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IET Signal Processing publishes topics such as algorithm advances in single and multi-dimensional, linear and non-linear, recursive and non-recursive digital filters and multi-rate filter banks; the application of chaos theory and neural network based approaches to signal processing.

Topics covered by scope include:

  • advances in single and multi-dimensional filter design and implementation
  • linear and nonlinear, fixed and adaptive digital filters and multirate filter banks
  • statistical signal processing techniques and analysis
  • classical, parametric and higher order spectral analysis
  • signal transformation and compression techniques, including time-frequency analysis
  • system modelling and adaptive identification techniques
  • machine learning based approaches to signal processing
  • Bayesian methods for signal processing, including Monte-Carlo Markov-chain and particle filtering techniques
  • theory and application of blind and semi-blind signal separation techniques
  • signal processing techniques for analysis, enhancement, coding, synthesis and recognition of speech signals
  • direction-finding and beamforming techniques for audio and electromagnetic signals
  • analysis techniques for biomedical signals
  • baseband signal processing techniques for transmission and reception of communication signals
  • signal processing techniques for data hiding and audio watermarking

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