Application of artificial neural computation in topex waveform data: A case study in water ratio regression

B. Zhang, F. W. Schwartz, D. Tong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Using the TOPEX radar altimeter for land cover studies has been of great interest due to the TOPEX near global coverage and its consistent availability of waveform data for about one and a half decades from 1992 to 2005. However, the complexity of the TOPEX Sensor Data Records (SDRs) makes the recognition of the radar echoes particularly difficult. In this paper, artificial neural computation as one of the most powerful algorithms in pattern recognition is investigated for water ratio assessment over Lake of the Woods area using TOPEX reflected radar signals. Results demonstrate that neural networks have the capability in identifying water proportion from the TOPEX radar information, controlling the predicted errors in a reasonable range.

Original languageEnglish (US)
Title of host publicationProceedings of the 7th IEEE International Conference on Cognitive Informatics, ICCI 2008
Pages232-238
Number of pages7
DOIs
StatePublished - 2008
Event7th IEEE International Conference on Cognitive Informatics, ICCI 2008 - Stanford University, CA, United States
Duration: Aug 14 2008Aug 16 2008

Publication series

NameProceedings of the 7th IEEE International Conference on Cognitive Informatics, ICCI 2008

Other

Other7th IEEE International Conference on Cognitive Informatics, ICCI 2008
CountryUnited States
CityStanford University, CA
Period8/14/088/16/08

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Information Systems

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