3 citations · 5 across the 9 of their papers we have counts for
5 papers · 1 filter
IzhiRISC-V -- a RISC-V-based Processor with Custom ISA Extension for Spiking Neuron Networks Processing with Izhikevich Neurons
Wiktor J. Szczerek, Artur Podobas
Spiking Neural Network processing promises to provide high energy efficiency due to the sparsity of the spiking events. However, when realized on general-purpose hardware -- such a…
Embedded FPGA Acceleration of Brain-Like Neural Networks: Online Learning to Scalable Inference
Muhammad Ihsan Al Hafiz, Naresh Ravichandran, Anders Lansner +2
Edge AI applications increasingly require models that can learn and adapt on-device with minimal energy budget. Traditional deep learning models, while powerful, are often overpara…
FPGA-Based Neural Network Accelerators for Space Applications: A Survey
Pedro Antunes, Artur Podobas
Space missions are becoming increasingly ambitious, necessitating high-performance onboard spacecraft computing systems. In response, field-programmable gate arrays (FPGAs) have ga…
A Reconfigurable Stream-Based FPGA Accelerator for Bayesian Confidence Propagation Neural Networks
Muhammad Ihsan Al Hafiz, Naresh Ravichandran, Anders Lansner +2
Brain-inspired algorithms are attractive and emerging alternatives to classical deep learning methods for use in various machine learning applications. Brain-inspired systems can f…
A Quarter of a Century of Neuromorphic Architectures on FPGAs -- an Overview
Wiktor J. Szczerek, Artur Podobas
Neuromorphic computing is a relatively new discipline of computer science, where the principles of biological brain's computation and memory are used to create a new way of process…