Improving the training and testing speed and the ability of generalization in learning vector quantization-DVQ

Learning vector quantization (LVQ) is a nearest neighbor classifier very close to the self-organizing feature map classifier. A novel method called dynamic vector quantization (DVQ) is proposed for improving the ability to generalize and the learning and testing speed. DVQ is evaluated on speech data and synthetic data. DVQ always gives best results with fewer reference vectors than LVQ2. On speech experiments, DVQ shows an improvement of about 5% in the recognition rate, and the learning speed is three times faster