Search Results - "Mehonić, Adnan"
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Editorial: Welcome to APL Machine Learning
Published in APL machine learning (01-03-2023)Get full text
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Silicon Oxide (SiOx): A Promising Material for Resistance Switching?
Published in Advanced materials (Weinheim) (25-10-2018)“…Interest in resistance switching is currently growing apace. The promise of novel high‐density, low‐power, high‐speed nonvolatile memory devices is appealing…”
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Memristors—From In‐Memory Computing, Deep Learning Acceleration, and Spiking Neural Networks to the Future of Neuromorphic and Bio‐Inspired Computing
Published in Advanced intelligent systems (01-11-2020)“…Machine learning, particularly in the form of deep learning (DL), has driven most of the recent fundamental developments in artificial intelligence (AI). DL is…”
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Multimodal transistors as ReLU activation functions in physical neural network classifiers
Published in Scientific reports (13-01-2022)“…Artificial neural networks (ANNs) providing sophisticated, power-efficient classification are finding their way into thin-film electronics. Thin-film…”
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Hardware implementation of memristor-based artificial neural networks
Published in Nature communications (04-03-2024)“…Artificial Intelligence (AI) is currently experiencing a bloom driven by deep learning (DL) techniques, which rely on networks of connected simple computing…”
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Resistive switching in silicon suboxide films
Published in Journal of applied geophysics (01-04-2012)“…We report a study of resistive switching in a silicon-based memristor/resistive RAM (RRAM)device in which the active layer is silicon-rich silica. The…”
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Recommended Methods to Study Resistive Switching Devices
Published in Advanced electronic materials (01-01-2019)“…Resistive switching (RS) is an interesting property shown by some materials systems that, especially during the last decade, has gained a lot of interest for…”
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Brains and bytes: Trends in neuromorphic technology
Published in APL machine learning (01-06-2023)Get full text
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Simulation of Inference Accuracy Using Realistic RRAM Devices
Published in Frontiers in neuroscience (12-06-2019)“…Resistive Random Access Memory (RRAM) is a promising technology for power efficient hardware in applications of artificial intelligence (AI) and machine…”
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Complementary Metal‐Oxide Semiconductor and Memristive Hardware for Neuromorphic Computing
Published in Advanced intelligent systems (01-05-2020)“…The ever‐increasing processing power demands of digital computers cannot continue to be fulfilled indefinitely unless there is a paradigm shift in computing…”
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Webinar Recap: Fostering a New Data Culture with APL Machine Learning
Published in APL machine learning (01-09-2024)Get full text
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Nanoscale Transformations in Metastable, Amorphous, Silicon-Rich Silica
Published in Advanced materials (Weinheim) (01-09-2016)“…Electrically biasing thin films of amorphous, substoichiometric silicon oxide drives surprisingly large structural changes, apparent as density variations,…”
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Editorial: Focus issue on energy-efficient neuromorphic devices, systems and algorithms
Published in Neuromorphic computing and engineering (01-12-2023)Get full text
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badcrossbar: A Python tool for computing and plotting currents and voltages in passive crossbar arrays
Published in SoftwareX (01-07-2020)“…Crossbar arrays are a popular solution when implementing systems that have array-like architecture. With the recent developments in the field of neuromorphic…”
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Memristive, Spintronic, and 2D‐Materials‐Based Devices to Improve and Complement Computing Hardware
Published in Advanced intelligent systems (01-08-2022)“…In a data‐driven economy, virtually all industries benefit from advances in information technology—powerful computing systems are critically important for…”
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Memristor-Based Edge Detection for Spike Encoded Pixels
Published in Frontiers in neuroscience (17-01-2020)“…Memristors have many uses in machine learning and neuromorphic hardware. From memory elements in dot product engines to replicating both synapse and neuron…”
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Nonideality‐Aware Training for Accurate and Robust Low‐Power Memristive Neural Networks
Published in Advanced science (01-06-2022)“…Recent years have seen a rapid rise of artificial neural networks being employed in a number of cognitive tasks. The ever‐increasing computing requirements of…”
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Silica: Nanoscale Transformations in Metastable, Amorphous, Silicon-Rich Silica (Adv. Mater. 34/2016)
Published in Advanced materials (Weinheim) (01-09-2016)“…Electrically biasing thin films of amorphous, substoichiometric silicon oxide drives surprisingly large structural changes, apparent as density variations,…”
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A nanoscale analysis method to reveal oxygen exchange between environment, oxide, and electrodes in ReRAM devices
Published in APL materials (01-11-2021)“…The limited sensitivity of existing analysis techniques at the nanometer scale makes it challenging to systematically examine the complex interactions in…”
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Roadmap to neuromorphic computing with emerging technologies
Published in APL materials (01-10-2024)Get full text
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