Embedded intelligence (EI) is an emerging research field and has the objective to
incorporate machine learning algorithms and intelligent decision-making capabilities into …

Over the past two decades, the use of low power Field Programmable Gate Arrays (FPGA)
for the acceleration of various vision systems mainly on embedded devices have become …

Abstract The Self-Organizing Map (SOM) has attracted much research in diverse fields of
study, where it has been successfully applied to a wide range of artificial intelligence …

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

The design of neuromorphic chips aims to develop electronic circuits dedicated to executing
artificial neural networks, mainly by exploring parallel processing. Unsupervised learning …

The Self-Organizing Map algorithm has been proven and demonstrated to be a useful
paradigm for unsupervised machine learning of two-dimensional projections 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 …

This paper presents an embedded system-on-a-programmable-chip (SoPC)-based parallel
ant colony optimization (ACO) algorithm and its application to optimal motion controller …

A potential threat to embedded systems is the execution of unknown or malicious software
capable of triggering harmful system behavior, aimed at theft of sensitive data or causing …

This paper presents an approach for substantial reduction of the training and operating
phases of Self-Organizing Maps in tasks of 2-D projection of multi-dimensional symbolic …