| 摘要 |
Signatures of entities to be recognized are assumed to be temporal scans of energy. They are converted to digital descriptor sets. Noise disruptions of signals can produce extra descriptors, losses of descriptors, and various deleterious distortions. Unique one-many descriptor matching and resulting descriptor enhancements greatly improve recognitions in hostile environments. Templates derived from entities are group-edited to increase auto-correlation scores (correct recognitions), while decreasing cross-correlation scores (incorrect recognitions). Recognitions become far more robust.
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