Adaptive near minimum error rate training for neural networks with application to multiuser detection in CDMA communication systems
Adaptive training of neural networks is typically done using some stochastic gradient algorithm that tries to minimize the mean square error (MSE). For many applications, such as channel equalization and code-division multiple-access (CDMA) multiuser detection, the goal is to minimize the error prob...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
2005-07.
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| Subjects: | |
| Online Access: | Get fulltext |