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mne-denoise 0.0.1 documentation

  • Getting started
  • DSS Module Documentation
  • TimeShiftDSS
  • Artifact Subspace Reconstruction
  • Reference-free BSS-CCA
    • Sensor Noise Suppression (SNS)
    • Singular Spectrum Analysis
    • Examples Gallery
    • API reference
    • Development workflow
  • GitHub
  • Getting started
  • DSS Module Documentation
  • TimeShiftDSS
  • Artifact Subspace Reconstruction
  • Reference-free BSS-CCA
  • Sensor Noise Suppression (SNS)
  • Singular Spectrum Analysis
  • Examples Gallery
  • API reference
  • Development workflow
  • GitHub

Section Navigation

  • Sensor Noise Suppression
    • Basic Sensor Noise Suppression
    • SNS assumptions and diagnostics
  • Reference-free BSS-CCA
    • Basic reference-free BSS-CCA
    • BSS-CCA algorithm properties
  • Singular Spectrum Analysis
    • Basic SSA decomposition and frequency-guided cleaning
    • Local SSA properties on a synthetic signal
  • DSS Examples
    • Fundamentals of DSS.
    • Artifact Correction with DSS.
    • Denoising Evoked Responses.
    • Denoising Rhythms (Spectral DSS).
    • Periodic Signals (SSVEP and Quasi-Periodic).
    • Temporal Biases for Ordinary DSS.
    • Time-Frequency DSS: Spectrogram Masking.
    • Blind Source Separation and ICA Equivalence.
    • Custom DSS: Defining Your Own Bias.
    • Efficiency Benchmark: DSS vs PCA, ICA, and Averaging.
    • Adaptive Wiener Masking for Bursty Signals.
    • Joint DSS (Multi-Dataset Repeatability).
    • Cardiac DSS as an Explicit Composition
  • ZapLine Examples
    • ZapLine: Line Noise Removal Fundamentals.
    • ZapLine: Parameter Tuning and Real Data.
    • ZapLine: Epoched Data and Real Data Examples.
    • ZapLine-plus: Adaptive Cleaning on Non-Stationary Noise.
    • ZapLine-plus: Advanced Settings and Features.
    • ZapLine on MEG-like data with many co-equal noise components.
  • ASR Examples
    • Artifact Subspace Reconstruction: Basic Usage.
    • Artifact Subspace Reconstruction: Raw QC and Annotations.
    • Adaptive ASR with chunk updates
    • JugglerASR for dense short bursts
    • Visualizing ASR with mne_denoise.viz
    • Choosing the ASR cutoff.
    • Riemannian ASR versus standard ASR.
    • Adaptive ASR variants (PSP / PSW / MW).
    • Juggler ASR: DBSCAN vs GEV reference selection.
    • Choosing an ASR variant.
    • ASR on Epochs and on MEG.
    • ASR diagnostics and quality control.
    • A realistic pipeline: filter, ASR, then ICA.
    • Quantifying Dataset Noise with RMS Statistics
    • Guided ASR: preserving neural activity that ASR would over-clean.
  • Spectrum Interpolation Examples
    • Spectrum Interpolation: Power-Line Noise Removal.
  • Examples Gallery
  • Singular Spectrum Analysis

Singular Spectrum Analysis#

Examples of additive Basic SSA, frequency-guided grouping, and Teixeira local SSA on deterministic synthetic signals.

Basic SSA decomposition and frequency-guided cleaning

Basic SSA decomposition and frequency-guided cleaning

Local SSA properties on a synthetic signal

Local SSA properties on a synthetic signal

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BSS-CCA algorithm properties

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Basic SSA decomposition and frequency-guided cleaning
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