Data di Pubblicazione:
2001
Citazione:
Multiscale models for data processing : an experimental sensitivity analysis / S. Ferrari, N.A. Borghese, V. Piuri. - In: IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT. - ISSN 0018-9456. - 50:4(2001 Aug), pp. 995-1002. [10.1109/19.948314]
Abstract:
Hierarchical radial basis functions (HRBFs) networks have been recently introduced as a tool for adaptive multiscale image reconstruction from range data. These are based on local operation on the data and are able to give a sparse approximation. In this paper, HRBFs are reframed for the regular sampling case, and they are compared with wavelet decomposition.
Results show that HRBFs, thanks to their constructive approach to approximation, are much more tolerant on errors in the parameters when errors occur in the configuration phase.
Tipologia IRIS:
01 - Articolo su periodico
Keywords:
Basis functions; Function spaces; Iterative decomposition; Multiresolutlon analysis; Multiscale signal decomposition; Quantization error; RBF networks; Robustness; Sensitivity; Signal processing; Wavelets
Elenco autori:
S. Ferrari, N.A. Borghese, V. Piuri
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