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신호 분석
데시메이션된 1차원 웨이블릿 변환 및 데시메이션되지 않은 1차원 웨이블릿 변환, 1차원 이산 웨이블릿 변환 필터 뱅크, 1차원 이중 트리 변환, 웨이블릿 패킷
이산 웨이블릿 변환, 이중 트리 변환, 웨이블릿 패킷을 사용하여 신호를 분석합니다.
함수
앱
신호 다중분해능 분석기 | Decompose signals into time-aligned components |
도움말 항목
임계적으로 샘플링된 DWT
- Haar Transforms for Time Series Data and Images
Use Haar transforms to analyze signal variability, create signal approximations, and watermark images. - Border Effects
Compensate for discrete wavelet transform border effects using zero padding, symmetrization, and smooth padding.
데시메이션되지 않은 DWT
- Analytic Wavelets Using the Dual-Tree Wavelet Transform
Create approximately analytic wavelets using the dual-tree complex wavelet transform. - Wavelet Cross-Correlation for Lead-Lag Analysis
Measure the similarity between two signals at different scales. - Nondecimated Discrete Stationary Wavelet Transforms (SWTs)
Use the stationary wavelet transform to restore wavelet translation invariance. - Critically Sampled and Oversampled Wavelet Filter Banks
Learn about tree-structured, multirate filter banks.
프랙털 분석
- 1-D Fractional Brownian Motion Synthesis
Synthesize a 1-D fractional Brownian motion signal. - Multifractal Analysis
Use wavelets to characterize local signal regularity using wavelet leaders.
웨이블릿 패킷 분석
- Wavelet Packets
Use wavelet packets indexed by position, scale, and frequency for wavelet decomposition of 1-D and 2-D signals. - Wavelet Packets: Decomposing the Details
This example shows how wavelet packets differ from the discrete wavelet transform (DWT).