搜索资源列表
Signal
- 过程信号的前馈-反馈型自适应盲分离算法：利用神经网络的自学习能力实现信号的盲分离已被证明是实现信号分离的一种有效方法,不同的神经网络模型对分离算法的效能将产生极大的影响 -The process of signal feedforward- feedback-based adaptive algorithm for blind source separation: Using neural networks to achieve self-learning ability of the bl
tuxiangfuyuan
- 该程序为盲源分离的仿真程序，对卷积模型的混合图像信号进行分离-The program for the blind source separation of the simulation program, a mixed model of convolution image signal separation
mangyuanfenli
- 信号分选中关于信号的盲分离，非常实用，能实现多个信号的分离，不需要先验信息-Signal Sorting on blind signal separation, very practical, to achieve a number of signal separation, do not need prior information
saperate
- 信源数动态变化的自适应盲分离算法-一种新的盲源分离算法，与大家共享。-Source number of dynamic changes of adaptive blind source separation algorithm- a new blind source separation algorithm, and for all to share.
saperate3
- 《超高斯与亚高斯混合信号的盲分离研究》，有用的忙分离算法文章。- Super-Gaussian and sub-Gaussian mixed-signal study of blind source separation, separation algorithm busy useful article.
saperate4
- 基于广义特征值和核函数的非线性盲分离算法.pdf-Based on the generalized eigenvalue and nuclear function algorithm for nonlinear blind source separation. Pdf
saperate5
- 盲源分离——理论、应用与展望.pdf-详细介绍了盲源分离的理论和应用。-Blind Source Separation- Theory, Application and Prospects. Pdf-detailed information on blind source separation theory and applications.
20090226
- 从盲声源信号的独立性出发!提出了一种新的盲声源混合信号分离方法:该方法基于信号联合概率的 分布统计!利用信号联合概率的方向导数熵最小获得最佳的旋转角度!最终实现盲信号分离:与快速独立分 量分析方法及神经网络方法相比!该方法不需要迭代计算:采用新的盲声源信号分离方法对轴承试验台的混 合声音信号进行识别!将电机和滚动轴承的声音分离出来!进而可以准确识别机械的故障-Blind sound source from the independence of the starting signal
FastICA
- 盲源分离中最为经典的不动点算法——FastICA,该算法简单，对初学者有很大的帮助-Blind Source Separation in the most classical fixed-point algorithm- FastICA, the algorithm is simple, for beginners there is a great help
kpca
- KPCA是一种非线性的盲源分离方法，很好用，推荐大家下载！-KPCA is a nonlinear blind source separation methods, very good, and recommend everyone to download!
BS-NG
- 盲信号自然梯度法盲分离程序，用于进行瞬时盲分离-Natural Gradient Blind Signal Separation legal procedures, for instantaneous blind source separation
qqqqq
- ：独立成分分析 ( I C A)在国内尚属一门新型的方法 介绍了I C A的原理及其算法 ，然后介绍了该算法在盲源 信号分离中的具体应用，并将此方法 与主成分方洼 ( P C A)进行了比较-: Independent Component Analysis (ICA) in China is a new method to introduce the principle of the ICA and its algorithm, and then introduced the algori
zishiyingfufankui
- 用于神经网络自适应算法的Matla盲源分离 -Adaptive algorithm for neural networks of the Matla Blind Source Separation
LMS
- 盲信号分离的LMS(最小二乘)自适应算法-Blind Signal Separation of LMS (least squares) adaptive algorithm
PAST2
- 基于投影逼近的子空间跟踪（PAST）方法，用于自适应盲信号分离-Based on the projection approximation subspace tracking (PAST) method for adaptive blind signal separation
Wigner_Hough
- 一种基于盲源分离和Wigner_Hough变换的线性调频信号检测方法.模式识别中的内容，图像图像处理的经典算法-Based on Blind Source Separation and Chirp Transform Wigner_Hough signal detection methods. Of the contents of pattern recognition, image of the classical image processing algorithm
SOBI
- 基于二阶统计量的盲源分离算法程序,对原始算法做了一定得改进。-blind source separation based on second order statistics，madke some improvement to the origin arithmetic
FastICAProcedure
- 利用FastICA实现盲信号分离，研究盲信号分离的朋友不可缺少的帮助程序-Use FastICA to achieve blind signal separation, blind signal separation research indispensable friend to help program
AMUSE
- AMUSE，独立成分分析(ICA)算法之一，用于混合语音信号的盲分离-AMUSE, algorithm of independent component analysis, used in blind speech signal separation.
bss_Zhangxianda
- 盲信号分离及其应用，张贤达教授的作品。格式为PDF形式的幻灯片。对盲分离初学者有用。-Blind Source Separation with Applications