IET Signal Processing publishes novel contributions in signal processing including: 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.