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• Tibetan Few-Shot Learning Model Based on Matching Networks
  crossref Ziyue Zhang, Gaojie Xiong, Yongbin Yu, Xiangxiang Wang 等 2024-03-19T18:09:52Z 置信度 0.70
• Hybrid Neuromorphic Edge Computing and Quantum Cloud Optimization for Martian Swarm Robot Survival and Map Recovery
  Martian dust storms cut off communication and break standard robot navigation. We built a hybrid system that keeps robot swarms alive during these blackouts and recovers their data quickly. Our rovers use Spiking Neural Networks (SNNs) on their own edge proces…
  crossref Chandan Sheikder, Weimin Zhang, Xiaopeng Chen, Shicheng Fan 等 2026-06-30T08:26:15Z 置信度 0.70
• Self-rectifying Ag2O1-δ-based synaptic crossbar array for neuromorphic computing applications
  crossref Bishal Kumar Keshari, Chetan Kodand Reddy Madadi, Sanghamitra DebRoy, Akshay Salimath 等 2026-05-02T18:36:08Z 置信度 0.70
• A Review on Gallium Oxide (Ga₂O₃) Phototransistors for Neuromorphic Computing
  crossref Monisha Biswas 2026-01-02T03:17:51Z 置信度 0.70
• Occurrence of robust memristive behavior for low-power transient resistive switching and photo-responsive neuromorphic computing in low-dimensional perovskite
  crossref Peiying Li, Xiaojie Li 2023-11-25T07:15:00Z 置信度 0.70
• Neuromorphic computing for content-based image retrieval
  Neuromorphic computing mimics the neural activity of the brain through emulating spiking neural networks. In numerous machine learning tasks, neuromorphic chips are expected to provide superior solutions in terms of cost and power efficiency. Here, we explore …
  crossref Te-Yuan Liu, Ata Mahjoubfar, Daniel Prusinski, Luis Stevens 2022-04-06T17:42:41Z 置信度 0.70
• Quantizing Small-Scale State-Space Models for Edge AI
  crossref Leo Zhao, Tristan Torchet, Melika Payvand, Laura Kriener 等 2026-01-21T21:07:17Z 置信度 0.70
• Modeling a Floating-Gate Memristive Device for Computer Aided Design of Neuromorphic Computing
  crossref L. Danial, V. Gupta, E. Pikhay, Y. Roizin 等 2020-06-15T23:28:37Z 置信度 0.70
• Advanced iontronic spiking modes with multiscale diffusive dynamics in a fluidic circuit
  Abstract Fluidic iontronics is emerging as a distinctive platform for implementing neuromorphic circuits, characterised by its reliance on the same aqueous medium and ionic signal carriers as the brain. Drawing upon recent theoretical advancements in both iont…
  crossref T M Kamsma, E A Rossing, C Spitoni, R van Roij 2024-04-30T08:41:23Z 置信度 0.70
• NANOSCALE STRANTRONIC MAGNETOELETRIC CELL FOR NEUROMORPHIC SYSTEMS
  Results are reported on numerical-analytic modelling of functional characteristics of a nanoscale neuron-like magnetoelectric cell. Nonlinear transfer activation functions of a composite cell and conditions of their formation in spin-reorientation processes in…
  crossref L. M. Krutyansky, V. L. Preobrazhensky 2026-03-13T10:38:22Z 置信度 0.70
• Bio-inspired ultra lower-power neuromorphic computing engine for embedded systems
  crossref Beiye Liu, Miao Hu, Hai Li, Yiran Chen 等 2013-11-21T15:52:07Z 置信度 0.70
• Integrating molecular photoswitch memory with nanoscale optoelectronics for neuromorphic computing
  Abstract Photonic solutions are potentially highly competitive for energy-efficient neuromorphic computing. However, a combination of specialized nanostructures is needed to implement all neuro-biological functionality. Here, we show that donor-acceptor Stenho…
  crossref David Alcer, Nelia Zaiats, Thomas K. Jensen, Abbey M. Philip 等 2025-01-13T22:59:28Z 置信度 0.70
• Neuromorphic Computing Systems: From CMOS To Emerging Nonvolatile Memory
  crossref Chaofei Yang, Ximing Qiao, Yiran Chen 2019-07-31T22:07:26Z 置信度 0.70
• Review for "Improved Neuromorphic Functionality in Organic Electrochemical Transistors Using Crosslinked-Polyvinyl alcohol for Fast Ion Transport and its Application to Pavlovian Transistors"
  crossref 2025-07-11T21:06:55Z 置信度 0.70
• CRISP: A JIT Compiled Neuromorphic Simulator
  crossref Jackson Mowry, James Plank 2026-07-16T05:57:39Z 置信度 0.70
• Fault Mitigation for SNN Classification of Neuromorphic Event Streams with Radiation-Induced Noise
  crossref Joshua Poravanthattil, Daniel C. Stumpp, Seth Roffe, Alan D. George 2025-07-14T17:40:12Z 置信度 0.70
• Introduction: Neuromorphic Materials
  crossref A. Alec Talin, Bilge Yildiz 2025-05-28T07:06:10Z 置信度 0.70
• Inversion symmetry-broken CuBO ₂ delafossite through anionic site doping for improved piezoelectric composites with PVDF and its application in nanogenerators and optoelectronic neuromorphic computing
  Self-charging photodetectors drive the development of energy-autonomous electronics for efficient use in memory, portable devices, neuromorphic computing, and optoelectronic systems.
  crossref Suvankar Poddar, Pulok Das, Souvik Bhattacharjee, Kalyan Kumar Chattopadhyay 2025-07-10T19:01:14Z 置信度 0.70
• Review for "Inverted resistive switching mechanism in polycrystalline PBTTT-C14 polymer devices based on contact geometry and molecular packing for neuromorphic memory"
  crossref 2025-05-30T17:05:17Z 置信度 0.70
• Engineering ZrO2/WS2 nanocomposite for multilevel memory and high-performance neuromorphic computing
  crossref Faisal Ghafoor, Honggyun Kim, Bilal Ghafoor, Muhammad Asif Hamayun 等 2025-10-18T17:06:07Z 置信度 0.70
• Hybrid Filamentary Switching in Fe2O3—Incorporated TiO2 Memristors for Memory and Neuromorphic Computing Application
  Memristive devices have emerged as promising candidates for next-generation non-volatile memory and neuromorphic computing systems owing to their simple device architecture, low power consumption, and capability for analog conductance modulation. In this work,…
  crossref Dwipak Prasad Sahu 2026-08-12T09:11:36Z 置信度 0.70
• Halide-Perovskite-Based Memristor Devices and Their Application in Neuromorphic Computing
  crossref Soumitra Satapathi, Kanishka Raj, Yukta, Mohammad Adil Afroz 2022-07-28T18:31:25Z 置信度 0.70
• Adversarial Robustness Analysis of Spiking Neural Networks for Neuromorphic Computing Systems
  crossref Venkateshmurthy B S, Sajja Suneel, Neha Ghildiyal, R. Naveenkumar 等 2026-07-07T19:42:48Z 置信度 0.70
• Improved Two-Step Finite-Time Stabilization Control for Time-Delay Systems
  crossref Yue Chen, Song Zhu 2024-03-19T18:09:52Z 置信度 0.70
• Formalizing Neuromorphic Control Systems A General Proposal and A Rhythmic Case Study
  crossref Taisia Medvedeva, Fernando Castaños, Alessio Franci 2026-01-12T18:19:56Z 置信度 0.70
• Harnessing Nonidealities in Analog In‐Memory Computing Circuits: A Physical Modeling Approach for Neuromorphic Systems
  Large‐scale deep learning models are increasingly constrained by their immense energy consumption, which limits their scalability and applicability for edge intelligence. In‐memory computing (IMC) offers a promising solution by addressing the von Neumann bottl…
  crossref Yusuke Sakemi, Yuji Okamoto, Takashi Morie, Sou Nobukawa 等 2025-08-18T19:04:54Z 置信度 0.70
• Review for "Improved Neuromorphic Functionality in Organic Electrochemical Transistors Using Crosslinked-Polyvinyl alcohol for Fast Ion Transport and its Application to Pavlovian Transistors"
  crossref 2025-07-11T21:06:55Z 置信度 0.70
• Realizing linear synaptic plasticity in electric double layer-gated transistors for improved predictive accuracy and efficiency in neuromorphic computing
  Abstract Neuromorphic computing offers a low-power, parallel alternative to traditional von Neumann architectures by addressing the sequential data processing bottlenecks. Electric double layer-gated transistors (EDLTs) resemble biological synapses with their …
  crossref Nithil Harris Manimaran, Cori Lee Mathew Sutton, Jake W Streamer, Cory Merkel 等 2024-12-13T22:53:12Z 置信度 0.70
• Materials Discovery for Energy-Efficient Neuromorphic Computing: A Co-Design Approach.
  crossref Christian Mailhiot 2022-11-30T03:18:50Z 置信度 0.70
• Node perturbation can effectively train multi-layer neural networks
  Abstract Backpropagation (BP) remains the dominant and most successful method for training parameters of deep neural network models. However, BP relies on two computationally distinct phases, does not provide a satisfactory explanation of biological learning, …
  crossref Sander Dalm, Marcel A J van Gerven, Nasir Ahmad 2026-08-19T22:50:46Z 置信度 0.70
• Synthetic neuromorphic computing in living cells
  Abstract Computational properties of neuronal networks have been applied to computing systems using simplified models comprising repeated connected nodes, e.g., perceptrons, with decision-making capabilities and flexible weighted links. Analogously to their re…
  crossref Luna Rizik, Loai Danial, Mouna Habib, Ron Weiss 等 2022-09-24T01:02:52Z 置信度 0.70
• Difficulties and approaches in enabling learning-in-memory using crossbar arrays of memristors
  Abstract Crossbar arrays of memristors are promising to accelerate the deep learning algorithm as a non-von-Neumann architecture, where the computation happens at the location of the memory. The computations are parallelly conducted employing the basic physica…
  crossref Wei Wang, Yang Li, Ming Wang 2024-07-24T19:07:11Z 置信度 0.70
• Accelerated Analog Neuromorphic Computing
  crossref Johannes Schemmel, Sebastian Billaudelle, Philipp Dauer, Johannes Weis 2022-03-25T10:05:10Z 置信度 0.70
• Simulation-based effective comparative analysis of neuron circuits for neuromorphic computation systems
  crossref Deepthi M.S., Shashidhara H.R., Jayaramu Raghu, Rudraswamy S.B. 2024-10-28T11:30:09Z 置信度 0.70
• Event-based seizure detection in human iEEG with neuromorphic hardware
  Abstract Background Epilepsy is a neurological disorder that affects approximately 1% of the global population. The current method for seizure monitoring, seizure diaries, is often inaccurate, making precise monitoring challenging. A monotonic descending “chir…
  preprints Flavia Davidhi, Filippo Costa, Debora Ledergerber, Giacomo Indiveri 等 2025 置信度 0.74
• PointLCA-Net: Using Point Clouds for Energy Efficient Sparse Spatio-Temporal Signal Recognition in Neuromorphic Systems
  crossref Sanaz Mahmoodi Takaghaj 2025-11-14T18:46:15Z 置信度 0.70
• CMOS implementation of field programmable spiking neural network for hardware reservoir computing
  Abstract The increasing complexity and energy demands of large-scale neural networks, such as deep neural networks and large language models, challenge their practical deployment in edge applications due to high power consumption, area requirements, and privac…
  crossref Ckristian Duran, Nanako Kimura, Zolboo Byambadorj, Tetsuya Iizuka 2026-04-29T22:52:45Z 置信度 0.70
• Implementation of STDP based learning rule in neuromorphic CMOS circuits
  crossref P. J. Srinidhi, T. R. Yashaswini, N. Uttunga, Syed Aslam Ali 等 2018-01-17T22:23:56Z 置信度 0.70
• Verdigraph NeuroGenesis: A Software Framework for Self-Evolving AI-Agent Cognitive Substrates
  Verdigraph NeuroGenesis v0.2.0 — software framework for self-evolving AI-agent cognitive substrates with mechanically verified operational invariants. Verdigraph is built on a simple observation: AI agents waste energy at industrial scale, and energy is carbon…
  datacite Hart, Justin 2026 置信度 0.66 artificial intelligenceAI agentsagent frameworksModel Context ProtocolMCP
• Phase-Topology Classification of Memristor Hysteresis Loops via Self-Crossings
  Memristive devices have revolutionized non-volatile memory and neuromorphic computing, yet the geometry of their hysteresis loops -- in particular, the occurrence and robustness of multiple self-crossings -- remains poorly understood. Here we introduce a topol…
  datacite Lipan, Ovidiu-Zeno, Neuhaus, Eric, Silva, Rafael Schio Wengenroth, Pradhan, Soumen 等 2026 置信度 0.66 Other Condensed Matter (cond-mat.other)FOS: Physical sciencesFOS: Physical sciences
• SymBrain: A Biomimetic Neuro-Symbolic Architecture for Small Language Models
  SymBrain: A 3-hemisphere neuro-symbolic architecture using Qwen2.5-Math-7B and Ministral-8B coordinated by an executive Prefrontal Cortex bridge. Achieves SOTA reasoning for its class (GSM8K: 88.50%, MATH: 58.41%, Physics: 56.09%) with 21.9% power savings.
  datacite Callens, Xavier 2026 置信度 0.66 Neuromorphic ComputingNeuro-SymbolicSmall Language ModelsGreen AIBiomimetic Co-Inference
• SymBrain: A Biomimetic Neuro-Symbolic Architecture for Small Language Models
  SymBrain: A 3-hemisphere neuro-symbolic architecture using Qwen2.5-Math-7B and Ministral-8B coordinated by an executive Prefrontal Cortex bridge. Achieves SOTA reasoning for its class (GSM8K: 88.50%, MATH: 58.41%, Physics: 56.09%) with 21.9% power savings.
  datacite Callens, Xavier 2026 置信度 0.66 Neuromorphic ComputingNeuro-SymbolicSmall Language ModelsGreen AIBiomimetic Co-Inference
• Biomimetic Co-Inference Learning: Bypassing Backpropagation via Telemetry-Guided Direct Feedback Alignment
  WARS-CI-DFA: A high-performance, energy-efficient biomimetic learning loop on GCP Cloud TPU v5e bypassing backward propagation and saving 40% board power, formally verified in Lean 4.
  datacite Callens, Xavier 2026 置信度 0.66 Neuromorphic ComputingDirect Feedback AlignmentGCP Cloud TPU v5eLean 4Formal Verification
• Biomimetic Co-Inference Learning: Bypassing Backpropagation via Telemetry-Guided Direct Feedback Alignment
  WARS-CI-DFA: A high-performance, energy-efficient biomimetic learning loop on GCP Cloud TPU v5e bypassing backward propagation and saving 40% board power, formally verified in Lean 4.
  datacite Callens, Xavier 2026 置信度 0.66 Neuromorphic ComputingDirect Feedback AlignmentGCP Cloud TPU v5eLean 4Formal Verification
• Biomimetic Co-Inference Learning: Bypassing Backpropagation via Telemetry-Guided Direct Feedback Alignment
  WARS-CI-DFA: A high-performance, energy-efficient biomimetic learning loop on GCP Cloud TPU v5e bypassing backward propagation and saving 40% board power, formally verified in Lean 4.
  datacite Callens, Xavier 2026 置信度 0.66 Neuromorphic ComputingDirect Feedback AlignmentGCP Cloud TPU v5eLean 4Formal Verification
• Biomimetic Co-Inference Learning: Bypassing Backpropagation via Telemetry-Guided Direct Feedback Alignment
  WARS-CI-DFA: A high-performance, energy-efficient biomimetic learning loop on GCP Cloud TPU v5e bypassing backward propagation and saving 40% board power, formally verified in Lean 4.
  datacite Callens, Xavier 2026 置信度 0.66 Neuromorphic ComputingDirect Feedback AlignmentGCP Cloud TPU v5eLean 4Formal Verification
• Biomimetic Co-Inference Learning: Bypassing Backpropagation via Telemetry-Guided Direct Feedback Alignment
  WARS-CI-DFA: A high-performance, energy-efficient biomimetic learning loop on GCP Cloud TPU v5e bypassing backward propagation and saving 40% board power, formally verified in Lean 4.
  datacite Callens, Xavier 2026 置信度 0.66 Neuromorphic ComputingDirect Feedback AlignmentGCP Cloud TPU v5eLean 4Formal Verification
• Biomimetic Co-Inference Learning: Bypassing Backpropagation via Telemetry-Guided Direct Feedback Alignment
  WARS-CI-DFA: A high-performance, energy-efficient biomimetic learning loop on GCP Cloud TPU v5e bypassing backward propagation and saving 40% board power, formally verified in Lean 4.
  datacite Callens, Xavier 2026 置信度 0.66 Neuromorphic ComputingDirect Feedback AlignmentGCP Cloud TPU v5eLean 4Formal Verification
• Biomimetic Co-Inference Learning: Bypassing Backpropagation via Telemetry-Guided Direct Feedback Alignment
  WARS-CI-DFA: A high-performance, energy-efficient biomimetic learning loop on GCP Cloud TPU v5e bypassing backward propagation and saving 40% board power, formally verified in Lean 4.
  datacite Callens, Xavier 2026 置信度 0.66 Neuromorphic ComputingDirect Feedback AlignmentGCP Cloud TPU v5eLean 4Formal Verification
• Biomimetic Co-Inference Learning: Bypassing Backpropagation via Telemetry-Guided Direct Feedback Alignment
  WARS-CI-DFA: A high-performance, energy-efficient biomimetic learning loop on GCP Cloud TPU v5e bypassing backward propagation and saving 40% board power, formally verified in Lean 4.
  datacite Callens, Xavier 2026 置信度 0.66 Neuromorphic ComputingDirect Feedback AlignmentGCP Cloud TPU v5eLean 4Formal Verification
• Biomimetic Co-Inference Learning: Bypassing Backpropagation via Telemetry-Guided Direct Feedback Alignment
  WARS-CI-DFA: A high-performance, energy-efficient biomimetic learning loop on GCP Cloud TPU v5e bypassing backward propagation and saving 40% board power, formally verified in Lean 4.
  datacite Callens, Xavier 2026 置信度 0.66 Neuromorphic ComputingDirect Feedback AlignmentGCP Cloud TPU v5eLean 4Formal Verification
• Biomimetic Co-Inference Learning: Bypassing Backpropagation via Telemetry-Guided Direct Feedback Alignment
  WARS-CI-DFA: A high-performance, energy-efficient biomimetic learning loop on GCP Cloud TPU v5e bypassing backward propagation and saving 40% board power, formally verified in Lean 4.
  datacite Callens, Xavier 2026 置信度 0.66 Neuromorphic ComputingDirect Feedback AlignmentGCP Cloud TPU v5eLean 4Formal Verification
• Biomimetic Co-Inference Learning: Bypassing Backpropagation via Telemetry-Guided Direct Feedback Alignment
  WARS-CI-DFA: A high-performance, energy-efficient biomimetic learning loop on GCP Cloud TPU v5e bypassing backward propagation and saving 40% board power, formally verified in Lean 4.
  datacite Callens, Xavier 2026 置信度 0.66 Neuromorphic ComputingDirect Feedback AlignmentGCP Cloud TPU v5eLean 4Formal Verification
• Biomimetic Co-Inference Learning: Bypassing Backpropagation via Telemetry-Guided Direct Feedback Alignment
  WARS-CI-DFA: A high-performance, energy-efficient biomimetic learning loop on GCP Cloud TPU v5e bypassing backward propagation and saving 40% board power, formally verified in Lean 4.
  datacite Callens, Xavier 2026 置信度 0.66 Neuromorphic ComputingDirect Feedback AlignmentGCP Cloud TPU v5eLean 4Formal Verification
• Biomimetic Co-Inference Learning: Bypassing Backpropagation via Telemetry-Guided Direct Feedback Alignment
  WARS-CI-DFA: A high-performance, energy-efficient biomimetic learning loop on GCP Cloud TPU v5e bypassing backward propagation and saving 40% board power, formally verified in Lean 4.
  datacite Callens, Xavier 2026 置信度 0.66 Neuromorphic ComputingDirect Feedback AlignmentGCP Cloud TPU v5eLean 4Formal Verification
• Biomimetic Co-Inference Learning: Bypassing Backpropagation via Telemetry-Guided Direct Feedback Alignment
  WARS-CI-DFA: A high-performance, energy-efficient biomimetic learning loop on GCP Cloud TPU v5e bypassing backward propagation and saving 40% board power, formally verified in Lean 4.
  datacite Callens, Xavier 2026 置信度 0.66 Neuromorphic ComputingDirect Feedback AlignmentGCP Cloud TPU v5eLean 4Formal Verification
• Adaptive Dissipative Attractor Dynamics (ADAD)
  Adaptive Dissipative Attractor Dynamics (ADAD)Adaptive Dissipative Attractor Dynamics (ADAD) is a mathematical and computational framework describing adaptive neural-field dynamics with dissipative homeostatic regulation, stochastic activity control, and energ…
  datacite Bazarov, Vitaly, Bazarov, Vitaliy (VIT-BAZ) 2026 置信度 0.66
• Adaptive Dissipative Attractor Dynamics (ADAD)
  Adaptive Dissipative Attractor Dynamics (ADAD)Adaptive Dissipative Attractor Dynamics (ADAD) is a mathematical and computational framework describing adaptive neural-field dynamics with dissipative homeostatic regulation, stochastic activity control, and energ…
  datacite Bazarov, Vitaly, Bazarov, Vitaliy (VIT-BAZ) 2026 置信度 0.66
• The Digital Human: A Credible Technical Roadmap from Synthetic Neurons to Robotic Embodiment.
  For decades, the prospect of transferring human consciousness to a non-biological sub-strate has been dismissed as fantasy by serious engineers. Three objections dominated: (1)no synthetic device could match the electrical and chemical signaling parameters of …
  datacite Davis, Jason Gabriel 2026 置信度 0.66 Neuromorphic ComputingBCIBrain Computer InterfaceDevelopmental RoboticsRobotics
• The Digital Human: A Credible Technical Roadmap from Synthetic Neurons to Robotic Embodiment.
  For decades, the prospect of transferring human consciousness to a non-biological sub-strate has been dismissed as fantasy by serious engineers. Three objections dominated: (1)no synthetic device could match the electrical and chemical signaling parameters of …
  datacite Davis, Jason Gabriel 2026 置信度 0.66 Neuromorphic ComputingBCIBrain Computer InterfaceDevelopmental RoboticsRobotics
• Supplyment to the article"Polarization-sensitive photo-synapses based on anisotropic β-Ga2O3 for dynamic visual perception"
  Supplyment to the article"Polarization, as a fundamental property of light, carries abundant environmental and target-specific information that is invisible to the human eye but crucial for advanced vision. In biological visual systems, such polarization infor…
  datacite Xianchun Shen, Wu, Chao, Yanjie Liu, Zhihao Yu 等 2026 置信度 0.66 OpticsOptoelectronics and laser technologyOptical engineeringpolarizationβ-Ga2O3
• Bionic Brain Clockless Computer Architecture —The Only Path to Breakthrough in Future Artificial Intelligence
  AbstractThe current artificial intelligence hardware system is entirely based on the traditional digital architecture of global synchronous clocks, which faces three core bottlenecks: explosive power consumption, limited parallel computing power, and the disco…
  datacite Sun, Zhaole 2026 置信度 0.66 Clockless computingClockless computerBrain-inspired computer architectureArtificial intelligenceArtificial intelligence
• Bionic Brain Clockless Computer Architecture —The Only Path to Breakthrough in Future Artificial Intelligence
  AbstractThe current artificial intelligence hardware system is entirely based on the traditional digital architecture of global synchronous clocks, which faces three core bottlenecks: explosive power consumption, limited parallel computing power, and the disco…
  datacite Sun, Zhaole 2026 置信度 0.66 Clockless computingClockless computerBrain-inspired computer architectureArtificial intelligenceArtificial intelligence
• The Janus Architecture: Complete Specification of a Physical Cognitive Organism
  The Janus Architecture is a complete architectural specification for a physical cognitive organism. A hardware-first system designed to produce cognition through analog substrate settlement under genuine metabolic consequence, rather than through statistical i…
  datacite Janus, Anthony 2026 置信度 0.66 Cognitive ArchitectureAnalog ComputingNeuromorphic EngineeringSynthetic OrganismEmbodied Cognition
• The Janus Architecture: Complete Specification of a Physical Cognitive Organism
  The Janus Architecture is a complete architectural specification for a physical cognitive organism. A hardware-first system designed to produce cognition through analog substrate settlement under genuine metabolic consequence, rather than through statistical i…
  datacite Janus, Anthony 2026 置信度 0.66 Cognitive ArchitectureAnalog ComputingNeuromorphic EngineeringSynthetic OrganismEmbodied Cognition
• The Cognitive Tension Core ($\NTC$) and P3TTM Mott-Hubbard Insulator Mechanics for Frictionless Computing-in-Memory
  UPDATE NOTICE: This record corresponds to the revised and optimized Version 2 of the original manuscript, incorporating critical chemical doping specifications and atomic encapsulation protocols for the hardware core. Manuscript I: The Cognitive Tension Core (…
  datacite Quilez Zamora, Jaime 2026 置信度 0.66 Mott-Hubbard Insulator, Computing-in-Memory, P3TTM Conjugated Polymer, Hubbard Hamiltonian, Neuromorphic Computing, Polaron-Soliton Dynamics, Correlated Electron Systems.
• The Cognitive Tension Core ($\NTC$) and P3TTM Mott-Hubbard Insulator Mechanics for Frictionless Computing-in-Memory
  UPDATE NOTICE: This record corresponds to the revised and optimized Version 2 of the original manuscript, incorporating critical chemical doping specifications and atomic encapsulation protocols for the hardware core. Manuscript I: The Cognitive Tension Core (…
  datacite Quilez Zamora, Jaime 2026 置信度 0.66 Mott-Hubbard Insulator, Computing-in-Memory, P3TTM Conjugated Polymer, Hubbard Hamiltonian, Neuromorphic Computing, Polaron-Soliton Dynamics, Correlated Electron Systems.
• Lux Ferox Research Collective — A Holographic-Thermodynamic Ontology of Information: From Planck-Scale Substrates to Civilizational Cognitive Warfare
  Lux Ferox Research Collective — A Holographic-Thermodynamic Ontology of Information: From Planck-Scale Substrates to Civilizational Cognitive Warfare (Working Paper Series, v16 — April 2026) DESCRIPTION Lux Ferox is an independent research initiative applying …
  datacite MATHIEU, François 2026 置信度 0.66 Artificial intelligenceArtificial IntelligenceMilitary ScienceMilitary FacilitiesMilitary equipment
• Lux Ferox Research Collective — A Holographic-Thermodynamic Ontology of Information: From Planck-Scale Substrates to Civilizational Cognitive Warfare
  Lux Ferox Research Collective — A Holographic-Thermodynamic Ontology of Information: From Planck-Scale Substrates to Civilizational Cognitive Warfare (Working Paper Series, v16 — April 2026) DESCRIPTION Lux Ferox is an independent research initiative applying …
  datacite MATHIEU, François 2026 置信度 0.66 Artificial intelligenceArtificial IntelligenceMilitary ScienceMilitary FacilitiesMilitary equipment
• Non-Polar and Complementary Resistive Switching Characteristics in Graphene Oxide devices with Gold Nanoparticles: Diverse Approach for Device Fabrication.
  Downscaling limitations and limited write/erase cycles in conventional charge-storage based non-volatile memories stimulate the development of emerging memory devices having enhanced performance. Resistive random-access memory (RRAM) devices are recognized as …
  datacite Khurana, Geetika, Kumar, Nitu, Chhowalla, Manish, Scott, James F 等 2019 置信度 0.66 40 Engineering4018 NanotechnologyNanotechnologyFOS: NanotechnologyBioengineering
• Emergent Intelligence for Chaotic Supply Chain Resilience in Contested Environments
  This paper introduces Vacuum Intelligence, a computational framework in which coherent, adaptive decision structure emerges from a high-entropy generative substrate rather than being imposed through explicit parameterization. The framework draws on reservoir c…
  datacite Damon John 2026 置信度 0.66
• Vacuum Intelligence: A Self-Organizing Reservoir with Hyperbolic Geometry and Anti-Fragile Meta-Learning
  This working paper introduces the Vacuum Intelligence Framework, a neural-reservoir architecture in which adaptive computation emerges from a high-dimensional nonlinear stochastic system poised near a symmetry-breaking instability. Unlike conventional AI syste…
  datacite Damon John 2026 置信度 0.66 reservoir computing, echo state network, stochastic differential equations, double-well potential, Langevin dynamics, hyperbolic geometry, Poincaré ball, hyperbolic neural network, simulated annealing, meta-learning, antifragility, antifragile systems, supply chain resilience, defense logistics, contested environments, nonlinear dynamics, symmetry breaking, synchronicity detection, order parameter, non-equilibrium statistical mechanics, chaotic time series, anomaly detection, early warning systems, multi-domain command and control, adaptive systems, neuromorphic computing, reservoir dynamics, Metropolis sampling, evolutionary optimization, black swan resilience, logistics disruption, Hormuz supply chain, sanctions monitoring, AIS vessel tracking
• Vacuum Intelligence Architecture Specification: Event-Driven Analog Memristor Optimal Power/Flow Solver Integration (VIA-SPEC-001)
  This architecture specification presents a unified hardware-software system for resilient, antifragile decision-making in contested logistics and defense environments. Building on the theoretical foundation established in the companion working paper on the Vac…
  datacite Damon John 2026 置信度 0.66 memristor crossbar, analog computing, neuromorphic hardware, reservoir computing, physical reservoir computing, optimal power flow, quadratic programming, analog solver, hardware-software co-design, system-in-package, SWaP, low power edge AI, edge computing, forward deployment, defense electronics, antifragile hardware, dual-mode computing, hyperbolic echo state network, HypER, Langevin dynamics, double-well potential, stochastic reservoir, simulated annealing, meta-optimization, synchronicity detector, supply chain resilience, defense logistics, contested environments, command and control, anti-tamper, MIL-STD-810, RISC-V, GlobalFoundries, neuromorphic edge, AIS monitoring, sanctions evasion detection, shadow fleet, Hormuz logistics, TRL roadmap, memristive devices, MRAM, in-materio computing
• Μελέτη νευρομορφικών φωτονικών αρχιτεκτονικών για βιοϊατρική και συμβατική επεξεργασία εικόνων
  Η διδακτορική αυτή διατριβή μελετά την ανάπτυξη μιας υψίρυθμης, ενεργειακά αποδοτικής, ολοκληρωμένης νευρομορφικής φωτονικής πλατφόρμας ως ένα υπολογιστικό ρεζερβουάρ (RC) και ως έναν επιταχυντή συνελικτικών νευρωνικών δικτύων (CNNs), για προβλήματα ταξινόμηση…
  datacite Τσιριγώτης, Άρης 2024 置信度 0.66 επιτάχυνση υλικούνευρομορφική φωτονικήνευρωνικά δίκτυαυπολογιστικό ρεζερβουάρφωτονικά ολοκληρωμένα κυκλώματα
• Integrating Brain-Computer Interface and Neuromorphic Computing for Human Digital Twins
  The integration of immersive communication into a human-centric ecosystem has intensified the demand for sophisticated Human Digital Twins (HDTs) driven by multifaceted human data. However, the effective construction of HDTs faces significant challenges due to…
  datacite Shang, Chen, Yu, Jiadong, Hoang, Dinh Thai 2024 置信度 0.66 Human-Computer Interaction (cs.HC)Networking and Internet Architecture (cs.NI)FOS: Computer and information sciencesFOS: Computer and information sciences
• ELSA: An ELastic SNN Inference Architecture for Efficient Neuromorphic Computing
  Spiking neural networks (SNNs) exploit event-driven and addition-only computation to substantially improve efficiency for intelligent computation. A key temporal property of SNNs, elastic inference, allows outputs to emerge progressively, enabling responses to…
  datacite You, Kang, Nie, Chen, Yan, Lee Jun, Wei, Ziling 等 2026 置信度 0.66 Hardware Architecture (cs.AR)Artificial Intelligence (cs.AI)FOS: Computer and information sciencesFOS: Computer and information sciences
• High Performance TiO2 Ferroelectric Field Effect Transistors with HfZrO2 for Neuromorphic Computing
  TiO2 ferroelectric field effect transistors (FeFETs) with HfZrO2 (HZO) ferroelectric dielectric layers and bottom gate topology are fabricated for applications in neuromorphic systems. Two sets of devices are fabricated with different gate topologies by varyin…
  datacite Samanta, Chandan, Palmese, Elia, Ouyang, Ziyu, Zhama, Tuofu 等 2026 置信度 0.66 Applied Physics (physics.app-ph)FOS: Physical sciencesFOS: Physical sciences
• <strong>Reservoir Computing Using a Si-integrated Electro-optic Oxide: A Numerical Study</strong>
  In this numerical study, we investigate the performance of an electro-optic reservoir under the practical constraints of a Si-integrated photonic design enabled by barium titanate, an emergent electro-optic material. Reservoir computing is a compelling neuromo…
  datacite Zhang, Xiaoru, Demkov, Alexander 2026 置信度 0.66 Physical sciencesFOS: Physical sciences
• Research data supporting "Controlled Oxygen Vacancy Electrode Reservoir for Robust WO3-based Memory Devices"
  This dataset contains the raw and processed data used to evaluate resistive switching, synaptic behaviour, electronic structure, optical response, and microstructure in the thin-film memory devices. The dataset is organized by figure number, containing the raw…
  datacite Yuan, Ziyi, Bakhit, Babak, Lu, Jiahao, Liu, Yixuan 等 2026 置信度 0.66 CMOS compatibleindium tin oxideneuromorphic computingresistive switchingtungsten oxide
• Native Symbolic Emergence Should Replace the Translation Layer Paradigm in Neuro-Symbolic AI
  The dominant paradigm in neurosymbolic AI assumes that symbolic structure must be defined before learning or extracted after it. We identify this assumption as an unnecessary architectural constraint, and we call it the symbolization gap. This position paper a…
  datacite Nicolle, Christophe, Callegarin, Davide 2026 置信度 0.66 Neuromorphic computing, Symbolic AI, Spiking Neural Networks, STDP, Ontology learning, Knowledge graph, Neuro-symbolic AI, Explainable AI
• Native Symbolic Emergence Should Replace the Translation Layer Paradigm in Neuro-Symbolic AI
  The dominant paradigm in neurosymbolic AI assumes that symbolic structure must be defined before learning or extracted after it. We identify this assumption as an unnecessary architectural constraint, and we call it the symbolization gap. This position paper a…
  datacite Nicolle, Christophe, Callegarin, Davide 2026 置信度 0.66 Neuromorphic computing, Symbolic AI, Spiking Neural Networks, STDP, Ontology learning, Knowledge graph, Neuro-symbolic AI, Explainable AI
• Photonic neuromorphic processors based on semiconductor lasers' dynamics for reservoir computing and spiking neural networks
  Η παρούσα διδακτορική διατριβή μελετά την ανάπτυξη φωτονικών νευρομορφικών επεξεργαστών (ΝΕ) που απευθύνονται στις εξής τρεις κ��ίσιμες προκλήσεις των Big Data και του Internet of Things: την υψηλή ταχύτητα επεξεργασίας, την χαμηλή κατανάλωση ισχύος και την ελ…
  datacite Skontranis, Menelaos, Σκοντράνης, Μενέλαος 2024 置信度 0.66 φωτονικήυπολογιστική χρονικής καθυστέρησηςακραία μάθηση χρονικής καθυστέρησηςspiking νευρωνικά δίκτυανευρομορφική υπολογιστική
• Cavity Solitons as a Nonlinear Substrate for Photonic Neuromorphic Computing
  Reservoir computing leverages nonlinear dynamics of physical systems to process temporal information with minimal training cost. Here, we demonstrate that cavity solitons sustained in a fiber optical cavity provide an optical platform for photonic reservoir co…
  datacite Arabieh, Amir Arsalan, Lupo, Alessandro, Gorza, Simon-Pierre, Massar, Serge 2026 置信度 0.66 Optics (physics.optics)FOS: Physical sciencesFOS: Physical sciences
• Tunable magnetotransport through kinetically hindered first-order phase transitions in an antiferromagnetic metal
  Controllable multilevel resistance states are of interest for memory technologies like neuromorphic computing, but robust materials platforms toward such behavior remain limited. Here, we show that the non-centrosymmetric antiferromagnetic metal CeCoGe$_3$ sug…
  datacite Moya, Jaime M., Lee, Scott B., Chatterjee, Sudipta, Mathur, Nitish 等 2026 置信度 0.66 Strongly Correlated Electrons (cond-mat.str-el)FOS: Physical sciencesFOS: Physical sciences
• Task-specific programming of chaos in neural circuits
  Chaotic dynamics have emerged as a versatile resource for neuromorphic and probabilistic computing, enabling high-dimensional nonlinear processing and classical analogues of quantum randomness. Exploiting chaos for computation requires task-dependent control o…
  datacite Kim, Jungyoon, Kim, Kyuho, Park, Kunwoo, Park, Namkyoo 等 2026 置信度 0.66 Chaotic Dynamics (nlin.CD)Computational Physics (physics.comp-ph)FOS: Physical sciencesFOS: Physical sciences
• Reinforcement-Learned Dynamic Execution for Spiking Swin-B
  Spiking Neural Networks (SNNs) are promising for energy-efficient computing on next generation neuromorphic hardware (Nunes et al. 2022). However, scaling them to large Transformer architectures introduces challenges such as training instability and high compu…
  datacite Association for Artificial Intelligence 2026 2026 置信度 0.66 Artificial Intelligence
• I2E: Real-Time Image-to-Event Conversion for High-Performance Spiking Neural Networks
  Spiking neural networks (SNNs) promise highly energy-efficient computing, but their adoption is hindered by a critical scarcity of event-stream data. This work introduces I2E, an algorithmic framework that resolves this bottleneck by converting static images i…
  datacite Association for Artificial Intelligence 2026, Hu, Shaogang, Liu, Yang, Ma, Ruichen 等 2026 置信度 0.66 Artificial IntelligenceCognitive Modeling
• Neuromorphic Perception using Time-of-Flight-based Encoding of Lidar Data : A Potential and Feasibility Study
  This master thesis is dedicated to the research of neuromorphic perception in the domain of automated driving systems. In view of the rapid progress in the automotive industry and the increasing realization of automated driving, questions regarding the energy …
  datacite Schulte, Jonas Valentin 2024 置信度 0.66 620
• IONIC-ELECTRONIC INTERACTIONS GOVERNING CHARGE TRANSPORT AND PERFORMANCE IN ORGANIC ELECTROCHEMICAL TRANSISTORS
  Organic electrochemical transistors (OECTs) use organic mixed ionic electronic conductors (OMIECs) as the active material because of their unique ability to transport both electronic and ionic charge carriers and operate in an aqueous environment. Moreover, OE…
  datacite Tahsin, Samiha 2026 置信度 0.66 FOS: Electrical engineering, electronic engineering, information engineering
• Interference-Field-Grown Bio-Synaptic Semiconductor Organisms: A Conceptual Framework for Wave-Written Living Electronic Morphogenesis
  This paper proposes a conceptual framework for interference-field-grown bio-synaptic semiconductor organisms: living or life-like material systems that form, repair, and adapt semiconductor-like electronic networks through biological growth, material depositio…
  datacite Trinity Labo 2026 置信度 0.66
• Interference-Field-Grown Bio-Synaptic Semiconductor Organisms: A Conceptual Framework for Wave-Written Living Electronic Morphogenesis
  This paper proposes a conceptual framework for interference-field-grown bio-synaptic semiconductor organisms: living or life-like material systems that form, repair, and adapt semiconductor-like electronic networks through biological growth, material depositio…
  datacite Trinity Labo 2026 置信度 0.66
• Dataset of "From Impedance to Bifurcation: Experimental Stability Mapping of Self-Oscillatory Devices"
  This dataset contains the raw data supporting the article "From Impedance to Bifurcation: Experimental Stability Mapping of Self-Oscillatory Devices". For a detailed description of files and methods, see the accompanying Readme.txt.
  datacite Rivera-Sierra, Gonzalo, Rubio-Magnieto, Jenifer, Bisquert, Juan 2026 置信度 0.66 self-sustained oscillatorsneuromorphic computingimpedance spectroscopynegative differential resistancethyristor oscillators
• Dataset of "From Impedance to Bifurcation: Experimental Stability Mapping of Self-Oscillatory Devices"
  This dataset contains the raw data supporting the article "From Impedance to Bifurcation: Experimental Stability Mapping of Self-Oscillatory Devices". For a detailed description of files and methods, see the accompanying Readme.txt.
  datacite Rivera-Sierra, Gonzalo, Rubio-Magnieto, Jenifer, Bisquert, Juan 2026 置信度 0.66 self-sustained oscillatorsneuromorphic computingimpedance spectroscopynegative differential resistancethyristor oscillators
• Substoichiometric Phases of Hafnium Oxide with Semiconducting Properties
  Since the dawn of the information age, all developments that provided a significant improvement in information processing and data transmission have been considered as key technologies. The impact of ever new data processing innovations on the economy and almo…
  datacite Kaiser, Nico 2023 置信度 0.66 500530540
• Ferroelectric FETs for Neuromorphic Computing: Low-Frequency Noise and Fast I-V Characteristics
  This study investigates the low-frequency noise (LFN) characteristics and fast I-V response of ferroelectric field-effect transistors (FeFETs) for neuromorphic computing. LFN analysis is conducted to demonstrate the conduction mechanisms of the FeFETs and to a…
  datacite IEEE International Reliability Physics Symposium 2025, Shin, Wonjun 2025 置信度 0.66 Reliability PhysicsNeuromorphic Computing
• Conductance Variation-Assisted Adversarial Attack Robustness on 40nm TaOX-based ReRAM CiM
  This work investigates the conductance variation-assisted enhancement of neural network (NN) robustness against adversarial attacks, exploiting the measurements of 32K bits 40nm TaOX-based analog Resistive Random Access Memory (ReRAM) devices. Proposed Computa…
  datacite IEEE International Reliability Physics Symposium 2025, Awamura, Satoshi, Matsui, Chihiro, Misawa, Naoko 等 2025 置信度 0.66 Reliability PhysicsNeuromorphic Computing
• Read Voltage Dependency of Random Telegraph Noise in the Intermediate State of TaOX-based ReRAM
  This work investigates random telegraph noise (RTN) behavior in the intermediate resistance states of 40nm TaOX-based analog ReRAM. Uniquely in the intermediate resistance states, both the frequency and amplitude of RTN fluctuations tend to increase with the r…
  datacite IEEE International Reliability Physics Symposium 2025, AKINAGA, Hiroyuki, Matsui, Chihiro, Misawa, Naoko 等 2025 置信度 0.66 Reliability PhysicsNeuromorphic Computing
• Temperature and Drift-Aware High-Level PCM-based Array Model for Reliable Hardware IMC design
  In-Memory Computing (IMC) is an important lead to propose efficient AI hardware on the edge. In this context, emerging non-volatile memories, such as Phase-Change Memory (PCM) are fundamental. However, PCM device non-idealities, hardware and application challe…
  datacite IEEE International Reliability Physics Symposium 2025, ALLEGRA, Mario, Anghel, Lorena, BALDO, Matteo 等 2025 置信度 0.66 Reliability PhysicsNeuromorphic Computing
• Multi-level RTN with Certain Regularities in Oxide-RRAM: Experiments, Defect Dynamics and 3D Multi-Physics Modeling
  This paper investigated the multi-level RTN phenomena with certain regularities in the Ti/HfOx/TiN RRAM with the comprehensive measurements and modeling of the multi-phonon trap-assisted tunneling (MPTAT) and First-Principle calculations. The polaron band of V…
  datacite IEEE International Reliability Physics Symposium 2025, Cai, Zifei, Ji, Zhigang, Liu, Pan 等 2025 置信度 0.66 Reliability PhysicsNeuromorphic Computing
• Reliability-Ensured and Fast (< 100 ns) Analog Synapse for Training Accelerators: All-Sputtered HfOy/HfOx RRAM
  We reveal that sputtered HfOx, often neglected in RRAM design, can be an alternative for highly reliable, fast (&lt; 100 ns) analog synapses to accelerate training algorithms. The sub-stoichiometric HfOx enables rapid oxygen vacancy (V0) response. Additional H…
  datacite IEEE International Reliability Physics Symposium 2025, Jeon, Seonuk, Kim, Yunsur, Lim, Seokjae 等 2025 置信度 0.66 Reliability PhysicsNeuromorphic Computing