Publications associées à Neuromorphic engineering

Reducing circuit design complexity for neuromorphic machine learning systems based on Non-Volatile Memory arrays

Machine Learning (ML) is an attractive application of Non-Volatile Memory (NVM) arrays [1,2]. However, achieving speedup over GPUs will require minimal neuron circuit sharing and thus highly area-efficient peripheral circuitry, so that ML reads and writes ...

2017

Control of Resistive Switching in Mott Memories Based on TiN/AM4Q8/TiN MIM Devices

Giovanni De Micheli, Davide Sacchetto, Pierre-Emmanuel Julien Marc Gaillardon, Jury Sandrini

The family of AM4Q8 chalcogenide Mott insulators gained attention in recent years for its application opportunities. Here, we explore and validate the resistive switching mechanism of thin-film of GaV4S8 sandwich ...

Electrochemical Society2017

Artificial spatiotemporal touch inputs reveal complementary decoding in neocortical neurons

Silvestro Micera

Investigations of the mechanisms of touch perception and decoding has been hampered by difficulties in achieving invariant patterns of skin sensor activation. To obtain reproducible spatiotemporal patterns of activation of sensory afferents, we used an art ...

Nature Publishing Group2017

On The Robustness of a Neural Network

Rachid Guerraoui, El Mahdi El Mhamdi, Sébastien Louis Alexandre Rouault

With the development of neural networks based machine learning and their usage in mission critical applications, voices are rising against the \textit{black box} aspect of neural networks as it becomes crucial to understand their limits and capabilities. W ...

2017

All-memristive neuromorphic computing with level-tuned neurons

Stanislaw Andrzej Wozniak, Evangelos Eleftheriou, Angeliki Pantazi

In the new era of cognitive computing, systems will be able to learn and interact with the environment in ways that will drastically enhance the capabilities of current processors, especially in extracting knowledge from vast amount of data obtained from m ...

Iop Publishing Ltd2016

Neuromorphic Computing Using Non-Volatile Memory

Seyoung Kim, Yusuf Leblebici, Irem Boybat Kara, Alessandro Fumarola, Abu Sebastian, Severin Sidler

Dense crossbar arrays of non-volatile memory (NVM) devices represent one possible path for implementing massively-parallel and highly energy-efficient neuromorphic computing systems. We first review recent advances in the application of NVM devices to thre ...

Taylor & Francis Ltd2016

Label-Free Ultrasensitive Memristive Aptasensor

Giovanni De Micheli, Sandro Carrara, Ioulia Tzouvadaki

We present the very first worldwide ever-reported electrochemical biosensor based on a memristive effect and DNA aptamers. This novel device is developed to propose a completely new approach in cancer diagnostics. In this study, an affinity-based technique ...

American Chemical Society2016

Scalable Neuron Circuit Using Conductive-Bridge RAM for Pattern Reconstructions

Behnoush Attarimashalkoubeh

— A novel neuron circuit using a Cu/Ti/Al2O3-based conductive-bridge random access memory (CBRAM) device for hardware neural networks that utilize nonvolatile memories as synaptic weights is introduced. The neuronal operations are designed and proved using ...

Institute of Electrical and Electronics Engineers2016

Learning spatio-temporal patterns in the presence of input noise using phase-change memristors

Stanislaw Andrzej Wozniak, Evangelos Eleftheriou, Angeliki Pantazi

Neuromorphic systems increasingly attract research interest owing to their ability to provide biologically inspired methods of computing, alternative to the classic von Neumann architecture. In these systems, computing relies on spike-based communication b ...

2016

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Neuromorphic engineering

Reducing circuit design complexity for neuromorphic machine learning systems based on Non-Volatile Memory arrays

Control of Resistive Switching in Mott Memories Based on TiN/AM4Q8/TiN MIM Devices

Artificial spatiotemporal touch inputs reveal complementary decoding in neocortical neurons

On The Robustness of a Neural Network

Automated point-neuron simplification of data-driven microcircuit models

All-memristive neuromorphic computing with level-tuned neurons

Neuromorphic Computing Using Non-Volatile Memory

Label-Free Ultrasensitive Memristive Aptasensor

Scalable Neuron Circuit Using Conductive-Bridge RAM for Pattern Reconstructions

Learning spatio-temporal patterns in the presence of input noise using phase-change memristors

Graph Chatbot

Chattez avec Graph Search

Control of Resistive Switching in Mott Memories Based on TiN/AM4Q8/TiN MIM Devices

Reducing circuit design complexity for neuromorphic machine learning systems based on Non-Volatile Memory arrays

All-memristive neuromorphic computing with level-tuned neurons

Scalable Neuron Circuit Using Conductive-Bridge RAM for Pattern Reconstructions

Artificial spatiotemporal touch inputs reveal complementary decoding in neocortical neurons

Automated point-neuron simplification of data-driven microcircuit models

Neuromorphic Computing Using Non-Volatile Memory

On The Robustness of a Neural Network

Label-Free Ultrasensitive Memristive Aptasensor

Learning spatio-temporal patterns in the presence of input noise using phase-change memristors