DPC

一种改进的自适应滤波算法,它通过选择自适应滤波器的系数更新时间间隔,在系统的收敛速度与计算量之间取得折衷 算法在每次系数更新时,利用了系统过去时刻数据(An improved adaptive filtering algorithm, it by selecting the adaptive filter coefficient update interval, the convergence rate and the trade-off between computation algorithm to update each coefficient, the use of the system data over the past time)

exm for Experiments with MATLAB (by Cleve Moler in 2008), 这本书是关于MATLAB的教材，乃MATLAB首席科学家兼董事长Cleve Moler的著作。(exm for Experiments with MATLAB (by Cleve Moler in 2008), this book is about teaching MATLAB, MATLAB is the chief scientist and chairman of Cleve Moler)

利用Matlab进行柴油机电子调速器，采用模糊控制理论(Using Matlab, electronic engine governor, the fuzzy control theory)

这是读取segy文件的matlab程序，对matlab中数学建模计算有着重要的作用(This matlab program read segy file.)

DS-spread spectrum系统中,噪声为加性高斯白噪声,传统单用户检测,线性解相关多用户检测和最小均方误差多用户检测的性能比较(DS-spread spectrum system, the noise is additive white Gaussian noise, the traditional single-user detection, the linear decorrelating multiuser detection and MMSE Multiuser Detection Performance Comparison)

在matlab中计算灰色关联度,可以计算农业经济，人文生态，环境，等等，用途广泛，方便使用。(gray system is good，many people liked it,it can calculate many things for agriculture,econmics and other things.so try to download it and use it.)

自己用matlab写的算术编码的程序，信源为二元信源,信源序列、码长均可自定义(own use Matlab write arithmetic coding procedures, source of the dual source, the source sequence, code length can be defined)

CVPR 2014上的关于图像显著性区域的检测matlab代码。(Wangjiang Zhu, Shuang Liang, Yichen Wei, and Jian Sun. Saliency Optimization from Robust Background Detection. In CVPR, 2014.)

matching pursuit code for signal processing like eeg ecg and voice.,etc.,

说明：  关于径向基函数神经网络、两个典型的反馈神经网络Hopfield网络、Elman网络的简单示例，适合初学者掌握径向基函数网络和反馈网络的神经网络工具箱函数，为全面学习这两类网络打下基础。(The simple examples of radial basis function neural network, two typical feedback neural networks Hopfield network and Elman network are suitable for beginners to master the neural network toolbox functions of radial basis function network and feedback network, which lays a foundation for comprehensive learning of these two types of networks.)