Abstract
Sound and Vision Engineering as an interdisciplinary branch of science should quickly assimilate new methods and new technologies. Meanwhile, there exist some advanced and well developed methods for analyzing and processing of data or signals that are only occasionally applied to this domain of science. These methods emerged from the artificial intelligence approach to image and signal processing problems. In the paper the intelligent algorithms, such as neural networks, fuzzy logic, genetic algorithm and the rough set method will be presented with regards to their applications to sound and vision engineering. The paper will include a practical demonstration of results achieved with intelligent algorithms applications to: bi-modal recognition of speech employing NN-PCA algorithm, perceptually-oriented noisy data processing methods, advanced sound acquisition, GA algorithm-based digital signal processing for telecommunication applications and others.
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© 2006 Springer-Verlag Berlin Heidelberg
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Czyzewski, A. (2006). Applications of Knowledge Technologies to Sound and Vision Engineering. In: Wang, GY., Peters, J.F., Skowron, A., Yao, Y. (eds) Rough Sets and Knowledge Technology. RSKT 2006. Lecture Notes in Computer Science(), vol 4062. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11795131_9
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DOI: https://doi.org/10.1007/11795131_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-36297-5
Online ISBN: 978-3-540-36299-9
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