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信号处理经典算法
- 15个信号处理经典算法模型及代码实现,涵盖 Dijkstra.DP.BFS/DFS.红黑树.KMP.遗传.启发式搜索.图像 特征提取 SIFT.傅立叶变换.Hash.快速排序.SPFA.快递选择 SELECT 等 15 个经典基础算法，
st1
- S变换 可用于对信号进行频谱分析 提取信号特征 包括幅值 相位 谐波成分等应用广泛 希望对大家的学习有帮助-S transform can be used to extract the signal spectrum analysis features include the magnitude of the phase signal harmonic components and so widely we hope to help learning
quzao
- 过滤噪声，提取信号，把采集的离散信号提取有用的部分。-Filter noise, extract the signal, the acquisition of discrete signals to extract useful parts.
MATLAB-bit-tongbu-tiqu
- 一种基于matlab的位同步提取方法，通过微分，滤波提取信号-a new matlab system
提取脑电的特征值
- 用matlab程序提取脑电肌电等信号的时域及频域特征值。
fsk2---haar
- 2FSK信号的小波分解，并提取信号的细节系数-Wavelet decomposition 2FSK signal and extracts a signal of detail coefficients
ASK-Haar
- ASK信号的连续小波变换,并提取信号的幅度信息-ASK signal of the continuous wavelet transform and extracts the signal amplitude information
EWT
- 经验小波变换结合EMD的自适应性和小波分析的理论框架,Gilles提出了一种称为经验小波变换(EWT)的自适应信号处理方法.其核心思想是通过对信号的Fourier谱进行自适应划分,建立合适的小波滤波器组来提取信号不同的AM-FM成分.-Empirical wavelet transform
cheby
- 利用IIR数字低通滤波器从噪声中提取信号，采用低通滤波器可以分离出有用信号，。采用切比雪夫Ⅱ型低通滤波器，将高频噪声滤除-The IIR digital low-pass filter is used to extract the signal the noise,. Using Chebyshev type low-pass filter to filter the high frequency noise
Prony
- Prony算法用来提取信号的幅值、频率、衰减因子和初相角。它在电力系统低频检测，谐波检测等方面运用非常广泛，但是缺点是抗噪性差，它的信号提取能力强，模拟曲线的能力强，但为了提高它的抗噪性，最好与其它方法相结合-The Prony algorithm is used to extract the amplitude, frequency, attenuation factor and initial phase angle of the signal. It is in the power sys
E_window
- 对信号进行STFT,CWT,DWT分析。做CWT时提取某一尺度下的时域图；做DWT时，提取信号不同分辨率下的高频成分-The analyses of signal used STFT, CWT, DWT
模极大值降噪算法
- 可以实现对心电信号中模极值点的提取，软硬阈值算法的对比实验，以及小波的多层次分解(It can extract the extreme point of the ECG signal)
CharacterDistill
- 常用的时频信号处理算法,用于机械部件的故障特征提取(fault feature extraction)
Wavelet packet analysis
- 小波包分解提取信号动力特性 能量特性 供大家参考(Wavelet packet analysis to extract the characteristic frequency of the vibration signal, and the calculation of the energy spectrum analysis)
我的MATLAB程序
- MRS信号包络提取 线性拟合 非线性拟合 非常好用(MRS signal envelope extraction, linear fitting, nonlinear fitting, very easy to use)
keypoint
- 对非平稳信号进行分段、截取，再对处理过后的短时信号做短时傅里叶变换，分析其频谱特性，并找到各个时间节点的频率特性，以便分析不同事件段内的声音特征，以图像的形式表达出，最终达到区分不同声音的目的。(The nonstationary signals are segmented, and then the interception, the short-time signal after processing the short-time Fourier transform, the analysi
基于小波包提取轴承故障
- 基于小波包变换对信号进行分解，提取机器轴承故障的特征信号进行损伤识别，(The signal is decomposed based on wavelet packet transform, and the characteristic signals of machine bearing faults are extracted to identify the damage,)
feature selection
- 各种信号特征提取，最大值，最小值，均值，商(Signal feature extraction)
data_practise
- 加速度信号提取并自动保存至手机中，可以过滤粗值。(The acceleration signal is extracted and automatically saved to the mobile phone, which can filter the coarse value.)
提取语音信号基频
- 用自相关函数提取语音信号基频，提取音频文件的基频等高线(Use the autocorrelation function on segments of the signal (windowsize: 100ms) and compute the fundamental frequency. Use a max_time_lag of 100ms in the autocorrelation function and a window shift of 25ms. Create a fundame