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Found 12 papers, 0 papers with code
Advancing Neuromorphic Computing: Mixed-Signal Design Techniques Leveraging Brain Code Units and Fundamental Code Units
This paper introduces a groundbreaking digital neuromorphic architecture that innovatively integrates Brain Code Unit (BCU) and Fundamental Code Unit (FCU) using mixedsignal design methodologies.
NEUROSEC: FPGA-Based Neuromorphic Audio Security
Neuromorphic systems, inspired by the complexity and functionality of the human brain, have gained interest in academic and industrial attention due to their unparalleled potential across a wide range of applications.
Harnessing FPGA Technology for Enhanced Biomedical Computation
This research delves into sophisticated neural network frameworks like Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-Term Memory Networks (LSTMs), and Deep Belief Networks (DBNs) for improved analysis of ECG signals via Field Programmable Gate Arrays (FPGAs).
HPCNeuroNet: Advancing Neuromorphic Audio Signal Processing with Transformer-Enhanced Spiking Neural Networks
This paper presents a novel approach to neuromorphic audio processing by integrating the strengths of Spiking Neural Networks (SNNs), Transformers, and high-performance computing (HPC) into the HPCNeuroNet architecture.
Astrocyte-Integrated Dynamic Function Exchange in Spiking Neural Networks
This paper presents an innovative methodology for improving the robustness and computational efficiency of Spiking Neural Networks (SNNs), a critical component in neuromorphic computing.
Exploiting FPGA Capabilities for Accelerated Biomedical Computing
This study presents advanced neural network architectures including Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-Term Memory Networks (LSTMs), and Deep Belief Networks (DBNs) for enhanced ECG signal analysis using Field Programmable Gate Arrays (FPGAs).
A Survey of Spiking Neural Network Accelerator on FPGA
Due to the ability to implement customized topology, FPGA is increasingly used to deploy SNNs in both embedded and high-performance applications.
Design optimization for high-performance computing using FPGA
We optimize Tensil AI's open-source inference accelerator for maximum performance using ResNet20 trained on CIFAR in this paper in order to gain insight into the use of FPGAs for high-performance computing.
An Energy-Efficient Reconfigurable Autoencoder Implementation on FPGA
We compare the different results achieved with the FPGA and GPU-based implementations and then discuss the pros and cons of each implementation.
A Coupled Neural Circuit Design for Guillain-Barre Syndrome
Thus, the resulting coupled analog hardware neuron model can be a proposed model for the simulation of reduced nerve conduction.
Multiscale Voxel Based Decoding For Enhanced Natural Image Reconstruction From Brain Activity
Reconstructing perceived images from human brain activity monitored by functional magnetic resonance imaging (fMRI) is hard, especially for natural images.
Implementing Spiking Neural Networks on Neuromorphic Architectures: A Review
Here, we provide a comprehensive overview of such frameworks proposed for both, platform-based design and hardware-software co-design.
