This paper deals with the employment of Echo State Networks for identification of nonlinear dynamical systems in the digital audio field. The real contribution of the work is that such networks have been implemented and run in real-time on a specific PC based software platform for the first time, up to the authors knowledge. The nonlinear dynamical systems to be identified in the audio applications here addressed are the mathematical model of a commercial Valve Amplifier and the low-frequency response of a loud-speaker. Experimental results have shown that, at a certain frequency sampling rate, the ESNs considered (after the training procedure performed off-line) are able to tackle the real-time tasks successfully. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Squartini, S., Cecchi, S., Rossini, M., & Piazza, F. (2007). Echo state networks for real-time audio applications. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4493 LNCS, pp. 731–740). Springer Verlag. https://doi.org/10.1007/978-3-540-72395-0_90
Mendeley helps you to discover research relevant for your work.