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用sa进行光谱图像的特征提取的matlab程序
- 用sa进行光谱图像的特征提取的matlab程序，该算法比用其他方法在性能方面高%15-with spectral images of the Matlab feature extraction procedure, the algorithm than other methods in high-performance
sndpeek
- sndpeek is just what it sounds (and looks) like: real-time 3D animated display/playback can use mic-input or wav/aiff/snd/raw/mat file (with playback) time-domain waveform FFT magnitude spectrum 3D waterfall plot lissajous! (inte
hyplas
- ************************************************************************ * * * * * THIS IS THE H Y P L A S 2.0 README FILE * * ----------------- * * * * HYPLAS is a finite element program for implicit small and large * * strain analisys of hyperelast
pulse
- 脉搏信号分析 （1）设计滤波器，实现对脉搏信号的噪声抑制和基线纠漂； （2）时域分析：波形特征检测； （3）功率谱分析：对消噪后的信号进行功率谱分析。要求计算信号的功率谱，功率谱峰值，峰值频率。 -Pulse signal analysis (1) design the filter, to achieve the pulse signal noise suppression and baseline drift correction (2) time-domain analy
jitterbug-1.23
- JITTERBUG 是一个用来仿真线性控制系统的Matlab工具箱。通过JITTERBUG，我们能得到延时、数据丢失对系统的性能影响。同时，这个工具箱还能计算控制系统中信号的谱密度。-JITTERBUG [Lincoln and Cervin, 2002] is a MATLAB-based toolbox that allows the computation of a quadratic performance criterion for a linear control syste
AR-matlab
- matlab源代码说明，有关ar谱特征提取的文档。说明很清晰，值得一看-matlab source code shows that the ar spectral feature extraction document. With clear, worth a visit
mmsp08
- Feature extraction is a key issue in contentbased image retrieval (CBIR). In the past, a number of texture features have been proposed in literature, including statistic methods and spectral methods. However, most of them are not able to accu
Textureclassificationusingspectralhistograms
- Based on a local spatial/frequency representation,we employ a spectral histogram as a feature statistic for texture classification. The spectral histogram consists of marginal distributions of responses of a bank of filters and encodes implicit
mypaper4
- To fully utilize the character of the bioradar echo signal, autocorrelation analysis, spectral estimation methods and time-frequency analysis are presented in this paper. These methods are employed to deal with no one, single people and multi-people
silenceRemoval
- his a simple method for silence removal and segmentation of audio streams that contain speech. The method is based in two simple audio features (signal energy and spectral centroid). As long as the feature sequences are extracted, as thresholding app
feature
- 该文件包含了一些常用的声辐射噪声的特征提取方法，包括波形的包络特征，高阶谱特征，分形维特征，奇异指数特征等。-The document contains some common acoustic feature extraction method of noise, including waveform envelope characteristics, higher order spectral features, characteristic of fractal dimension, si
zhijiefapuguji
- 估计功率谱密度的平滑周期图是一种计算简单的经典方法，其主要特点是与任何模型参数无关，是一种非参数化的方法。-Estimated power spectral density is a smooth periodogram simple classical calculation method, the main feature is not related to any model parameter, is a non-parametric methods.
Seal-Identification
- 运用H15；I色彩窄间对印章图像颜色特征提取等一系列预处理，研究了多种识 别方法后发现基于纹理特征的印鉴识别方法不但速度快，而且识别率也较高，并且方法简便。通 过将极坐标和傅垦叶变换结合，计算m印签图像纹理的频谱度量，来完成印鉴的特征提取，运用支 持向量机分类器对印鉴进行识别，实验证明，方法具有良好的旋转不变纹理分析性能，提高了识别 率。-It WaS found a fast，simple and a higher seal image(HSI)identification
EEG-based-identification-method
- ：基于脑电信号的身份识别是通过采集试验者的脑部信号来进行身份认证。对于同一个外部刺激或者主体在思考同一个 事件的时候，不同人的大脑所产生的认知脑电信号不同。选取与运动意识想象有关的电极后，分析不同个体在特定状况下脑 电的个体差异，采用以回归系数、能量谱密度、相同步、线性复杂度多种信号处理结合方法对运动想象脑电信号进行处理来 进行特征提取。组合多元特征向量并运用多层BP 神经网络对不同个体的脑电信号进行分类，并在不同的意识想象及不同数 据长度、不同的波段对试验者进行识别率验证分析。
MESH
- 无线MESH网络是近年被高度重视和快速发展的新型网络技术。该网络是面向基于IP接入的新型无线移动通信技术，适合于区域环境覆盖和宽带高速无线接入。无线Mesh网络基于呈网状分布的众多无线接入点间的相互合作和协同，具有宽带高速和高频谱效率的优势，具有动态自组织、自配置、自维护等突出特点。-The wireless mesh network in recent years has been attached great importance to the rapid development of ne
SCSToolboxV2
- 将压缩感知用于谱估计中，根据论文谱压缩感知的一些程序-Compressive sensing (CS) is a new approach to simultaneous sensing and compression of sparse and compressible signals based on randomized dimensionality reduction. To recover a signal from its compressive measurements,
CSD_Detect_Eval1
- 认知无线电中信号检测循环频谱特征检测方法-The signal detection circulation spectral feature detection
svm
- 基于光谱特征的提取算法，很实用，分类精度高-Based on spectral feature extraction algorithm, very practical, high classification accuracy
PCAPMAPPLSPBP
- 这是一种基于近红外光谱的非线性建模方法及系统，从各所述近红外光谱数据随机挑出一部分作为校正集，挑出一部分作为验证集；将所述校正集和所述验证集通过主成分分析得到光谱特征空间；在所述光谱特征空间中，通过马氏距离法选取所述校正集里与所述验证集的各个样本最近似的样本作为校正子集；从所述校正子集中提取主成分数，作为BP神经网络的输入层建立回归模型，不仅能解决各因素之间多重相关的问题，还避免了大量的噪声和一些无用的信息，降低了变量维数，在BP神经网络的非线性映射能力和适应学习能力的基础上，提高了模型的预测稳
Feature-Denoising
- joint sparse representation (JSR)方法用于车内语音增强的特征降噪算法-address reducing the mismatch between training and testing conditions for hands-free in-car speech recognition. It is well known that the distortions caused by background noise, channel effec