Projects per year
Abstract
Finding an optimal representation of a signal in an over-complete dictionary is often quite difficult. Since general results in this field are not very application friendly it truly helps to specify the framework as much as possible. We investigate the method Minimum Fuel Neural Network (MFNN) for finding sparse representations of music signals. This method is a set of two ordinary differential equations. We argue that the most important parameter for optimal use of this method is the discretization step size, and we demonstrate that this can be a priori determined. This significantly speeds up the convergence of the MFNN to the optimal sparse solution.
| Original language | Danish |
|---|---|
| Title of host publication | Proceedings of IEEE International Conference on Accoustics, Speech and Signal Processing |
| Number of pages | 4 |
| Volume | 4 |
| Publication date | 2004 |
| Pages | 301-304 |
| Publication status | Published - 2004 |
| Event | IEEE International Conference on Acoustics, Speech, and Signal Processing - Montreal, Canada Duration: 17 May 2004 → 21 May 2004 |
Conference
| Conference | IEEE International Conference on Acoustics, Speech, and Signal Processing |
|---|---|
| Country/Territory | Canada |
| City | Montreal |
| Period | 17/05/2004 → 21/05/2004 |
Projects
- 1 Finished
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WAVES: Wavelets in Audio/Visual Electronic Systems
Stoustrup, J., la Cour-Harbo, A., Andersen, P., Pedersen, T. S., Odgaard, P. F., Vidal Sanchez, E., Bendtsen, J. D., Christensen, H. V., Endelt, L. Ø., Borup, L., Nielsen, M., Hansen, P. C., Christensen, O., Søndergaard, P. L., Skjølstrup, C. E., Verbraak, B., Fløe Mikkelsen, H., Nissen, P. A., Madsen, O. & Thorsen, P.
Danish Technical Research Foundation
30/06/2007 → 01/09/2009
Project: Research