搜索资源列表
CIA2
- 一种独立分量分析的算法，内有详细介绍每一步程序的作用和意义-Independent component analysis algorithm, with detailed descr iption of each step of the process of the role and significance
ICA
- 关于独立分量分析在脑电信号处理中用matlab实现的应用-On independent component analysis in the eeg signals processing with the application of matlab
BKSA_BSS
- 一种新的基于峰度的盲源分离开关算法（附参考文章），无需假设源信号的概率密度函数, 可直接对独立分量分析中的激活函数进行自适应学习。-A New kurtosis switching algorithm for blind source separation (with reference to the article), without assuming that the probability density function of the source signal, independent
ICA
- ICA独立分量分析，通过协方差白化，熵编码算法。-ICA, through covariance albino, entropy coding algorithm.
ZSYFLJS
- 基于自适应学习率独立分量分析的图像盲分离-Blind adaptive learning rate based on independent component analysis separated
fourierica
- FourierICA是一种无监管的自适应学习方法，用于盲源分离问题，将短时傅里叶变换STFT与独立分量分析ICA相结合。-FourierICA is an unsupervised learning method suitable for the analysis of bss.The method performs independent component analysis(ICA) on short-time Fourier transforms of the data.
stICA
- 独立分量分析中的固定点算法用于处理图片,算法可以分析医院的影像图片，进而有助于对病人的器官进行功能性分析。- Independent component analysis in fixed-point algorithms for processing the image, the algorithm may analyze the hospital s image picture, and thus contribute to the patient s organ for functiona
ICA_PICTURE
- 应用独立分量分析方法对图片进行图像分离处理，可以将医学影像的图片进行分离，单独进行分析。-Independent component analysis of images for image separation processing, medical imaging picture can be separated, analyzed separately.
FastICA_25
- 基于独立分量分析的fastICA算法在各个方面运用的基本算法- FastICA algorithm based on independent component analysis is used in all aspects of the basic algorithm
JAD
- JADE算法分析 用于独立分量分析和盲源分离算法-JADE algorithm
jiandan
- 对简单信号进行混合，并且运用独立分量分析方法进行分离验证-The mix of simple signal, and the use of independent component analysis method for separation of verification
57169speal
- 盲分离程序，利用FSATICA独立分量分析的方法实现了线性混合信号的盲分离-Blind separation procedures, the use FSATICA independent component analysis method to achieve a linear mixed-signal blind separation
FastICA_25
- 快速ICA分析.快速独立分量分析。给出实例并分解-Fast ICA.FASTICA(mixedsig) estimates the independent components given multidimensional signals.
FASTICA
- 快速独立分量分析用于图像处理源代码,工具包-FsatICA for image processing
ccfxmjmu
- 基于负熵最大的独立分量分析，信号处理中的旋转不变子空间法，单径或多径瑞利衰落信道仿真，含噪脉冲信号进行相关检测,ICA（主分量分析）算法和程序。- Based on negative entropy largest independent component analysis, Signal Processing ESPRIT method, Single path or multipath Rayleigh fading channel simulation, Noisy pulse corr
etffhchf
- 基于负熵最大的独立分量分析，包括数据分析、绘图等等,滤波求和方式实现宽带波束形成，自己编的5种调制信号，进行逐步线性回归。- Based on negative entropy largest independent component analysis, Data analysis, plotting, etc., Filtering summation way broadband beamforming, Own five modulation signal, Stepwise linear
fdywfpvm
- 包括 MUSIC算法，ESPRIT算法 ROOT-MUSIC算法，相控阵天线的方向图（切比雪夫加权），基于互功率谱的时延估计，最大信噪比的独立分量分析算法，基于欧几里得距离的聚类分析。- Including the MUSIC algorithm, ESPRIT algorithm ROOT-MUSIC algorithm, Phased array antenna pattern (Chebyshev weights), Based on the time delay estimation o
ggsihsva
- 最大信噪比的独立分量分析算法，有循环检测，周期性检测，用于信号特征提取、信号消噪，基于matlab GUI界面设计,基于欧几里得距离的聚类分析。- SNR largest independent component analysis algorithm, There are cycle detection, periodic testing, For feature extraction, signal de-noising, Based on matlab GUI interface desi
hawdhwud
- 虚拟力的无线传感网络覆盖，具有丰富的参数选项,主要是基于mtlab的程序，基于chebyshev的水声信号分析，最大信噪比的独立分量分析算法。- Virtual power wireless sensor network coverage, It has a wealth of parameter options, Mainly based on the mtlab procedures, Based chebyshev underwater acoustic signal analysis,
ifppapwi
- 构成不同频率的调制信号，采用加权网络中节点强度和权重都是幂率分布的模型，使用拉亚普诺夫指数的公式，BP神经网络用于函数拟合与模式识别，基于负熵最大的独立分量分析。- Constituting the modulated signals of different frequencies, Using weighted model nodes in the network strength and weight are power law distribution, Raya Punuo Fu in