Pokric, B., Allinson, N. M., Bergstrom, E. T. and Goodall, D. M. (1999) Combining linear filtering and radial basis function networks for accurate profile recovery. IEE Proceedings - Vision, Image and Signal Processing, 153 (6). pp. 297-305. ISSN 1350-245X
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| Item Type: | Article |
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| Item Status: | Live Archive |
Abstract
The efficient method presented for the accurate approximation of signal profiles corrupted by noise is based on a principled combination of linear and nonlinear processing. The nonlinear processing is realised using a radial basis network which is designed, trained and validated within the strict time constraints set by instrumentation requirements. The quality of profile approximation and the decision to use either linear or nonlinear processing are set by confidence limits which, in turn, are set by the best estimate of current system noise. The approach is described in terms of a novel capillary electrophoresis instrument with all processing implemented on a dedicated DSP subsystem
| Additional Information: | The efficient method presented for the accurate approximation of signal profiles corrupted by noise is based on a principled combination of linear and nonlinear processing. The nonlinear processing is realised using a radial basis network which is designed, trained and validated within the strict time constraints set by instrumentation requirements. The quality of profile approximation and the decision to use either linear or nonlinear processing are set by confidence limits which, in turn, are set by the best estimate of current system noise. The approach is described in terms of a novel capillary electrophoresis instrument with all processing implemented on a dedicated DSP subsystem |
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| Keywords: | electrophoresis, filtering theory, radial basis function networks |
| Subjects: | G Mathematical and Computer Sciences > G740 Computer Vision |
| Divisions: | College of Science > School of Computer Science |
| ID Code: | 5130 |
| Deposited On: | 02 May 2012 07:13 |
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