The method performs continuously vector quantization over a distribution that changes over time. It deals with both sudden changes and continuous ones, and is ...

The method performs continuously vector quantization over a distribution that changes over time. It deals with both sudden changes and continuous ones.

In this paper, an original method extended from growing neural gas (GNG-T) [B. Fritzke, A growing neural gas network learns topologies, in: G. Tesauro, ...

The method performs continuously vector quantization over a distribution that changes over time. It deals with both sudden changes and continuous ones, and is ...

This work proposes a new growth approach that, when applied to MS-BL-GNG, significantly increases the learning speed and adaptability of dynamic data ...

This work describes a neural network based architecture that represents and estimates object motion in videos. This architecture addresses multiple computer ...

In this paper, an original method extended from growing neural gas (GNG-T) [B. Fritzke, A growing neural gas network learns topologies, in: G. Tesauro, ...

author = {Hervé Frezza-Buet}, title = {{Following non-stationary distributions by controlling the vector quantization accuracy of a growing neural gas network}} ...

Following non-stationary distributions by controlling the vector quantization accuracy of a growing neural gas network. H Frezza-Buet. Neurocomputing 71 (7-9) ...

Following non-stationary distributions by controlling the vector quantization accuracy of a growing neural gas network · Author Picture Hervé Frezza-Buet.