Hardware implementation of the neural gas
F. Ancona, Stefano Rovetta, Rodolfo Zunino · Proceedings of International Conference on Neural Networks (ICNN'97) · 2002
The paper presents a hardware implementation of the neural gas (NGAS) algorithm. The NGAS is based on vector quantization and is applied to very low bit-rate video compression. The algorithm exhibits interesting properties that can be exploited in an HW realization. The modular structure provides inherent parallelism and can therefore be regarded as an open architecture. The neuro-board interfaces to a PC through a standard ISA bus. The novelty of the proposed solution lies in providing a PC-based configurable HW support for VQ training joining affordable costs with satisfactory effectiveness. Simplicity and easy control for HW tests and SW development represent the basic advantages of the overall approach.