频谱估计
周期图，Welch 和 Lomb-Scargle PSD，相干性，传递函数，频率重排
使用 periodogram、pwelch 或 plomb 分析均匀或非均匀采样信号的频谱内容。使用重排锐化周期图估计。确定信号之间的频域相干性。基于输入和输出测量值估计传递函数。研究频域中的 MIMO 系统。
App
| 信号分析器 | 可视化和比较多个信号和频谱 |
|---|
函数
估算器
| cpsd | Cross power spectral density |
|---|---|
| findpeaks | Find local maxima |
| mscohere | Magnitude-squared coherence |
| pentropy | Spectral entropy of signal |
| periodogram | Periodogram power spectral density estimate |
| plomb | Lomb-Scargle periodogram |
| pmtm | Multitaper power spectral density estimate |
| poctave | Generate octave spectrum |
| pspectrum | Analyze signals in the frequency and time-frequency domains |
| pwelch | Welch’s power spectral density estimate |
| tfestimate | Transfer function estimate |
dB转换
| db | Convert energy or power measurements to decibels |
|---|---|
| db2mag | Convert decibels to magnitude |
| db2pow | Convert decibels to power |
| mag2db | Convert magnitude to decibels |
| pow2db | Convert power to decibels |
主题
Nonparametric Methods
- Learn about the periodogram, modified periodogram, Welch, and multitaper methods of nonparametric spectral estimation.
Detect a Distorted Signal in Noise
- Use frequency analysis to characterize a signal embedded in noise.
Detect Periodicity in a Signal with Missing Samples
- Use the Lomb-Scargle periodogram to study the periodicity of an irregularly sampled signal.
测量信号的功率
- 估计包含信号大部分功率的频带宽度。对于失真信号，确定基波和谐波中存储的功率。
幅值估计和填零
- 通过填零获得正弦信号幅值的精确估计。
Bias and Variability in the Periodogram
- Reduce bias and variability in the periodogram using windows and averaging.
比较两个信号的频率成分
- 识别频域中信号之间的相似性。
Significance Testing for Periodic Component
- Assess the significance of a sinusoidal component in white noise using Fisher's g-statistic.
Find Periodicity in a Categorical Time Series
- Perform spectral analysis of data whose values are not inherently numerical.
交叉频谱和幅值平方相干性
- 获取正弦分量之间的相位滞后，并识别时间序列中的频域相关性。
Nonparametric Spectrum Object to Function Replacement
- Replace calls to nonparametric psd and msspectrum objects with function calls.