Self-organizing feature maps (SOMs) are commonly used technique for clustering and data
dimensionality reduction in many application fields. Indeed, their inherent property of …

Many self-organizing maps (SOMs) implemented on hardware restrict their neighborhood
function values to negative powers of two. In this paper, we propose a novel hardware …

In this paper we compare a scalable FPGA-based hardware accelerator for the emulation of
Self-Organizing Feature Maps (SOMs) with a multi-threaded software implementation on a …

This paper proposes a hardware SOM architecture with nested structure. The proposed
hardware SOM is made of a single module, and the module is made of four smaller …

A framework to perform hardware-in-the-loop (HIL) simulations in the designflow of digital
controllers, based on Field Programmable Gate Array (FPGA) technology, is presented. The …

The advantage in multiprocessors is the performance speedup obtained with processorlevel
parallelism. Similarly, the flexibility for application-specific adaptability is the advantage in …

This paper proposes a new scalable hardware SOM architecture in which neurons can
easily be increased. Learning of SOM is made of two operations, ie, winner search and …

Machine learning applications have gained substantial recognition in recent years due to
their significant impact on a myriad of sectors such as healthcare, automation, and artificial …

Future increases in computing power strongly rely on miniaturization, large scale integration,
and parallelization. Yet, approaching the nanometer realm poses new challenges in terms of …

Hyperspectral imaging has been proven to be a viable tool for automated food inspection
that is non-invasive and on-line capable. In this contribution a hardware implemented Self …