搜索资源列表
yuyinduandianjiance
- 对一段语音信号进行预处理，加窗，求过零率，短时能量，求各种语音信号的特征参数。
tfagui
- 对信号进行自适应核二次型时频分布变换，显示信号的时频特征-Adaptive signals nuclear quadratic transform time-frequency distribution, indicating the time-frequency characteristics
xiaobobianhuantezheng
- 小波变换与信号瞬时特征分析，希望对大家有帮助。-matlab
wei-ruo-xin-hao
- 利用matlab产生正弦信号，加噪声，分析其加噪前后的数字特征-Using matlab to produce a sinusoidal signal plus noise, and analyze the numbers before and after adding noise characteristics
featrue7
- 通信信号调制方式识别 AK.Nandi 提出的时域的7个特征 的MATLAB 程序-signal Modulation Recongnition features
wavelet-transform
- 小波变换程序可以实现信号特征提取，图像处理等功能。-Wavelet transform procedure can achieve signal feature extraction, image processing and other functions.
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
EEG
- 脑电信号提取及特征分析 生物医学工程及信号处理专业可以-EEG feature extraction and analysis
emd
- 运用EMd算法实现了信号的处理，并且对信号进行傅里叶变化获得其频域特征，冲采样后获得特征参数建立神经网络与实验进行识别- EMd use signal processing algorithm, and the Fourier transform of the signal in the frequency domain to obtain its characteristic red after sampling to obtain the characteristic parameter
time_features1
- 画振动轴承时域信号特征图，包括rms，峭度，等-draw the feature pictures of rolling bearing using vibration signal.
Heart-sound-signal-extraction
- 一种对心音信号特征提取的小波包算法的研究。-A study of heart sound signal feature extraction wavelet packet algorithm.
Application-of-HHT
- 改进HHT算法及在心音信号分析中的应用，目的是为了研究心脏的动力学特征，将HHT算法引入到心音的信号分析中。-Improved FFT algorithm and the heart sound signal analysis applications, the purpose was to study the kinetics of the heart, the HHT algorithm into the signal analysis of heart sounds.
mul_fea_ext
- 里面包含多种信号特征提取算法，有短时变换算法，包络特征提取算法，模糊函数算法，包络前沿算法，还有PCA降维等(It contains a variety of signal feature extraction algorithms, including short-time transform algorithm, envelope feature extraction algorithm, fuzzy function algorithm, envelope front algorithm,
emd
- 信号处理，用于信号分解和分析。将原信号进行包络分解后，提取特征信号，从而可以进一步的分析和处理。(Signal processing is used for signal decomposition and analysis.The original signal is decomposed by envelope, and then the characteristic signal is extracted, which can be further analyzed and process
思维进化算法优化BP神经网络——非线性函数拟合
- BP神经网络的数据分类——语音特征信号分类，matlab(Data classification of BP neural network -- speech feature signal classification)
EMD模型
- 经验模态分解（Empirical Mode Decomposition，简称EMD))方法被认为是2000年来以傅立叶变换为基础的线性和稳态频谱分析的一个重大突破?，该方法是依据数据自身的时间尺度特征来进行信号分解，无须预先设定任何基函数。 该方法的关键是经验模式分解，它能使复杂信号分解为有限个本征模函数（Intrinsic Mode Function，简称IMF），所分解出来的各IMF分量包含了原信号的不同时间尺度的局部特征信号。经验模态分解法能使非平稳数据进行平稳化
高阶统计量法微弱信号检测
- 基于高阶统计量特征的通信系统中微弱信号检测程序(Weak Signal Detection Program in Communication System Based on Higher Order Statistics)
MFCCs
- 将语音识别领域的MFCC方法通过修改能够对三维地震数据进行特征提取实现了语音识别方法在地震信号方面的运用(The MFCC method in the field of speech recognition can be modified to extract the features of 3D seismic data to realize the application of speech recognition method in seismic signal)