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time_index1.rar
- 刀具在线监测故障信号的时域频域时频域特征提取matlab程序 ,Tool-line monitoring of fault signals in time domain frequency domain time-frequency domain feature extraction procedures matlab
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- 轴承全寿命数据的各种时域频域特征提取，包括17个时域和13个频域特征-Bearing a variety of life-cycle data in time domain frequency domain feature extraction
caracteranaysis_fault
- BP神经网络的时域频域特征参数计算公式，用以计算参数的敏感性-BP neural network for time domain frequency domain parameters of the formula used to calculate the sensitivity of parameters
Untitled
- 基于ＭＡＴＬＡＢ的小波分析应用：运用小波的时域、频域特征对摩托车发动机故障诊断和齿轮点蚀故障诊断-Wavelet analysis of MATLAB-based applications: the use of wavelets in time domain, frequency domain characteristics of motorcycles engine fault diagnosis and fault diagnosis of gear pitting
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- 对神经网络在故障诊断中的应用进行了探讨，针对潜油电泵机组故障的多态性 和多层次性，结合振动数据的轴向频域特征，建立了基于高斯-牛顿法的 BP 神经网络， 通过对其训练和学习，实现了三种常见故障的有效诊断。-The neural network fault diagnosis in the paper discusses the application, esp for fault the polymorphism of unit And more layered, combined
RickerWaveletsSpectrum
- 产生一个雷克子波组的时域和频谱特征，用以演示雷克子波的时域和频域特征。-Generated the Ricker wavelets of time domain and spectral characteristics, to demonstrate the Ricker wavelets time domain and frequency domain characteristics.
tezhengtiqu
- 此程序简单实用，用于数据的特征提取。选取了波形因子、峭度、频段带能量百分比等时域频域特征量。-This procedure is simple and practical, for data feature extraction. Select form factor, kurtosis, band band energy percentage frequency domain characteristics.
Matlab-wavelet-noise-removal
- 小波去噪程序，根据信号的频域特征对信号进行小波分解，然后去噪-program for artifact removal, this function is obtained based on the frequency feature of signal.
zhuchengxu
- 读取轴承全寿命周期中的每组数据，并对其进行多域特征提取，包括时域和频域特征提取，用于轴承性能退化评估的研究很有用，自己亲手调试成功-Read bearing the full life cycle of each set of data, and extract its multi-domain characteristics, including time domain and frequency domain feature extraction for bearing performanc
Fast-Fourier-Transform
- 有了傅立叶变换，我们可以从信号的频域特征去分析信号。尤其在无线通信系统 中，傅里叶变换的重要性就更加明显了，无论是设计者还是测试工程师，在工作中都会和傅立叶变换打交道。-With the Fourier transform, we can go to analyze signals the frequency domain characteristics of the signal. Especially in a wireless communication system, the impo
time-frequency-feature
- 此代码用于故障诊断特征提取，所提取特征包括传统时、频域特征和时频特征三部分，数据为轴承数据-This code is used when troubleshooting feature extraction, the extracted features, including traditional, frequency domain and time-frequency characteristics of three parts, the data is bearing data
时频域统计特征
- 信号的时频域统计特征，可用于后续模式识别,特征选择，特征提取。(The time-frequency statistics of the signal can be used for subsequent pattern recognition.)
inverse_st
- 广义S变换及其逆变换，用于对非平稳信号进行时频分析，研究信号的频域特征随时间的变化情况(The generalized S transform and its inverse transform are used to analyze the time-frequency of nonstationary signals and study the change of frequency domain characteristics with time.)
voice_wav_frequency
- matlab语音信号分析时域频域，加窗，降噪滤波，端点检测，时域特征和频域特征提取(Matlab speech signal analysis in time domain, frequency domain, windowing, denoising, filtering, endpoint detection, time domain feature and frequency domain feature extraction.)
matlab
- 拉普拉斯特征映射,最大差异展开，时频域特征(Laplacian Eigenmap Maximum difference expansion Fast Maximum difference expansion ISOMAP)
特征提取
- matlab程序，用于提取脑电数据的五种频域特征指标数值(matlab code, Five Frequency Domain Characteristic Index Values for Extracting EEG Data)
时域频域29个特征提取
- 利用matlab提取出频域和时域信号的29个特征(Using MATLAB to extract 29 features of frequency and time domain signals)
时域频域29个特征提取
- 利用matlab提取出频域和时域信号的29个特征，主运行文件feature_extraction，fre_statistical_compute和time_statistical_compute分别提取频域和时域的特征，生成的29个特征保存在生成的feature矩阵中。(Using MATLAB to extract 29 features of frequency-domain and time-domain signals, the main running files feature ex
cal_waveletfeature
- 计算小波包特征，小波分解得到能量比、小波熵。小波熵是一个统称，不是一种具体的熵算法。(The wavelet packet features are calculated, and the energy ratio and wavelet entropy are obtained by wavelet decomposition. Wavelet entropy is a general term, not a specific entropy algorithm.)
肌电信号处理
- 表面肌电信号处理的matlab程序，包括带通滤波、50Hz陷波滤波程序，以及计算时域、频域的指标iMEG、RMS ， MF、MPF(The matlab program of sEMG signal processing includes band-pass filter, 50 Hz notch filter program, and calculation of time and frequency domain index IMEG, RMS, MF, MPF)