Abstract
NeuroSpectraNet demonstrated that neural processing power can be harnessed for anal. of SSIMS spectra. If a spectrum similar to an unknown exist in NeuroSpectraNet's database, it would efficiently and correctly identify the unknown in a matter of seconds. If an unknown is so unique that it is completely new to NeuroSpectraNet's self-organizing mechanism, NeuroSpectraNet is designed to help the analyst to correctly identify predefined functionalities that may be present in the unknown. Because the anal. is fast and reliable, the spectrometrist can focus his attention on more complex tasks better armed. [on SciFinder (R)]
| Original language | English |
|---|---|
| Title of host publication | Second. Ion Mass Spectrom., SIMS XII, Proc. Int. Conf., 12th |
| Pages | 805-808 |
| Number of pages | 4 |
| Publication status | Published - 2000 |
Keywords
- Simulation and Modeling (neural network
- NeuroSpectraNet - self-organizing neural network mechanism for interpretation of complex SSIMS spectra)
- Secondary-ion mass spectrometry (static
- neuroSpectraNet organizing neural network static SIMS