/pyaec

simple and efficient python implemention of a series of adaptive filters. including time domain adaptive filters(lms、nlms、rls、ap、kalman)、nonlinear adaptive filters(volterra filter、functional link adaptive filters)、frequency domain adaptive filters(frequency domain adaptive filter、frequency domain kalman filter) for acoustic echo cancellation.

Primary LanguagePythonApache License 2.0Apache-2.0

pyaec

pyaec is a simple and efficient python implemention of a series of adaptive filters for acoustic echo cancellation.

About

This project aims to use the simplest lines of python code to implement these adaptive filters, making it easier to learn these algorithms.

List of Implementioned Adaptive Filters

Time Domain Adaptive Filters

  • Least Mean Squares Filter (LMS)
  • Block Least Mean Squares Filter (BLMS)
  • Normalized Least Mean Squares Filter (NLMS)
  • Block Normalized Least Mean Squares Filter (BNLMS)
  • Recursive Least Squares Filter (RLS)
  • Affine Projection Algorithm (APA)
  • Kalman Filter (KALMAN)

Nonlinear Adaptive Filters

  • Second Order Volterra Filter (SVF)
  • Trigonometric Functional Link Adaptive Filter (FLAF)
  • Adaptive Exponential Functional Link Adaptive Filter (AEFLAF)
  • Split Funcional Link Adaptive Filter (SFLAF)
  • Collaborative Functional Link Adaptive Filter (CFLAF)

Frequency Domain Adaptive Filters

  • Frequency Domain Adaptive Filter (FDAF)
  • Partitioned-Block-Based Frequency Domain Adaptive Filter (PFDAF)
  • Frequency Domain Kalman Filter (FDKF)
  • Partitioned-Block-Based Frequency Domain Kalman Filter (PFDKF)

Requirements

  • Python 3.6+
  • librosa
  • pyroomacoustics

Usage

python run.py

Author

ewan xu ewan_xu@outlook.com

Some Reference Books And Papers

  • Kong-Aik Lee, Woon-Seng Gan, Sen M. Kuo - Subband Adaptive Filtering Theory and Implementation

  • Simon Haykin - Adaptive Filter Theory

  • F.Kuech, E.Mabande, and G.Enzner, "State-space architecture of the partitioned-block-based acoustic echo controller,"in 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014, pp. 1295-1299: IEEE

  • A.Gurin, G.Faucon and R.Le Bouquin-Jeanns, "Nonlinear acoustic echo cancellation based on Volterra filters", IEEE Trans.Speech Audio Process., vol. 11, no. 6, pp. 672-683, Nov. 2003

  • V.Patel, V.Gandhi, S.Heda, and N.V.George, “Design of Adaptive Exponential Functional Link Network-Based Nonlinear Filters,” IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 63, no. 9, pp. 1434–1442, 2016.

  • D.Comminiello, M.Scarpiniti, L.A.Azpicueta-Ruiz, J. Arenas-Garcia, and A. Uncini, “Functional link adaptive filters for non-linear acoustic echo cancellation,”IEEE Transactions on Audio,Speech, and Language Processing, vol. 21, no. 7, pp. 1502–1512,2013