Digital Filters and Signal Processing

Digital filters, together with signal processing, are being employed in the new technologies and information systems, and are implemented in different areas and applications. Digital filters and signal processing are used with no costs and they can be adapted to different cases with great flexibility and reliability. This book presents advanced developments in digital filters and signal process methods covering different cases studies. They present the main essence of the subject, with the principal approaches to the most recent mathematical models that are being employed worldwide

Applications of loudness models in audio engineering

This thesis investigates the application of perceptual models to areas of audio engineering, with a particular focus on music production. The goal was to establish efficient and practical tools for the measurement and control of the perceived loudness of musical sounds. Two types of loudness model were investigated: the single-band model and the multiband excitation pattern (EP) model. The heuristic single-band devices were designed to be simple but sufficiently effective for real-world application, whereas the multiband procedures were developed to give a reasonable account of a large body of psychoacoustic findings according to a functional model of the peripheral hearing system. The research addresses the extent to which current models of loudness generalise to musical instruments, and whether can they be successfully employed in music applications. The domain-specific disparity between the two types of model was first tackled by reducing the computational load of state-of-the-art EP models to allow for fast but low-error auditory signal processing. Two elaborate hearing models were analysed and optimised using musical instruments and speech as test stimuli. It was shown that, after significantly reducing the complexity of both procedures, estimates of global loudness, such as peak loudness, as well as the intermediate auditory representations can be preserved with high accuracy. Based on the optimisations, two real-time applications were developed: a binaural loudness meter and an automatic multitrack mixer. This second system was designed to work independently of the loudness measurement procedure, and therefore supports both linear and nonlinear models. This allowed for a single mixing device to be assessed using different loudness metrics and this was demonstrated by evaluating three configurations through subjective assessment. Unexpectedly, when asked to rate both the overall quality of a mix and the degree to which instruments were equally loud, listeners preferred mixes generated using heuristic single-band models over those produced using a multiband procedure. A series of more systematic listening tests were conducted to further investigate this finding. Subjective loudness matches of musical instruments commonly found in western popular music were collected to evaluate the performance of five published models. The results were in accord with the application-based assessment, namely that current EP procedures do not generalise well when estimating the relative loudness of musical sounds which have marked differences in spectral content. Model specific issues were identified relating to the calculation of spectral loudness summation (SLS) and the method used to determine the global-loudness percept of time-varying musical sounds; associated refinements were proposed. It was shown that a new multiband loudness model with a heuristic loudness transformation yields superior performance over existing methods. This supports the idea that a revised model of SLS is needed, and therefore that modification to this stage in existing psychoacoustic procedures is an essential step towards the goal of achieving real-world deployment

Computational Intelligence in Electromyography Analysis

Electromyography (EMG) is a technique for evaluating and recording the electrical activity produced by skeletal muscles. EMG may be used clinically for the diagnosis of neuromuscular problems and for assessing biomechanical and motor control deficits and other functional disorders. Furthermore, it can be used as a control signal for interfacing with orthotic and/or prosthetic devices or other rehabilitation assists. This book presents an updated overview of signal processing applications and recent developments in EMG from a number of diverse aspects and various applications in clinical and experimental research. It will provide readers with a detailed introduction to EMG signal processing techniques and applications, while presenting several new results and explanation of existing algorithms. This book is organized into 18 chapters, covering the current theoretical and practical approaches of EMG research