Name
Abstract | ||
|---|---|---|
This brief presents a methodology to develop recursive filters in reproducing kernel Hilbert spaces. Unlike previous approaches that exploit the kernel trick on filtered and then mapped samples, we explicitly define the model recursivity in the Hilbert space. For that, we exploit some properties of functional analysis and recursive computation of dot products without the need of preimaging or a training dataset. We illustrate the feasibility of the methodology in the particular case of the γ-filter, which is an infinite impulse response filter with controlled stability and memory depth. Different algorithmic formulations emerge from the signal model. Experiments in chaotic and electroencephalographic time series prediction, complex nonlinear system identification, and adaptive antenna array processing demonstrate the potential of the approach for scenarios where recursivity and nonlinearity have to be readily combined. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/TNNLS.2013.2293871 | Neural Networks and Learning Systems, IEEE Transactions |
Keywords | Field | DocType |
Hilbert spaces,IIR filters,adaptive filters,recursive filters,stability,time series,adaptive antenna array processing,adaptive filtering,chaotic time series prediction,complex nonlinear system identification,controlled stability,electroencephalographic time series prediction,functional analysis,infinite impulse response filter,kernel Hilbert spaces,memory depth,recursive filtering,Adaptive,autoregressive and moving-average,filter,kernel methods,recursive,recursive. | Computer science,Adaptive filter,Artificial intelligence,Hilbert space,Kernel (linear algebra),Mathematical optimization,Pattern recognition,Infinite impulse response,Nonlinear system identification,Algorithm,Kernel adaptive filter,Kernel method,Reproducing kernel Hilbert space | Journal |
Volume | Issue | ISSN |
25 | 7 | 2162-237X |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Devis Tuia | 1 | 1715 | 101.88 |
| Jordi Muñoz-Marí | 2 | 559 | 40.11 |
| José Luis Rojo-Álvarez | 3 | 270 | 41.81 |
| Manel Martínez-ramón | 4 | 216 | 19.66 |
| Gustavo Camps-Valls | 5 | 2011 | 114.02 |
| Munoz-Mari, J. | 6 | 9 | 1.65 |
| Rojo-Alvarez, J.L. | 7 | 67 | 7.44 |
| Martinez-Ramon, M. | 8 | 0 | 0.34 |