Quantum-Hybrid Neural Vector Quantization – A Mathematical Approach
2021
The paper demonstrates how to realize neural vector quantizers by means of quantum computing approaches. Particularly, we consider self-organizing maps and the neural gas vector quantizer for unsupervised learning as well as generalized learning vector quantization for classification learning. We show how quantum computing concepts can be adopted for these algorithms. The respective mathematical framework is explained in detail.
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
33
References
0
Citations
NaN
KQI