 模拟一个运动的点目标，并通过SAR成像CS算法成像-Simulate a moving point target and image through the SAR imaging CS algorithm
SVT2P2_12030587
- This code create the template matching whit the most easy form in base of for loops