Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[Unreleased]

DSS Module: Complete implementation of Denoising Source Separation
- DSS estimator with scikit-learn compatible API
- IterativeDSS for nonlinear/iterative DSS
- 20+ pluggable denoiser functions:
  - Spectral: BandpassBias, LineNoiseBias
  - Temporal: TimeShiftBias, SmoothingBias, DCTDenoiser
  - Periodic: CombFilterBias, PeakFilterBias, CycleAverageBias
  - ICA-style: KurtosisDenoiser, SkewDenoiser, TanhMaskDenoiser
- Variants: tsr, ssvep, narrowband
- Full MNE-Python integration (Raw, Epochs, Evoked)
ZapLine Module: Line noise removal algorithms
- ZapLine estimator for standard mode
- ZapLine adaptive mode (ZapLine-plus) with automatic frequency detection
- Per-chunk processing for non-stationary data
- Quality assurance with spectral checks
Visualization: Component and comparison plotting
- plot_dss_components
- plot_dss_sources
- plot_before_after
Documentation: Sphinx-based documentation with examples
- 12 DSS examples
- 5 ZapLine examples
- API reference
Testing: Comprehensive test suite with 91% coverage
- Cross-platform: Ubuntu, macOS, Windows
- Python 3.10, 3.11, 3.12, 3.13