Novel Neuromorphic Artificial Neural Network Circuit Architecture

A technical paper titled “Mosaic: in-memory computing and routing for small-world spike-based neuromorphic systems” was published by researchers at CEA-LETI Université Grenoble Alpes, University of Zurich and ETH Zurich. Abstract: "The brain’s connectivity is locally dense and globally sparse, forming a small-world graph—a principle prevalent in the evolution of various species, sugg... » read more

Analog Planar Memristor Device: Developing, Designing, and Manufacturing

A new technical paper titled "Analog monolayer SWCNTs-based memristive 2D structure for energy-efficient deep learning in spiking neural networks" was published by researchers at Delft University of Technology and Khalifa University. Abstract: "Advances in materials science and memory devices work in tandem for the evolution of Artificial Intelligence systems. Energy-efficient computation... » read more

A Survey Of Recent Advances In Spiking Neural Networks From Algorithms To HW Acceleration

A technical paper titled “Recent Advances in Scalable Energy-Efficient and Trustworthy Spiking Neural networks: from Algorithms to Technology” was published by researchers at Intel Labs, University of California Santa Cruz, University of Wisconsin-Madison, and University of Southern California. Abstract: "Neuromorphic computing and, in particular, spiking neural networks (SNNs) have becom... » read more

Neuromorphic Computing: Graphene-Based Memristors For Future AI Hardware From Fabrication To SNNs

A technical paper titled “A Review of Graphene-Based Memristive Neuromorphic Devices and Circuits” was published by researchers at James Cook University (Australia) and York University (Canada). Abstract: "As data processing volume increases, the limitations of traditional computers and the need for more efficient computing methods become evident. Neuromorphic computing mimics the brain's... » read more

Analog Circuits Enabling Learning in Mixed-Signal Neuromorphic SNNs, With Tristate Stability and Weight Discretization Circuits

A technical paper titled “Neuromorphic analog circuits for robust on-chip always-on learning in spiking neural networks” was published by researchers at University of Zurich and ETH Zurich. Abstract: "Mixed-signal neuromorphic systems represent a promising solution for solving extreme-edge computing tasks without relying on external computing resources. Their spiking neural network circui... » read more

DW-MTJ Devices For Noise-Resilient Networks For Neuromorphic Computing On The Edge

A technical paper titled "Stochastic domain wall-magnetic tunnel junction artificial neurons for noise-resilient spiking neural networks" was published by researchers at University of Texas at Austin. Abstract: "The spatiotemporal nature of neuronal behavior in spiking neural networks (SNNs) makes SNNs promising for edge applications that require high energy efficiency. To realize SNNs in har... » read more

Recent Developments in Neuromorphic Computing, Focusing on Hardware Design and Reliability

A new technical paper titled "Special Session: Neuromorphic hardware design and reliability from traditional CMOS to emerging technologies" was published by researchers at Univ. Lyon, Ecole Centrale de Lyon, Univ. Grenoble Alpes, Hewlett Packard Labs, CEA-LETI, and Politecnico di Torino. Abstract "The field of neuromorphic computing has been rapidly evolving in recent years, with an incre... » read more

Spiking Neural Networks: Hardware & Algorithm Developments

A new technical paper titled "Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware" was published by researchers at Purdue University, Pennsylvania State University, and Yale University. Excerpt from Abstract: "In this article, we outline several strides that neuromorphic computing based on spiking neural networks (SNNs) has taken over the recent past, a... » read more

Neuromorphic Computing: Challenges, Opportunities Including Materials, Algorithms, Devices & Ethics

This new research paper titled "2022 roadmap on neuromorphic computing and engineering" is from numerous researchers at Technical University of Denmark, Instituto de Microelectrónica de Sevilla, CSIC, University of Seville, and many others. Partial Abstract: "The aim of this roadmap is to present a snapshot of the present state of neuromorphic technology and provide an opinion on the chall... » read more

Novel Spintronic Neuro-mimetic Device Emulating the LIF Neuron Dynamics w/High Energy Efficiency & Compact Footprints

New technical paper titled "Noise resilient leaky integrate-and-fire neurons based on multi-domain spintronic devices" from researchers at Purdue University. Abstract "The capability of emulating neural functionalities efficiently in hardware is crucial for building neuromorphic computing systems. While various types of neuro-mimetic devices have been investigated, it remains challenging to... » read more

← Older posts