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.