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• Natural DNA biopolymer synaptic emulator for neuromorphic computing
  crossref Yueh-Cheng Lin, Tzu-Hsin Hsiao, Yi-Ting Li, Lin-Di Huang 等 2023-01-06T12:00:08Z 置信度 0.70
• Mixed-Signal Neuromorphic Computing Circuits Using Hybrid CMOS-RRAM Integration
  crossref Vishal Saxena 2020-12-29T20:32:46Z 置信度 0.70
• Building Reservoir Computing Hardware Using Low Energy-Barrier Magnetics
  crossref Samiran Ganguly, Avik W. Ghosh 2020-07-28T04:42:57Z 置信度 0.70
• Neuromorphic Learning VLSI Systems: A Survey
  crossref Gert Cauwenberghs 2007-08-25T22:15:23Z 置信度 0.70
• Memristive-based in-memory computing: from device to large-scale CMOS integration
  Abstract With the rapid emergence of in-memory computing systems based on memristive technology, the integration of such memory devices in large-scale architectures is one of the main aspects to tackle. In this work we present a study of HfO 2 -based memristiv…
  crossref E Perez-Bosch Quesada, E Perez, M Kalishettyhalli Mahadevaiah, C Wenger 2021-10-06T06:28:22Z 置信度 0.70
• Scaled resistively-coupled VO2 oscillators for neuromorphic computing
  crossref Elisabetta Corti, Bernd Gotsmann, Kirsten Moselund, Adrian M. Ionescu 等 2019-11-25T20:11:39Z 置信度 0.70
• Multilayer redox-based HfOx/Al2O3/TiO2 memristive structures for neuromorphic computing
  Abstract Redox-based memristive devices have shown great potential for application in neuromorphic computing systems. However, the demands on the device characteristics depend on the implemented computational scheme and unifying the desired properties in one s…
  crossref Seongae Park, Benjamin Spetzler, Tzvetan Ivanov, Martin Ziegler 2022-10-29T17:02:48Z 置信度 0.70
• Neuromorphic Computing-Enabled Digital Twin Framework for Sustainable IT Supply Chain Integration in Smart Urban Ecosystems
  The convergence of neuromorphic computing, digital twin technologies, and sustainable supply chain management presents unprecedented opportunities for transforming urban cyber-physical systems. This viewpoint paper introduces a novel conceptual framework that …
  crossref Viraj P. Tathavadekar, Nitin R. Mahankale 2025-11-28T09:27:44Z 置信度 0.70
• Novel Approaches for Neuromorphic Computing: Materials, Concepts and Devices
  crossref 2020-09-21T19:00:52Z 置信度 0.70
• Neuromorphic Computing Systems with Emerging Nonvolatile Memories: A Circuits and Systems Perspective
  crossref Bonan Yan, Ziru Li, Brady Taylor, Hai Li 等 2020-09-22T20:24:53Z 置信度 0.70
• Neuromorphic In-Memory Computing For Solving Convection-Diffusion Systems ¹
  crossref Angela Slavova, Spiridon Nikolaidis, Ventsislav Ignatov 2026-07-31T18:16:44Z 置信度 0.70
• Neuromorphic Computing in the Study of Neuroplasticity in Astronauts in Microgravity
  crossref Anahí Quintero Granados, Alan Rosas Palacios, Yuritzi Elena Ordaz Huerta, Jair Molina Arce 等 2026-01-16T14:22:34Z 置信度 0.70
• 1398 NEGF modelling of a single-qubit operation: initialization-manipulation-measurement
  crossref 2026-07-06T19:15:47Z 置信度 0.70
• Front Matter
  crossref 2024-01-02T21:15:12Z 置信度 0.70
• A universal neuromorphic vision processing system
  crossref Hongwei Tan, Sebastiaan van Dijken 2024-11-12T10:01:48Z 置信度 0.70
• A neuromorphic multi-scale approach for heart rate and state detection
  Abstract With the advent of novel sensor and machine learning technologies, it is becoming possible to develop wearable systems that perform continuous recording and processing of biosignals for health or body state assessment. For example, modern smartwatches…
  crossref Chiara De Luca, Mirco Tincani, Giacomo Indiveri, Elisa Donati 2024-12-31T03:34:27Z 置信度 0.70
• Towards ARSPI-NET: Advancing EEG Feature Extraction with Neuromorphic Algorithms
  crossref Andrew Lane, Wendy Tang, Brady Nelson 2024-12-27T14:09:04Z 置信度 0.70
• Design and investigation of various memristor models for neuromorphic applications
  crossref Shailendra Singh, Raghav Dwivedi, Jeetendra Singh, Balwinder Raj 2024-01-21T05:58:12Z 置信度 0.70
• SoftHebb: Bayesian inference in unsupervised Hebbian soft winner-take-all networks
  Abstract Hebbian plasticity in winner-take-all (WTA) networks is highly attractive for neuromorphic on-chip learning, owing to its efficient, local, unsupervised, and on-line nature. Moreover, its biological plausibility may help overcome important limitations…
  crossref Timoleon Moraitis, Dmitry Toichkin, Adrien Journé, Yansong Chua 等 2022-11-30T06:23:58Z 置信度 0.70
• Exploring response time and synaptic plasticity in P3HT ion-gated transistors for neuromorphic computing: impact of P3HT molecular weight and film thickness
  Response time and plasticity of P3HT-IGTs can be controlled by engineering input stimuli, P3HT molecular weight and channel thickness.
  crossref Ramin Karimi Azari, Zhaojing Gao, Alexandre Carrière, Clara Santato 2024-02-29T16:41:16Z 置信度 0.70
• The more the merrier: running multiple neuromorphic components on-chip for robotic control
  Abstract It has long been realized that neuromorphic hardware offers benefits for the domain of robotics such as low energy, low latency, as well as unique methods of learning. In aiming for more complex tasks, especially those incorporating multimodal data, o…
  crossref Evan Eames, Priyadarshini Kannan, Ronan Sangouard, Philipp Plank 等 2026-02-25T22:50:12Z 置信度 0.70
• Text Sentiment and Semantic Networks Analysis for MOOC Review Texts
  crossref Hua Jiang, Qing Guo, Feng Jiang 2024-03-19T14:09:52Z 置信度 0.70
• Neuromorphic hardware based on memristive nanodevices for seizure detection and recovery
  Abstract During the last decades, neuromorphic engineers have developed specific hardware designed to build efficient computing systems inspired by the structure of the human brain. The emergence of nanoscale memristors provided these systems with a new compon…
  crossref Iván Díez-de-los-Ríos, Javad Farsani, Saverio Ricci, Davide Bridarolli 等 2026-01-21T22:51:09Z 置信度 0.70
• FERROELECTRIC THIN FILMS FOR NEUROMORPHIC COMPUTING: SYNTHESIS, CHARACTERIZATION, AND DEVICE INTEGRATION
  The limitations of conventional von Neumann computing architectures in handling complex, data-intensive tasks have spurred significant interest in brain-inspired neuromorphic computing. A critical challenge in this field is the development of hardware that can…
  crossref Nurul Huda, Amin Zaki, Nong Chai, Siti Shofiah 2026-07-20T05:06:23Z 置信度 0.70
• Algebraic Quantum-AI Co-Design of Energy-Adaptive Semiconductor Architectures for Edge Intelligence and Neuromorphic Computing
  Abstract This study investigates the algebraic co-design of quantum-AI abstractions, energy-adaptive semiconductor architectures, and neuromorphic computing pathways for edge intelligence. The core problem addressed is the growing mismatch between the computat…
  crossref Murali Krishna Pasupuleti 2026-04-05T09:56:21Z 置信度 0.70
• Development of an Apparatus of Imaginative Information Representation for Neuromorphic Devices
  crossref N. A. Simonov 2024-11-21T14:25:00Z 置信度 0.70
• Silicon Photonics for Neuromorphic Computing and Artificial Intelligence: Applications and Roadmap
  crossref B. J. Shastri, C. Huang, A. N. Tait, T. Ferreira de Lima 等 2022-06-16T15:37:43Z 置信度 0.70
• Hardware implementation of SNN-based neuromorphic computing architecture for sign language recognition
  crossref Rashi Goyal, Mohita Jaiswal, Kartik Khandelwal, Viren Sharma 等 2026-04-03T18:18:50Z 置信度 0.70
• Using Neuromorphic Hardware for the Scalable Execution of Massively Parallel, Communication-Intensive Algorithms
  crossref Louis Blin, Ahsan Javed Awan, Thomas Heinis 2019-01-10T23:32:31Z 置信度 0.70
• Emerging Artificial Synaptic Devices for Neuromorphic Computing
  Abstract In today's era of big‐data, a new computing paradigm beyond today's von‐Neumann architecture is needed to process these large‐scale datasets efficiently. Inspired by the brain, which is better at complex tasks than even supercomputers with much better…
  crossref Qingzhou Wan, Mohammad T. Sharbati, John R. Erickson, Yanhao Du 等 2019-03-06T04:22:14Z 置信度 0.70
• Gate-Tunable Planar TiO2/Graphene Memristor for Neuromorphic Computing
  crossref I. L. Jityaev, M. S. Kartel, Yu. Yu. Jityaeva, V. A. Smirnov 2026-03-23T18:31:13Z 置信度 0.70
• Revolutionizing neuromorphic computing with memristor-based artificial neurons
  Abstract As traditional von Neumann architectures face limitations in handling the demands of big data and complex computational tasks, neuromorphic computing has emerged as a promising alternative, inspired by the human brain's neural networks. Volatile memri…
  crossref Yanning Chen, Guobin Zhang, Fang Liu, Bo Wu 等 2025-06-13T16:01:23Z 置信度 0.70
• Solving Minimum Spanning Tree Problem in Spiking Neural Networks: Improved Results
  crossref Simon Janssen, Stijn Groenen, Simon Reichert, Johan Kwisthout 2024-12-02T18:37:03Z 置信度 0.70
• Organic neuromorphic electronics for sensory coding and biohybrid systems
  crossref Yoeri van de Burgt 2023-02-01T09:31:42Z 置信度 0.70
• Hydrogen-Induced Topotactic Phase Transformations of Cobaltite Thin Films
  Manipulating physical properties through ion migration in complex oxide thin films is an emerging research direction to achieve tunable materials for advanced applications. While the reduction of complex oxides has been widely reported, few reports exist on th…
  datacite Feng, Mingzhen, Li, Junjie, Zhang, Shenli, Pofelski, Alexandre 等 2024 置信度 0.66
• Hydrogen-Induced Topotactic Phase Transformations of Cobaltite Thin Films
  Manipulating physical properties through ion migration in complex oxide thin films is an emerging research direction to achieve tunable materials for advanced applications. While the reduction of complex oxides has been widely reported, few reports exist on th…
  datacite Feng, Mingzhen, Li, Junjie, Zhang, Shenli, Pofelski, Alexandre 等 2024 置信度 0.66
• Nanoenabled Trainable Systems: From Biointerfaces to Biomimetics
  In the dynamic biological system, cells and tissues adapt to diverse environmental conditions and form memories, an essential aspect of training for survival and evolution. An understanding of the biological training principles will inform the design of biomim…
  datacite Li, Pengju, Kim, Saehyun, Tian, Bozhi 2022 置信度 0.66 Trainable biointerfacesnanomaterialsbiomimeticsliving materialsadaptive systems
• Nanoenabled Trainable Systems: From Biointerfaces to Biomimetics
  In the dynamic biological system, cells and tissues adapt to diverse environmental conditions and form memories, an essential aspect of training for survival and evolution. An understanding of the biological training principles will inform the design of biomim…
  datacite Li, Pengju, Kim, Saehyun, Tian, Bozhi 2022 置信度 0.66 Trainable biointerfacesnanomaterialsbiomimeticsliving materialsadaptive systems
• HiAER-Spike Software-Hardware Reconfigurable Platform for Event-Driven Neuromorphic Computing at Scale
  In this work, we present HiAER-Spike, a modular, reconfigurable, event-driven neuromorphic computing platform designed to execute large spiking neural networks with up to 160 million neurons and 40 billion synapses - roughly twice the neurons of a mouse brain …
  datacite Frank, Gwenevere, Hota, Gopabandhu, Wang, Keli, Deng, Christopher 等 2026 置信度 0.66 Hardware Architecture (cs.AR)Artificial Intelligence (cs.AI)FOS: Computer and information sciencesFOS: Computer and information sciences
• Adaptive-Frequency Resonate-and-Fire Neurons for Spectral Estimation of Streaming Radar Signals
  Frequency Modulated Continuous Wave (FMCW) radar systems traditionally rely on Fourier-based methods, such as the Fast Fourier Transform (FFT), to estimate target range and velocity. While computationally efficient, these approaches require storing and process…
  datacite Chiavazza, Stefano, Yuan, Sen, Geilen, Marc, Fioranelli, Francesco 等 2026 置信度 0.66 Neural and Evolutionary Computing (cs.NE)FOS: Computer and information sciencesFOS: Computer and information sciences
• Non-Parametric Dual-Manifold Mapping via 8-Bit Bounded Transformation Matrices: Challenging FP-centric Hardware Paradigms in Low-Energy AI
  Modern deep learning hardware paradigms rely heavily on computationally expensive floating-point arithmetic (FP32, FP16, and FP8), requiring massive thermal and energetic overheads to maintain gradient-based optimization. This paper introduces a non-parametric…
  datacite Kopp, Lars 2026 置信度 0.66 Hardware Architecture (cs.AR)FOS: Computer and information sciencesFOS: Computer and information sciencesComputer science -- Artificial intelligence -- Deep learning
• Quantum-Driven Neuromorphic Computing for Million-Qubit-Scale Workloads
  We introduce Apollo, a 10000 node p-qubit neuromorphic processor fabricated in 16 nm mixed signal CMOS and operating fully at room temperature with a typical analog core power envelope of about 0.5 W. Its fundamental element, the p-qubit, is a bistable stochas…
  datacite Ivanov, Adams, Rahmeh, Samer, Nascimento, Erick Giovani Sperandio, Herrmann, Daniela 2026 置信度 0.66 Quantum Physics (quant-ph)Hardware Architecture (cs.AR)FOS: Physical sciencesFOS: Physical sciencesFOS: Computer and information sciences
• Elucidating dynamic conductive state changes in amorphous lithium lanthanum titanate for resistive switching devices
  Exploration of novel resistive switching materials attracts attention to achieve neuromorphic computing that can surpass the limit of the current Von-Neumann computing for the time of Internet of Things (IoT). Battery materials priorly used to serve as an elec…
  datacite Shimizu, Ryosuke, Cheng, Diyi, Zhu, Guomin, Han, Bing 等 2023 置信度 0.66 Solid electrolyteResistive SwitchingLi-ion batteryOxygen vacancy
• Elucidating dynamic conductive state changes in amorphous lithium lanthanum titanate for resistive switching devices
  Exploration of novel resistive switching materials attracts attention to achieve neuromorphic computing that can surpass the limit of the current Von-Neumann computing for the time of Internet of Things (IoT). Battery materials priorly used to serve as an elec…
  datacite Shimizu, Ryosuke, Cheng, Diyi, Zhu, Guomin, Han, Bing 等 2023 置信度 0.66 Solid electrolyteResistive SwitchingLi-ion batteryOxygen vacancy
• NeuroSilk - Bio Neuromorphic Humanoid Robotics: Integration of Proton Donor–Acceptor (PrDA) Artificial Spider Silk Hydrogel Fibers for Soft Ionic Signal Transmission, HASEL Artificial Muscles, and Carbon Fiber Endoskeleton toward Embodied AI Systems
  This thesis introduces the NeuroSilk Hybrid Robotics Architecture (NSS), a biomimetic framework for humanoid robots that emulates the human musculoskeletal and nervous systems through the coordinated integration of three principal technologies: neuron-inspired…
  datacite Vatulia, Leona Valeria 2026 置信度 0.66
• NeuroSilk - Bio Neuromorphic Humanoid Robotics: Integration of Proton Donor–Acceptor (PrDA) Artificial Spider Silk Hydrogel Fibers for Soft Ionic Signal Transmission, HASEL Artificial Muscles, and Carbon Fiber Endoskeleton toward Embodied AI Systems
  This thesis introduces the NeuroSilk Hybrid Robotics Architecture (NSS), a biomimetic framework for humanoid robots that emulates the human musculoskeletal and nervous systems through the coordinated integration of three principal technologies: neuron-inspired…
  datacite Vatulia, Leona Valeria 2026 置信度 0.66
• Beyond Transformers: Emerging Neural Architectures, Energy-Efficient AI, and Multimodal Fusion for Next-Generation Artificial Intelligence
  It analyzes the limitations of traditional Transformer models (such as quadratic computational complexity and high energy consumption) and explores promising alternative architectures like State Space Models (SSMs) and Mamba. The paper also investigates techni…
  datacite akazou, ibtissam 2026 置信度 0.66
• Beyond Transformers: Emerging Neural Architectures, Energy-Efficient AI, and Multimodal Fusion for Next-Generation Artificial Intelligence
  It analyzes the limitations of traditional Transformer models (such as quadratic computational complexity and high energy consumption) and explores promising alternative architectures like State Space Models (SSMs) and Mamba. The paper also investigates techni…
  datacite akazou, ibtissam 2026 置信度 0.66
• Device-to-logic variability propagation in RRAM-based logic-in-memory architectures
  Logic-in-memory (LiM) has emerged as a promising paradigm to address the von Neumann bottleneck by integrating data storage and in-situ computation. Resistive random-access memory (RRAM) is a strong candidate for LiM owing to its non-volatility, fast switching…
  datacite Bende, Ankit, Singh, Simranjeet, Kumar Jha, Chandan, Storelli, Daniele 等 2026 置信度 0.66 621.3
• 沙漏_一种基于电荷守恒的存算一体模拟计算架构
  # AbstractThis paper proposes a novel computing architecture that fundamentally bypasses and breaks the bottleneck of the micro-scaling race of Moore's Law, which relies on transistor miniaturization. This architecture is named the **Hourglass Charge-Conservat…
  datacite huang, xiaoyan 2026 置信度 0.66 Computer ArchitectureMaterials ScienceElectrical and Electronic EngineeringFOS: Electrical engineering, electronic engineering, information engineeringArtificial Intelligence
• 沙漏_一种基于电荷守恒的存算一体模拟计算架构
  # AbstractThis paper proposes a novel computing architecture that fundamentally bypasses and breaks the bottleneck of the micro-scaling race of Moore's Law, which relies on transistor miniaturization. This architecture is named the **Hourglass Charge-Conservat…
  datacite huang, xiaoyan 2026 置信度 0.66 Computer ArchitectureMaterials ScienceElectrical and Electronic EngineeringFOS: Electrical engineering, electronic engineering, information engineeringArtificial Intelligence
• Coupled integrated photonic quantum memristors using a single photon source made of a colour center
  Photonic quantum memristors provide a measurement-induced route to nonlinear and history-dependent quantum dynamics. Experimental demonstrations have so far focused on isolated devices or simple cascaded devices configurations. Here, we experimentally realize …
  datacite Baldazzi, Alessio, Ancel, Roy Philip George Konnoth, Guaraldo, Sebastiano, Fattori, Ivan 等 2026 置信度 0.66 Quantum Physics (quant-ph)FOS: Physical sciencesFOS: Physical sciences
• Integrated magnonic neural circuits based on nonlinear wave neurons
  Artificial intelligence is driving intense interest in alternative computing hardware capable of neural information processing beyond conventional charge-based electronics. Among emerging approaches, wave-based computing promises highly parallel and energy-eff…
  datacite Guo, Mengying, Jing, Xudong, Davidkova, Kristýna, Verba, Roman 等 2026 置信度 0.66 Materials Science (cond-mat.mtrl-sci)Applied Physics (physics.app-ph)FOS: Physical sciencesFOS: Physical sciences
• A New Threshold Switching Device With Tunable Negative Differential Resistance Based on ErMnO3 Polymorphs
  Negative differential resistance (NDR) devices have emerged as promising building blocks for neuromorphic computing due to their inherent nonlinear and threshold-dependent electrical behavior. In particular, current-controlled NDR devices can exhibit abrupt sw…
  datacite Wu, Rong, Maudet, Florian, Phan, Thanh Luan, Hamouda, Wassim 等 2026 置信度 0.66 ErMnO3hexagonalnegative differential resistanceorthorhombicpolymorphs
• Adaptive-Frequency Resonate-and-Fire Neurons for Spectral Estimation of Streaming Radar Signals
  This dataset contains the data to reproduce the results presented in the paper: "Adaptive-Frequency Resonate-and-Fire Neurons for Spectral Estimation of Streaming Radar Signals". The work introduces a dynamical system of adaptive-frequency neuron, specifically…
  datacite Chiavazza, Stefano, Yuan, Sen, Geilen, Marc, Fioranelli, Francesco 等 2026 置信度 0.66 neuromorphic computingFMCW Radar
• Adaptive-Frequency Resonate-and-Fire Neurons for Spectral Estimation of Streaming Radar Signals
  This dataset contains the data to reproduce the results presented in the paper: "Adaptive-Frequency Resonate-and-Fire Neurons for Spectral Estimation of Streaming Radar Signals". The work introduces a dynamical system of adaptive-frequency neuron, specifically…
  datacite Chiavazza, Stefano, Yuan, Sen, Geilen, Marc, Fioranelli, Francesco 等 2026 置信度 0.66 neuromorphic computingFMCW Radar
• Mimicking Neural Habituation Behavior with Pristine Leaf-based Memristors
  Neuromorphic computing systems allow electronics to mimic the behavior of biological neurons and hold potential for high-efficiency computation needed for artificial intelligence. One class of electronic units capable of mimicking neural behavior is resistive …
  datacite Savage, Andrew, Wilder, Samantha, Adhikari, Ramesh 2026 置信度 0.66 Physical sciencesFOS: Physical sciences
• Threshold Dynamics of Silver Filament Formation and Rupture in Ag/SiO2/Au Memristors
  Memristive devices with tunable volatility represent a promising platform for neuromorphic computing and adaptive electronics, enabling temporal information processing and gradual memory consolidation. Understanding the threshold dynamics governing conductive …
  datacite Ranade, Varun, Veldhoen, William, Gibbins, Felix, Shradha, Sajal 等 2026 置信度 0.66 MemristorsResistive SwitchingVolatile MemoriesMemory devicesNeuromorphic computing
• Towards faster machine olfaction: advances in high-speed sensing and processing
  This thesis investigates the principles and methods for achieving high temporal resolution in odour sampling and processing for machine perception. Initially, a comprehensive review of fast olfaction mechanisms in insects and mammals is provided, highlighting …
  datacite Dennler, Nik 2024 置信度 0.66
• Neuromorphic Reinforcement Learning for Quadruped Locomotion Control on Uneven Terrain
  Reinforcement learning (RL) has enabled robust quadruped locomotion over complex terrain, but most learned controllers are trained offline with backpropagation in massively parallel simulation and deployed as fixed policies, limiting adaptation to terrain vari…
  datacite Han, Zhuangyu, Sengupta, Abhronil 2026 置信度 0.66 Neural and Evolutionary Computing (cs.NE)Robotics (cs.RO)FOS: Computer and information sciencesFOS: Computer and information sciences
• Electrothermally Modulated Nanophotonic Waveguide-integrated Ring Resonator
  Reconfigurable integrated chips of photonic components and networks are envisaged to play a key role in realizing highly efficient integrated photonic information processing. Electrothermally modulated optical effect (ETMOE) is a powerful thermo-optic tuning m…
  datacite Gupta, Sujal, Xavier, Jolly 2025 置信度 0.66 Optics (physics.optics)Applied Physics (physics.app-ph)FOS: Physical sciencesFOS: Physical sciences
• Spiking Neural Network inference on FPGAs with hls4ml
  Spiking Neural Networks (SNNs) provide a naturally temporal machine-learning framework. Their neurons maintain an internal state and propagate information through discrete spikes, enabling low-latency temporal inference. Although SNNs are often associated with…
  datacite Dillon, Barry M. 2026 置信度 0.66 Neural and Evolutionary Computing (cs.NE)Machine Learning (cs.LG)FOS: Computer and information sciencesFOS: Computer and information sciences
• Hardware architectures for event-driven feature extraction algorithms
  Over the last decade, Neuromorphic Engineering (NE) has evolved into a prominent scientific discipline, advancing biologically inspired sensors, algorithms, hardware architectures, and processing techniques that emulate key operational principles of the human …
  datacite Jose, Philip 2026 置信度 0.66
• ExSpike: A General Full-Event Neuromorphic Architecture for Exploiting Irregular Sparsity with Event Compression
  Spiking neural networks (SNNs) promise energy-efficient computing due to their sparse spatio-temporal activity. However, effectively translating such irregular sparsity into practical performance and energy gains remains challenging, as full-event computing ar…
  datacite Chen, Yuehai, Merchant, Farhad 2026 置信度 0.66
• ExSpike: A General Full-Event Neuromorphic Architecture for Exploiting Irregular Sparsity with Event Compression
  Spiking neural networks (SNNs) promise energy-efficient computing due to their sparse spatio-temporal activity. However, effectively translating such irregular sparsity into practical performance and energy gains remains challenging, as full-event computing ar…
  datacite Chen, Yuehai, Merchant, Farhad 2026 置信度 0.66
• <strong>Electrically controlled tuning the nonlinearity and asymmetry of synaptic behaviors in a magnetoelectrically coupled memristor for high-performance neuromorphic computing</strong>
  High-performance artificial synaptic devices capable of emulating biological synaptic functions are crucial for developing energy-efficient neuromorphic computing systems. Memristors, whose conductance can be modulated to mimic synaptic plasticity, offer a pro…
  datacite Song, Guangxiao, Zhou, Hao-Miao, Yu, Guoliang, Zhu, Haibin 等 2026 置信度 0.66 Physical sciencesFOS: Physical sciences
• Convolutional Sparse Coding via the Locally Competitive Algorithm on Loihi 2
  Sparse coding provides a principled framework for signal representation by expressing an input as a linear combination of only a small number of basis functions. The Locally Competitive Algorithm (LCA) is particularly attractive in the context of neuromorphic …
  datacite Kasenbacher, Geoffrey, Ruepp, Daniel, Ecke, Gerrit A. 2026 置信度 0.66 Machine Learning (cs.LG)FOS: Computer and information sciencesFOS: Computer and information sciences
• Unifying von-Neumann HPC and Neuromorphic Acceleration via the EBRAINS Research Infrastructure: A Framework for High-Performance Workflows
  Modern scientific workflows increasingly span diverse computing architectures, yet executing a single computational model across disparate systems often forces researchers to maintain fragmented, site-specific pipelines. In this paper, we address this challeng…
  datacite Singh, Krishna Kant, Linssen, Charl, Müller, Eric, Mathioulaki, Eleni 等 2026 置信度 0.66 Distributed, Parallel, and Cluster Computing (cs.DC)FOS: Computer and information sciencesFOS: Computer and information sciences
• ARIA: A Zero-Hallucination Neuro-Symbolic Architecture for Persistent Memory, Sparse Graph Reasoning, and Autonomous Self-Evolution
  ARIA is a deterministic neuro-symbolic cognitive architecture designed to integrate persistent memory, autonomous goal formation, causal reasoning, self-modifying cognitive structures, and large-scale knowledge representation. Unlike conventional transformer-b…
  datacite Counselor Service Holding LTD, Vettorato, Nicola 2026 置信度 0.66 Artificial General Intelligence AGI Neuro-Symbolic AI Cognitive Architecture Persistent Memory Autonomous Goal Formation Knowledge Graphs AtomSpace Causal Reasoning Artificial Intelligence Machine Learning Neuromorphic Computing
• ARIA: A Zero-Hallucination Neuro-Symbolic Architecture for Persistent Memory, Sparse Graph Reasoning, and Autonomous Self-Evolution
  ARIA is a deterministic neuro-symbolic cognitive architecture designed to integrate persistent memory, autonomous goal formation, causal reasoning, self-modifying cognitive structures, and large-scale knowledge representation. Unlike conventional transformer-b…
  datacite Counselor Service Holding LTD, Vettorato, Nicola 2026 置信度 0.66 Artificial General Intelligence AGI Neuro-Symbolic AI Cognitive Architecture Persistent Memory Autonomous Goal Formation Knowledge Graphs AtomSpace Causal Reasoning Artificial Intelligence Machine Learning Neuromorphic Computing
• Jigyāsā: A Self-Taught Thinking Model Trained on Autonomously Generated Knowledge via SNN-Modulated Curiosity Loops
  Jigyāsā is a language model trained entirely on knowledge it generated itself — starting from a single seed question about entropy and time, the system autonomously explored 500 knowledge nodes across nine domains, including physics, consciousness, linguistics…
  datacite Swaminathan, Venkatesh 2026 置信度 0.66 neuromorphic computingspiking neural networkscontinual learningnociceptive metaplasticityBhaya Quiescence Law
• Wave_Unified_Spectral_Technologies.docx
  This paper provides a concise conceptual survey of the Spectral Computing paradigm and its natural extensions into the physical sciences. At its centre stands the spectral computer — an architecture in which information is encoded, routed and processed as stru…
  datacite Desmond, Timothy 2026 置信度 0.66 Science, Waveform, Quantum,Physics, Holography, Laser, X-Ray, Unified, Information,Medical,Advance, Spectral Computing, Spectral Instruction Set Architecture, S-ISA, Phase-Based Computation, Coherent Computing, Post-Binary Architecture, Neuromorphic Computing
• Wave_Unified_Spectral_Technologies.docx
  This paper provides a concise conceptual survey of the Spectral Computing paradigm and its natural extensions into the physical sciences. At its centre stands the spectral computer — an architecture in which information is encoded, routed and processed as stru…
  datacite Desmond, Timothy 2026 置信度 0.66 Science, Waveform, Quantum,Physics, Holography, Laser, X-Ray, Unified, Information,Medical,Advance, Spectral Computing, Spectral Instruction Set Architecture, S-ISA, Phase-Based Computation, Coherent Computing, Post-Binary Architecture, Neuromorphic Computing
• Spectral_Computing_Product_Pitch_v2.docx
  Spectral Computing is a new computing architecture built on a fundamentally different mathematical substrate from the binary logic that has powered electronics since the 1940s. It does not require exotic materials, new physics, or untested engineering. Approxi…
  datacite Desmond, Timothy 2026 置信度 0.66 Computing, quantum, classical, research Spectral Computing, Spectral Instruction Set Architecture, S-ISA, Phase-Based Computation, Coherent Computing, Post-Binary Architecture, Neuromorphic Computing
• Spectral_Computing_Product_Pitch_v2.docx
  Spectral Computing is a new computing architecture built on a fundamentally different mathematical substrate from the binary logic that has powered electronics since the 1940s. It does not require exotic materials, new physics, or untested engineering. Approxi…
  datacite Desmond, Timothy 2026 置信度 0.66 Computing, quantum, classical, research Spectral Computing, Spectral Instruction Set Architecture, S-ISA, Phase-Based Computation, Coherent Computing, Post-Binary Architecture, Neuromorphic Computing
• Variational-Spectral-GKSL Closed Dynamical Theory of a Quantum-Information Field
  Version:v0.1-formalization Author:Vitaliy Bazarov(VIT-BAZ) ORCID:0009-0007-9967-5807 Status:Preprint / theoretical specification / formal research archive Description:This archive contains the current formalization package for the UAU–ESVG–SAAU–Σ* framework: a…
  datacite Bazarov, Vitaly 2026 置信度 0.66
• Variational-Spectral-GKSL Closed Dynamical Theory of a Quantum-Information Field
  Version:v0.1-formalization Author:Vitaliy Bazarov(VIT-BAZ) ORCID:0009-0007-9967-5807 Status:Preprint / theoretical specification / formal research archive Description:This archive contains the current formalization package for the UAU–ESVG–SAAU–Σ* framework: a…
  datacite Bazarov, Vitaly 2026 置信度 0.66
• Gate controlled EDL-based capacitor-diodes (G-CAPode) for switchable signal filters with logic gate functionality
  This work explores a novel application of the G-CAPode - a previously developed, 3D-printed gate-controlled electrochemical capacitor-diode - by demonstrating its ability to perform logic operations in ionic circuits. The G-CAPode integrates diode-like rectifi…
  datacite Gellrich, Christin, Galek, Przemysław, Shupletsov, Leonid, Grothe, Julia 等 2025 置信度 0.66 3D printingG-CAPodeIonic transistor, Ionic diodeSignal filtering, IontronicsVaractor
• SC-NeuroCore: Universal Stochastic Computing Framework for Neuromorphic Hardware
  A high-performance neuromorphic computing framework combining stochastic computing with spiking neural networks. 122 neuron models (1943-2026), Rust SIMD engine (111 models, 41.3 Gbit/s AVX-512, PyO3 bindings), bit-true Verilog RTL co-simulation, FPGA synthesi…
  datacite Sotek, Miroslav 2026 置信度 0.66 neuromorphicstochastic computingspiking neural networksFPGAhyper-dimensional computing
• SC-NeuroCore: Universal Stochastic Computing Framework for Neuromorphic Hardware
  A high-performance neuromorphic computing framework combining stochastic computing with spiking neural networks. 122 neuron models (1943-2026), Rust SIMD engine (111 models, 41.3 Gbit/s AVX-512, PyO3 bindings), bit-true Verilog RTL co-simulation, FPGA synthesi…
  datacite Sotek, Miroslav 2026 置信度 0.66 neuromorphicstochastic computingspiking neural networksFPGAhyper-dimensional computing
• SC-NeuroCore: Universal Stochastic Computing Framework for Neuromorphic Hardware
  A high-performance neuromorphic computing framework combining stochastic computing with spiking neural networks. 122 neuron models (1943-2026), Rust SIMD engine (111 models, 41.3 Gbit/s AVX-512, PyO3 bindings), bit-true Verilog RTL co-simulation, FPGA synthesi…
  datacite Sotek, Miroslav 2026 置信度 0.66 neuromorphicstochastic computingspiking neural networksFPGAhyper-dimensional computing
• SC-NeuroCore: Universal Stochastic Computing Framework for Neuromorphic Hardware
  A high-performance neuromorphic computing framework combining stochastic computing with spiking neural networks. 122 neuron models (1943-2026), Rust SIMD engine (111 models, 41.3 Gbit/s AVX-512, PyO3 bindings), bit-true Verilog RTL co-simulation, FPGA synthesi…
  datacite Sotek, Miroslav 2026 置信度 0.66 neuromorphicstochastic computingspiking neural networksFPGAhyper-dimensional computing
• SC-NeuroCore: Universal Stochastic Computing Framework for Neuromorphic Hardware
  A high-performance neuromorphic computing framework combining stochastic computing with spiking neural networks. 122 neuron models (1943-2026), Rust SIMD engine (111 models, 41.3 Gbit/s AVX-512, PyO3 bindings), bit-true Verilog RTL co-simulation, FPGA synthesi…
  datacite Sotek, Miroslav 2026 置信度 0.66 neuromorphicstochastic computingspiking neural networksFPGAhyper-dimensional computing
• SC-NeuroCore: Universal Stochastic Computing Framework for Neuromorphic Hardware
  A high-performance neuromorphic computing framework combining stochastic computing with spiking neural networks. 122 neuron models (1943-2026), Rust SIMD engine (111 models, 41.3 Gbit/s AVX-512, PyO3 bindings), bit-true Verilog RTL co-simulation, FPGA synthesi…
  datacite Sotek, Miroslav 2026 置信度 0.66 neuromorphicstochastic computingspiking neural networksFPGAhyper-dimensional computing
• SC-NeuroCore: Universal Stochastic Computing Framework for Neuromorphic Hardware
  A high-performance neuromorphic computing framework combining stochastic computing with spiking neural networks. 122 neuron models (1943-2026), Rust SIMD engine (111 models, 41.3 Gbit/s AVX-512, PyO3 bindings), bit-true Verilog RTL co-simulation, FPGA synthesi…
  datacite Sotek, Miroslav 2026 置信度 0.66 neuromorphicstochastic computingspiking neural networksFPGAhyper-dimensional computing
• SC-NeuroCore: Universal Stochastic Computing Framework for Neuromorphic Hardware
  A high-performance neuromorphic computing framework combining stochastic computing with spiking neural networks. 122 neuron models (1943-2026), Rust SIMD engine (111 models, 41.3 Gbit/s AVX-512, PyO3 bindings), bit-true Verilog RTL co-simulation, FPGA synthesi…
  datacite Sotek, Miroslav 2026 置信度 0.66 neuromorphicstochastic computingspiking neural networksFPGAhyper-dimensional computing
• SC-NeuroCore: Universal Stochastic Computing Framework for Neuromorphic Hardware
  A high-performance neuromorphic computing framework combining stochastic computing with spiking neural networks. 122 neuron models (1943-2026), Rust SIMD engine (111 models, 41.3 Gbit/s AVX-512, PyO3 bindings), bit-true Verilog RTL co-simulation, FPGA synthesi…
  datacite Sotek, Miroslav 2026 置信度 0.66 neuromorphicstochastic computingspiking neural networksFPGAhyper-dimensional computing
• SC-NeuroCore: Universal Stochastic Computing Framework for Neuromorphic Hardware
  A high-performance neuromorphic computing framework combining stochastic computing with spiking neural networks. 122 neuron models (1943-2026), Rust SIMD engine (111 models, 41.3 Gbit/s AVX-512, PyO3 bindings), bit-true Verilog RTL co-simulation, FPGA synthesi…
  datacite Sotek, Miroslav 2026 置信度 0.66 neuromorphicstochastic computingspiking neural networksFPGAhyper-dimensional computing
• The role of charge carrier diffusion in halide perovskite luminophores with memory for optical computing
  The optical elements that can combine memory and signal modulation have become a topic of interest in the field of neuromorphic computing systems. In particular, the optical analogue of a memristor called memlumor exhibits promising features in which the chang…
  datacite Ekgardt, Alexey, Sapozhnikova, Elizaveta, Verkhogliadov, Grigorii, Pushkarev, Anatoly 2026 置信度 0.66 neuromorphic systemsmemlumorsmetal halide perovskitesphotoluminescencecharge carrier diffusion
• An Exact-Fixed-Point Reference Benchmark and Validation Methodology for Simulators of Signed k-State Voter Dynamics on Networks
  Open technical disclosure · v1.0 · 5 June 2026. This document specifies, in fully reproducible and implementation-ready detail, a tiered reference benchmark and an associated validation methodology for simulators of signed k-state voter dynamics on networks, a…
  datacite Melegh, Janos Gabor 2026 置信度 0.66
• An Exact-Fixed-Point Reference Benchmark and Validation Methodology for Simulators of Signed k-State Voter Dynamics on Networks
  Open technical disclosure · v1.0 · 5 June 2026. This document specifies, in fully reproducible and implementation-ready detail, a tiered reference benchmark and an associated validation methodology for simulators of signed k-state voter dynamics on networks, a…
  datacite Melegh, Janos Gabor 2026 置信度 0.66
• Nonlinear Inference Capacity of Fiber-Optical Extreme Learning Machines
  The intrinsic complexity of nonlinear optical phenomena offers a fundamentally new resource to analog brain-inspired computing, with the potential to address the pressing energy requirements of artificial intelligence. We introduce and investigate the concept …
  datacite Saeed, Sobhi, Müftüoglu, Mehmet, Cheeran, Glitta R., Bocklitz, Thomas 等 2025 置信度 0.66 Optics (physics.optics)FOS: Physical sciencesFOS: Physical sciences
• Scalability in Neural Control of Musculoskeletal Robots
  Anthropomimetic robots are robots that sense, behave, interact and feel like humans. By this definition, anthropomimetic robots require human-like physical hardware and actuation, but also brain-like control and sensing. The most self-evident realization to me…
  datacite Richter, Christoph, Jentzsch, Sören, Hostettler, Rafael, Garrido, Jesús A. 等 2016 置信度 0.66 Robotics (cs.RO)Distributed, Parallel, and Cluster Computing (cs.DC)Neural and Evolutionary Computing (cs.NE)Systems and Control (eess.SY)FOS: Computer and information sciences
• Electrolyte Bonding Engineering for Highly Uniform GeTe-based CBRAM and Parallel Hebbian Learning in Selector-free Hopfield Networks
  Hopfield networks offer a hardware-friendly framework for energy-efficient associative memory, yet their practical realization in memristor crossbar arrays is critically hindered by device-to-device (D2D) variability, which prevents reliable parallel programmi…
  datacite Bang, Jiin, Hwang, Jingyeong, Kang, Unhyeon, Oh, Seungmin 等 2026 置信度 0.66 Applied Physics (physics.app-ph)Disordered Systems and Neural Networks (cond-mat.dis-nn)FOS: Physical sciencesFOS: Physical sciences
• The Aetherium Unified Framework: Quantum Dark Fluid, Physical AGI, and Mathematical Validations (Complete Archive)
  Cet ensemble documentaire constitue l'archive intégrale du cadre unifié Aetherium. Ce modèle propose une résolution de la conjecture du "Dark Fluid" (2005) en unifiant la cosmologie, la dynamique des fluides quantiques et l'intelligence artificielle physique. …
  datacite MORIN, Richard 2026 置信度 0.66 agidark fluidquantum fluidscollatz conjectureNavier-Stokes Regularization
• The Aetherium Unified Framework: Quantum Dark Fluid, Physical AGI, and Mathematical Validations (Complete Archive)
  Cet ensemble documentaire constitue l'archive intégrale du cadre unifié Aetherium. Ce modèle propose une résolution de la conjecture du "Dark Fluid" (2005) en unifiant la cosmologie, la dynamique des fluides quantiques et l'intelligence artificielle physique. …
  datacite MORIN, Richard 2026 置信度 0.66 agidark fluidquantum fluidscollatz conjectureNavier-Stokes Regularization
• Topology-Aware Packet Classification and Adaptive Local-Core Selection for SpiNNaker: Design and Reproducible Virtual-Mode Benchmarking
  This paper develops a proposal for topology-aware packet classification and adaptive local-core selection in SpiNNaker. A dispatch-class mechanism refines standard routing table entries by restricting inter-chip forwarding directions and reducing local process…
  datacite Christopher Lee Burgess 2026 置信度 0.66 Neuromorphic ComputingSpiNNaker
• Topology-Aware Packet Classification and Adaptive Local-Core Selection for SpiNNaker: Design and Reproducible Virtual-Mode Benchmarking
  This paper develops a proposal for topology-aware packet classification and adaptive local-core selection in SpiNNaker. A dispatch-class mechanism refines standard routing table entries by restricting inter-chip forwarding directions and reducing local process…
  datacite Christopher Lee Burgess 2026 置信度 0.66 Neuromorphic ComputingSpiNNaker
• Higher-order exceptional points in a multimode continuum optoacoustic system
  Exceptional points appear in non-Hermitian systems as degeneracies, where not only eigenvalues but also eigenvectors coalesce. They are of great theoretical and experimental interest due to their exotic topological properties and enhanced sensitivity to pertur…
  datacite Montag, Anton, Gohsrich, Julius T., Levoy, Quentin, Stiller, Birgit 等 2026 置信度 0.66 Optics (physics.optics)FOS: Physical sciencesFOS: Physical sciences
• Constructive community race: full-density spiking neural network model drives neuromorphic computing
  Neuromorphic computing and engineering 6(1), 012001 - (2026). doi:10.1088/2634-4386/ae379a
  datacite Senk, Johanna, Kurth, Anno C, Furber, Steve, Gemmeke, Tobias 等 2026 置信度 0.66 621.3