Final Progress Report on Robust and/or Adaptive Filtering by Neural Networks
Abstract
The purpose of this project is to develop a general and systematic approach to robust and/or adaptive filtering in the presence of uncertain environmental parameters. Mathematical justification, intuitive understanding and numerical confirmation of risk-averting neural networks for general robust processing with various degrees of robustness have been achieved. Those of neural networks with long- and short-term memories for general adaptive processing have also been accomplished. A novel method of training neural networks that is effective in avoiding poor local minima has been discovered. This discovery is a major breakthrough in the development of neural computing. Robust neural filters have been mathematically justified and numerically tested. General adaptive filtering and general robust adaptive filtering turned out to be much more difficult than expected. Nevertheless, schemes for them by neural computing, which are mathematically natural and convincing, have finally been conceived.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 30, 2002
- Accession Number
- ADA416027
Entities
People
- James T. Lo