Spiking Neural Networks Based on OxRAM Synapses for Real-Time Unsupervised Spike Sorting [PDF]
Frontiers in Neuroscience, 2016 In this paper, we present an alternative approach to perform spike sorting of complex brain signals based on spiking neural networks (SNN). The proposed architecture is suitable for hardware implementation by using RRAM technology for the implementation ...
Elisa Vianello, Blaise Yvert
exaly +7 more sources
Compact Modeling Solutions for Oxide-Based Resistive Switching Memories (OxRAM)
Journal of Low Power Electronics and Applications, 2014 Emerging non-volatile memories based on resistive switching mechanisms attract intense R&D efforts from both academia and industry. Oxide-based Resistive Random Acces Memories (OxRAM) gather noteworthy performances, such as fast write/read speed, low
Weisheng Zhao, Jean-Michel Portal
exaly +4 more sources
Rethinking 1T1R architecture and OxRAM stack for memristive neural network inference in-memory
Frontiers in NanotechnologyNeural Network hardware in-memory implementations based on memristive synapses are a promising path towards energy efficient Edge computing. Among others, Oxide-based Resistive Random Access Memory (OxRAMs) devices utilization for synaptic weight ...
François Andrieu
exaly +4 more sources
Hardware-Efficient Stochastic Binary CNN Architectures for Near-Sensor Computing [PDF]
Frontiers in Neuroscience, 2022 With recent advances in the field of artificial intelligence (AI) such as binarized neural networks (BNNs), a wide variety of vision applications with energy-optimized implementations have become possible at the edge.
Vivek Parmar +3 more
doaj +2 more sources
Self-Organizing Neural Networks Based on OxRAM Devices under a Fully Unsupervised Training Scheme [PDF]
Materials, 2019 A fully-unsupervised learning algorithm for reaching self-organization in neuromorphic architectures is provided in this work. We experimentally demonstrate spike-timing dependent plasticity (STDP) in Oxide-based Resistive Random Access Memory (OxRAM ...
Javier Martin +2 more
exaly +4 more sources
Corrigendum: Spiking Neural Networks Based on OxRAM Synapses for Real-Time Unsupervised Spike Sorting [PDF]
Frontiers in Neuroscience, 2017 Thilo Werner +13 more
doaj +2 more sources
Neuromorphic Low-Power Inference on Memristive Crossbars With On-Chip Offset Calibration
IEEE Access, 2021 Monolithic integration of silicon with nano-sized Redox-based resistive Random-Access Memory (ReRAM) devices opened the door to the creation of dense synaptic connections for bio-inspired neuromorphic circuits.
Charanraj Mohan +5 more
doaj +1 more source
In-Memory Computation Based Mapping of Keccak-f Hash Function
Frontiers in Nanotechnology, 2022 Cryptographic hash functions play a central role in data security for applications such as message authentication, data verification, and detecting malicious or illegal modification of data.
Sandeep Kaur Kingra +2 more
doaj +1 more source
Endurance of 2 Mbit Based BEOL Integrated ReRAM
IEEE Access, 2022 In this work, we experimentally characterize the endurance of 2 Mbit resistive switching random access memories (ReRAMs) from a 16 MBit test-chip. Here, very rare failure events where the memory cells become stuck in the low-resistive state (LRS) are ...
Nils Kopperberg +6 more
doaj +1 more source
IEEE Access, 2022 Training a CNN involves computationally intense optimization algorithms to fit the network using a training dataset, to update the network weight for inferencing and then pattern classification.
Nagaraj Lakshmana Prabhu +1 more
doaj +1 more source