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• Biomimetic and AI-Guided Designs for Redox-Active Semiconducting Polymers
  Bioelectronics serves as an indispensable technology to directly interface with biological tissues for uncovering biological mechanism and applying health diagnosis and therapeutic interventions to the human body. Despite the considerable successes achieved on…
  datacite Dai, Yahao 2024 置信度 0.66 BioelectronicsPolymer semiconductorsOrganic electrochemical transistorsBiosensorsHydrogels
• Biomimetic and AI-Guided Designs for Redox-Active Semiconducting Polymers
  Bioelectronics serves as an indispensable technology to directly interface with biological tissues for uncovering biological mechanism and applying health diagnosis and therapeutic interventions to the human body. Despite the considerable successes achieved on…
  datacite Dai, Yahao 2024 置信度 0.66 BioelectronicsPolymer semiconductorsOrganic electrochemical transistorsBiosensorsHydrogels
• ARCHITECTURAL BLUEPRINT THE SPINTRONIC NEURAL PROCESSING UNIT
  This work presents the Spintronic Neural Processing Unit (sNPU), a non-von Neumann hardware architecture designed to eliminate the memory wall and thermal limitations of conventional silicon GPU architectures during large-scale artificial intelligence inferenc…
  datacite Procaccia, Francis 2026 置信度 0.66 Device physics spin-orbit torquemagnetic tunnel junctionSOT-MTJbeta-tungstenspin Hall effect
• SPARSE COINCIDENCE-BASED SEMANTIC ATTENTION FOR SPIKING NEURAL SENTENCE EMBEDDING
  Transformer-based models dominate natural language processing (NLP) but incur substantial computational costs due to dense matrix multiplications within self-attention mechanisms. Spiking Neural Networks (SNNs) provide a biologically plausible and energy-effic…
  datacite Muhammad, Akhyar 2026 置信度 0.66 Spiking Neural NetworksNatural Language ProcessingSentence EmbeddingSemantic AttentionNeuromorphic Computing
• Quantization Meets Spikes: Nearly Lossless Conversion at the First Timestep via Polarity Multi-Spike Mapping
  Spiking neural networks (SNNs) offer advantages in computational efficiency via event-driven computing, compared to traditional artificial neural networks (ANNs). While direct training methods tackle the challenge of non-differentiable activation mechanisms in…
  datacite Zhang, Hangming, Li, Zheng, Ma, Chenxiang, Tang, Huajin 等 2025 置信度 0.66 Neural and Evolutionary Computing (cs.NE)FOS: Computer and information sciencesFOS: Computer and information sciences
• BrainIAc: A Multi-Scale Adaptive Dynamical Systems Framework for Computational Neuroscience (v2.2)
  Multiscale Spiking Neural Learning System with Biological Control Substrate Overview This project presents a unified computational framework for learning in spiking neural networks (SNNs) coupled with a hierarchical biological control substrate. The system int…
  datacite Vallois, Theo Henock André 2026 置信度 0.66 spiking neural networksneuromorphic computinghybrid neural networksepropBPTT
• BrainIAc: A Multi-Scale Adaptive Dynamical Systems Framework for Computational Neuroscience (v2.2)
  Multiscale Spiking Neural Learning System with Biological Control Substrate Overview This project presents a unified computational framework for learning in spiking neural networks (SNNs) coupled with a hierarchical biological control substrate. The system int…
  datacite Vallois, Theo Henock André 2026 置信度 0.66 spiking neural networksneuromorphic computinghybrid neural networksepropBPTT
• CAMELEON: Cognitively Adaptive Memory with Emotion-weighted Layered Expert Orchestration Network
  We present CAMELEON — a conceptual architecture for AI agents that grow more personalised through lived interaction rather than retraining. The architecture combines emotion-weighted context compression, interpretable domain-expert routing via keyword saliency…
  datacite Arumugam, Rajkumar 2026 置信度 0.66 mixture of experts, continual learning, affective computing, neuromorphic computing, cognitive architecture
• CAMELEON: Cognitively Adaptive Memory with Emotion-weighted Layered Expert Orchestration Network
  We present CAMELEON — a conceptual architecture for AI agents that grow more personalised through lived interaction rather than retraining. The architecture combines emotion-weighted context compression, interpretable domain-expert routing via keyword saliency…
  datacite Arumugam, Rajkumar 2026 置信度 0.66 mixture of experts, continual learning, affective computing, neuromorphic computing, cognitive architecture
• A tensor network approach for chaotic time series prediction
  Making accurate predictions of chaotic time series is a complex challenge. Reservoir computing, a neuromorphic-inspired approach, has emerged as a powerful tool for this task. It exploits the memory and nonlinearity of dynamical systems without requiring exten…
  datacite Martínez-Peña, Rodrigo, Orús, Román 2025 置信度 0.66 Machine Learning (cs.LG)Neural and Evolutionary Computing (cs.NE)Computational Physics (physics.comp-ph)FOS: Computer and information sciencesFOS: Computer and information sciences
• An Optimization Framework for Automated Assessment of Biological Plausibility of Spiking Neurons
  Biological plausibility is a key concept in neuromorphic computing and spiking neural networks, yet it remains inconsistently defined and difficult to quantify. In this work, we present an open-source framework for the automated assessment of biological plausi…
  datacite Nitzsche, Sven, Ionita, Alexandru, Faust, Andreas, Ionescu, Bogdan 等 2026 置信度 0.66 Neural and Evolutionary Computing (cs.NE)FOS: Computer and information sciencesFOS: Computer and information sciences
• <strong>Integration of oscillator-based feature extraction for energy-efficient convolutional neural networks</strong>
  The rapid growth in machine learning (ML) and artificial intelligence (AI) workloads has increased the demand for computing power. Although digital computing accelerators dominate today's market, analog computing architectures are emerging as promising energy-…
  datacite Kapadia, Rehan R., Mousavi, Mirbehrad, Wu, Zezhi, Ahsan, Ragib 等 2026 置信度 0.66 Engineering
• A 65-nm Privacy-Preserving Neuromorphic Encoder With 7.13-nJ Efficiency, 2.38-Mb/mm^2 Item-Memory Density, and Federated Learning Support
  The increasing demand for privacy-preserving personal data analytics in smart assistants, wearable health monitors, and context-aware systems calls for hardware that is both energy-efficient and secure. This work presents a 65-nm privacy-preserving neuromorphi…
  datacite Cheng, Boyang, Liu, Jianbo, Davis, Steven, Enciso, Zephan M. 等 2026 置信度 0.66 Hardware Architecture (cs.AR)FOS: Computer and information sciencesFOS: Computer and information sciences
• Neuromorphic Wireless Split Computing with Resonate-and-Fire Neurons
  Neuromorphic computing offers an energy-efficient alternative to conventional deep learning accelerators, particularly for real-time processing of time-series data. However, many edge applications, such as wireless sensing and audio recognition, generate strea…
  datacite Wu, Dengyu, Chen, Jiechen, Poor, H. Vincent, Rajendran, Bipin 等 2025 置信度 0.66 Machine Learning (cs.LG)Information Theory (cs.IT)Neural and Evolutionary Computing (cs.NE)FOS: Computer and information sciencesFOS: Computer and information sciences
• Neural dynamical systems on ferroelectric compute-in-memory for real-time forecasting
  Neural dynamical systems are expressive temporal predictors that capture continuous-time dynamics through fine-grained state updates. However, this sequential structure maps poorly onto digital hardware optimized for dense matrix operations, a mismatch that an…
  datacite Katti, Keshava, Selvakumar, Adithya, Chaudhari, Pratik, Jariwala, Deep 2026 置信度 0.66 Emerging Technologies (cs.ET)Hardware Architecture (cs.AR)Neural and Evolutionary Computing (cs.NE)FOS: Computer and information sciencesFOS: Computer and information sciences
• The Coherence Cost: 1/√Depth as the Universal Law of Compiled Existence
  The Coherence Cost: 1/√Depth as the Universal Law of Compiled Existence Driven By Dean A. Kulik June 2026 Abstract Five independent systems — a deep residual neural network, a neural optimizer, a graph clustering algorithm, an online learning protocol, and a n…
  datacite kulik, dean 2026 置信度 0.66
• The Coherence Cost: 1/√Depth as the Universal Law of Compiled Existence
  The Coherence Cost: 1/√Depth as the Universal Law of Compiled Existence Driven By Dean A. Kulik June 2026 Abstract Five independent systems — a deep residual neural network, a neural optimizer, a graph clustering algorithm, an online learning protocol, and a n…
  datacite kulik, dean 2026 置信度 0.66
• 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
• Verdigraph NeuroGenesis: A Software Framework for Self-Evolving AI-Agent Cognitive Substrates, with Mechanically Verified Operational Invariants (v0.2.0)
  [DEPRECATED DUPLICATE — superseded by the canonical Verdigraph record, DOI 10.5281/zenodo.20261686. This orphan deposit is retained for link stability only; cite the canonical record.] Superseded — canonical v0.2.0 has moved. This record is the original v0.2.0…
  datacite Hart, Justin 2026 置信度 0.66 artificial intelligenceAI agentsformal verificationLean theorem proverLean 4
• Verdigraph NeuroGenesis: A Software Framework for Self-Evolving AI-Agent Cognitive Substrates, with Mechanically Verified Operational Invariants (v0.2.0)
  [DEPRECATED DUPLICATE — superseded by the canonical Verdigraph record, DOI 10.5281/zenodo.20261686. This orphan deposit is retained for link stability only; cite the canonical record.] Superseded — canonical v0.2.0 has moved. This record is the original v0.2.0…
  datacite Hart, Justin 2026 置信度 0.66 artificial intelligenceAI agentsformal verificationLean theorem proverLean 4
• SPARSE COINCIDENCE-BASED SEMANTIC ATTENTION FOR SPIKING NEURAL SENTENCE EMBEDDING
  Transformer-based models dominate natural language processing (NLP) but in-cur substantial computational costs due to dense matrix multiplications withinself-attention mechanisms. Spiking Neural Networks (SNNs) provide a biolog-ically plausible and energy-effi…
  datacite Muhammad, Akhyar 2026 置信度 0.66 Spiking Neural NetworksNatural Language ProcessingSentence EmbeddingSemantic AttentionNeuromorphic Computing
• SECURE AND INTELLIGENT IOT SYSTEMS: ARCHITECTURES, THREATS, AND DEFENSE
  This book brings together advanced research that explores the design, security, and sustainability of intelligent and connected computing systems. The chapters collectively reflect the rapid evolution of embedded intelligence, trusted digital environments, and…
  datacite Mebarki, Abdelkrim, DABBABI, Karim, AGOI, Moses Adeolu, OGUNSANWO, Gbenga Oyewole 等 2026 置信度 0.66 secure IoT systemsneuromorphic computingcognitive microcontrollersRISC architectureedge computing
• SECURE AND INTELLIGENT IOT SYSTEMS: ARCHITECTURES, THREATS, AND DEFENSE
  This book brings together advanced research that explores the design, security, and sustainability of intelligent and connected computing systems. The chapters collectively reflect the rapid evolution of embedded intelligence, trusted digital environments, and…
  datacite Mebarki, Abdelkrim, DABBABI, Karim, AGOI, Moses Adeolu, OGUNSANWO, Gbenga Oyewole 等 2026 置信度 0.66 secure IoT systemsneuromorphic computingcognitive microcontrollersRISC architectureedge computing
• Neuromorphic Computing For Real Time Handwritten Digit Recognition
  The emergence of neuromorphic computing as a biologically inspired paradigm has created remarkable opportunities for ultra-low-latency, energy-efficient pattern recognition tasks. Conventional deep learning systems, while achieving state-of-the-art recognition…
  datacite Sandhiya K, A.S. Arunachalam 2026 置信度 0.66 Neuromorphic ComputingHandwritten Digit RecognitionSpiking Neural Networks (SNN)STBPTemporal Coding; snnTorch
• Neuromorphic Computing For Real Time Handwritten Digit Recognition
  The emergence of neuromorphic computing as a biologically inspired paradigm has created remarkable opportunities for ultra-low-latency, energy-efficient pattern recognition tasks. Conventional deep learning systems, while achieving state-of-the-art recognition…
  datacite Sandhiya K, A.S. Arunachalam 2026 置信度 0.66 Neuromorphic ComputingHandwritten Digit RecognitionSpiking Neural Networks (SNN)STBPTemporal Coding; snnTorch
• The Scale-Invariant Informational Landscape: Extending the Hamouda Informational Gravity Model (HIGM) to Quantum Biological Fidelity and Neuromorphic Computing
  datacite Hamouda, Samir 2026 置信度 0.66
• Topology Is the Substrate: Cross-Emotion Coupling as the Load-Bearing Requirement for Computational Emotional Architecture
  Four research communities are each building a piece of the same machine, and none of them is talking to the others. Neuromorphic robotic skin now senses touch and pain. Neuromorphic chips now process at biological timescales and power budgets. Brain-computer i…
  datacite Lee, Wilton 2026 置信度 0.66 Kuramoto oscillatoremotional architecturecross-emotion couplingaffective computingmachine presence
• Topology Is the Substrate: Cross-Emotion Coupling as the Load-Bearing Requirement for Computational Emotional Architecture
  Four research communities are each building a piece of the same machine, and none of them is talking to the others. Neuromorphic robotic skin now senses touch and pain. Neuromorphic chips now process at biological timescales and power budgets. Brain-computer i…
  datacite Lee, Wilton 2026 置信度 0.66 Kuramoto oscillatoremotional architecturecross-emotion couplingaffective computingmachine presence
• Project Mnemosyne: From Device to Field (Associative Memory and Selective Forgetting in Janus Fractal Crossbar Array)
  Project Mnemosyne bridges the gap between Project Janus [1]—a single fractal memristive junction—and the neuromorphic computing systems envisioned in Project Raphael. Where Janus established a single synapse capable of 32-level analog storage and KWW stretched…
  datacite Liu, Tung Ning 2026 置信度 0.66 reservoir computing; associative memory; KWW forgetting; Janus memristor; (Eu,Pr,Y)2O3; neuromorphic computing; Menger sponge; fractal crossbar; Lorenz prediction; selective forgetting
• Cerebellum-Inspired Memtransistors Enable Emergent Differentiation for Hardware-Efficient Novelty Detection
  Artificial intelligence (AI) algorithms are currently executed using silicon-based hardware, resulting in excessively high energy demand for data centers. Edge computing AI for healthcare, robotics, and autonomous vehicles presents even stricter constraints on…
  datacite Hersam, Mark, Sangwan, Vinod, Trivedi, Amit, Raman, Indira 等 2026 置信度 0.66 neuromorphic computing, memtransistor, cerebellum, anomaly detection, molybdenum disulfide, edge computing, arryhthmia detection
• Cerebellum-Inspired Memtransistors Enable Emergent Differentiation for Hardware-Efficient Novelty Detection
  Artificial intelligence (AI) algorithms are currently executed using silicon-based hardware, resulting in excessively high energy demand for data centers. Edge computing AI for healthcare, robotics, and autonomous vehicles presents even stricter constraints on…
  datacite Hersam, Mark, Sangwan, Vinod, Trivedi, Amit, Raman, Indira 等 2026 置信度 0.66 neuromorphic computing, memtransistor, cerebellum, anomaly detection, molybdenum disulfide, edge computing, arryhthmia detection
• Inductive nanopore synapse element for iontronic neuromorphic computing
  preprints 2023 置信度 0.74
• Ultrafast Silicon Optical Nonlinear Activator for Neuromorphic Computing
  Abstract Optical neural networks (ONNs) have shown great promise in overcoming the speed and efficiency bottlenecks of artificial neural networks (ANNs). However, the absence of high-speed, energy-efficient nonlinear activators significantly impedes the advanc…
  preprints Siqi Yan, Ziwen Zhou, Chen Liu, Weiwei Zhao 等 2023 置信度 0.74
• Orchestrated excitatory and inhibitory plasticity produces stable dynamics in heterogeneous neuromorphic computing systems
  preprints 2023 置信度 0.74
• Proposing magnetoimpedance effect for neuromorphic computing
  preprints 2023 置信度 0.74
• Weighted Spin Torque Nano-Oscillator System for Neuromorphic Computing
  preprints 2023 置信度 0.74
• Adaptive Programmable Networks for In Materia Neuromorphic Computing
  Abstract Nanomagnetic artificial spin-systems are ideal candidates for neuromorphic hardware. Their passive memory, state-dependent dynamics and nonlinear GHz spin-wave response provide powerful computation. However, any single physical reservoir must trade-of…
  preprints Kilian Stenning, Jack Gartside, Luca Manneschi, Christopher Cheung 等 2022 置信度 0.74
• Stable recurrent dynamics in heterogeneous neuromorphic computing systems using excitatory and inhibitory plasticity
  preprints 2023 置信度 0.74
• Photonic Multiplexing Techniques for Optical Neuromorphic Computing
  preprints 2022 置信度 0.74
• Spike Optimization to Improve Properties of Ferroelectric Tunnel Junction Synaptic Devices for Neuromorphic Computing System Applications
  The continuous advancement of Artificial Intelligence (AI) technology depends on the efficient processing of unstructured data, encompassing text, speech, and video. Traditional serial computing systems based on the von Neumann architecture, employed in inform…
  preprints Jisu Byun, Wonwoo Kho, Hyunjoo Hwang, Yoomi Kang 等 2023 置信度 0.74
• Neuromorphic Computing Based on Wavelength-Division Multiplexing
  preprints 2022 置信度 0.74
• Neuromorphic computing for short-term wind power forecasting
  preprints 2022 置信度 0.74
• Bio-inspired Artificial synapse for neuromorphic computing based on NiO nanoparticle thin film
  Abstract The unprecedented need for data processing in the modern technological era has created opportunities in neuromorphic devices and computation. This is primarily due to the extensive parallel processing done in our human brain. Data processing and logic…
  preprints Keval Hadiyal, Ramakrishnan Ganesan, A. Rastogi, R. Thamankar 2023 置信度 0.74
• A low-power vertical dual-gate neurotransistor with short-term memory for high energy-efficient neuromorphic computing
  Abstract Neuromorphic computing aims to emulate the computing processes of the brain by replicating the functions of biological neural networks using electronic counterparts. One promising approach is dendritic computing, which takes inspiration from the multi…
  preprints Han Xu, Qing Luo, Junjie An, Yue Li 等 2023 置信度 0.74
• A Large-Dynamic-Range Violet Phosphorus Heterostructure Optoelectronic Synapse for High-Complexity Neuromorphic Computing
  preprints 2023 置信度 0.74
• Synthetic neuromorphic computing in living cells
  preprints 2021 置信度 0.74
• Replicating the Bright-Light Therapy of Seasonal Affective Disorder through Dual-Gate Dielectric Synaptic Transistors: An Exploration of Neuromorphic Computing Approaches
  preprints 2023 置信度 0.74
• Multi-State MRAM Cells For Hardware Neuromorphic Computing
  preprints 2021 置信度 0.74
• Shape-Dependent Multi-Weight Magnetic Artificial Synapses for Neuromorphic Computing
  Abstract In neuromorphic computing, artificial synapses provide a multi-weight conductance state that is set based on inputs from neurons, analogous to the brain. Additional properties of the synapse beyond multiple weights can be needed, and can depend on the…
  preprints Thomas Leonard, Sam Liu, Mahshid Alamdar, Can Cui 等 2022 置信度 0.74
• 2D  Metal-Organic Frameworks Based Optoelectronic Neuromorphic Transistors for Human  Emotion-Simulation and Neuromorphic Computing
  preprints 2022 置信度 0.74
• Thermally-stable threshold selector based on CuAg alloy for energy-efficient memory and neuromorphic computing applications
  preprints 2022 置信度 0.74
• Supporting Information for "2D  Metal-Organic Frameworks Based Optoelectronic Neuromorphic Transistors for Human  Emotion-Simulation and Neuromorphic Computing"    
  preprints 2022 置信度 0.74
• Markov Chain Abstractions of Electrochemical Reaction-Diffusion in Synaptic Transmission for Neuromorphic Computing
  preprints 2020 置信度 0.74
• Low-latency neuromorphic closed-loop control of hippocampal ripples <i>in vivo</i>
  Real-time closed-loop neuromodulation, in which stimulation is precisely timed to ongoing brain dynamics, holds transformative potential for treating neurological disorders and probing neural circuit function. However, it requires low-latency, energy-efficient…
  europepmc 2026 置信度 0.80
• MAFA: Bio-Inspired Physics-Driven Activation Layers for Stateful In-Memory Computing
  europepmc 2026 置信度 0.80
• Nanofluidic memristor with an ultra-low operating voltage
  europepmc 2026 置信度 0.80
• Neuromorphic Energy-Aware Learning for Adaptive Deep Brain Stimulation
  europepmc 2026 置信度 0.80
• Investigating Volatile Resistive Switching in Organic Gel Electrolyte Memristors
  europepmc 2026 置信度 0.80
• Dual-Mode Deep-Ultraviolet Photodetection and neuromorphic vision sensor via Thermal Engineering of Oxygen Vacancies in Ga2O3
  Abstract The integration of neuromorphic vision sensors and photodetectors has attracted considerable interest. Here, a facile single-step thermal oxidation strategy is employed to fabricate Ga 2 O 3 thin films, realizing dual functionalities within a single m…
  europepmc Yanqiang Cao 2026 置信度 0.80
• Neuromorphic Satellite Intelligence: A Formal Framework for Event-Driven Architectures, Spike-Based Algorithms, and Quantitative Energy-Accuracy Trade-offs
  Abstract Satellite onboard computing faces an irreducible tension: mission intelligence requirements grow monotonically while power, mass, and radiation budgets remain fixed. This paper advances the State of the art on three fronts. First, we develop a formal …
  europepmc Suresh Kumar TP, Vikas Agnihotri 2026 置信度 0.80
• Spintronic Neuromorphic Hardware Using Domain Wall Based Neurons and Quantized Synapses
  Abstract In this work, we simulate the functionality of artificial neuron and synapse using spin-orbit torque-based spintronic devices and implemented a fully connected artificial neural netwrok (ANN). These neuro-synaptic devices are emulated using transverse…
  europepmc Sakshi Kiran Bandekar, Arnab Ganguly, Debanjan Polley, Debasis Das 2026 置信度 0.80
• Reconfigurable Multistate MRAM Synapses with Vortex STNO based Neurons for Scalable In-Memory Convolutional Neural Networks
  europepmc 2026 置信度 0.80
• Predictive tactile coding in a memristive neuromorphic tactile system
  Abstract Flexible tactile electronics have progressed rapidly in wearable electronics, electronic skin, tactile sensing materials and neuromorphic sensory devices, yet most artificial touch systems still interpret contact only after the signal has already been…
  europepmc 2026 置信度 0.80
• Intrinsic Neuromorphic Behaviors in PEDOT/PSS Nanoscale Networks and their Enhancement via Ethylene Glycol Doping
  europepmc 2026 置信度 0.80
• Data-In-situ Computing with One-Pixel-Multiple-Memristor Architecture for Neuromorphic Sequential Vision
  Abstract Neuromorphic vision systems based on memristors offer an energy-efficient approach to artificial vision, yet traditional pixel(s)-to-one-memristor architectures remain inefficient in dynamic image processing due to limited temporary storage. Here, ins…
  preprints Wei Wang, Yi Sun, Peiwen Tong, Jiangrong Shen 等 2026 置信度 0.74
• uSense: Unary-Computing-based Stochastic Edge Neuromorphic Sensing
  preprints 2026 置信度 0.74
• Inductor-Stabilized Charge-Controlled Memristor Neuromorphic Circuit Design With Complex Firing Dynamics
  Abstract Neuromorphic circuits based on memristive devices have attracted increasing attention for their potential to emulate biological neuronal dynamics and enable energy-efficient brain-inspired computing. In this paper, an inductor-stabilized charge-contro…
  preprints 2026 置信度 0.74
• Physical Mechanisms and Applications of High-Durability Polymer- Based Artificial Synapses Using P3DT
  europepmc 2026 置信度 0.80
• Nanostructured Zirconia thin films as neurogliomorphic interface for neural cells of central and peripheral nervous system
  preprints 2026 置信度 0.74
• Guide to Spintronic Crossbar Arrays: From Binary Switches to Analog Computing
  preprints 2026 置信度 0.74
• Fabrication of Stochastic Ni@PVP Nanowire Networks for Memristive Platforms
  preprints 2026 置信度 0.74
• A Synchronization-Driven Learning Rule for Pattern Separation in Self-Organizing Probabilistic Spiking Neural Networks
  Abstract Neuroscience-inspired neural networks provide a promising framework for bridging biological principles and adaptive artificial intelligence systems. Here, we propose a novel synchronization-based synaptic learning rule for self-organizing probabilisti…
  europepmc 2026 置信度 0.80
• Universal RKKY-like Interactions Between Tilted Skyrmions in Chiral Magnets
  preprints 2026 置信度 0.74
• Hardware implementation of photonic neuromorphic autonomous navigation
  preprints 2026 置信度 0.74
• A Closer-to-Brain Heterosynaptic Learning Rule for Spatiotemporal Spike Pattern Detection with Low-Resolution Synapse
  The brain is believed to process information efficiently in a different manner from deep learning-based artificial intelligence (AI). Brain-like next-generation AI is gaining attention owing to its potential to perform human-like, highly adaptive, robust, and …
  preprints 2026 置信度 0.74
• Self-Contrastive Single-Forward Learning for Efficient Forward-Forward Unsupervised Representation Learning
  preprints 2026 置信度 0.74
• DelRec: learning delays in recurrent spiking neural networks
  Abstract Biological neurons transmit information with stereotyped electrical impulses called ``spikes'', sensitive to coincident timings. Spiking Neural Networks (SNNs), introduced in the nineties, have gained popularity in AI for their energy efficiency and c…
  preprints Alexandre Queant, Ulysse Rancon, Benoit COTTEREAU, Timothée Masquelier 2026 置信度 0.74
• Linking Device Dynamics to Neural Network Performance in Ionically Gated Synaptic Transistors
  preprints 2026 置信度 0.74
• Spatiotemporal Ferro-Ionic Dynamics in Van der Waals Ferroelectrics
  preprints 2026 置信度 0.74
• SE-SNN: Squeeze-and-Excitation Enhanced Spiking Neural Networks with Learnable Neuron Dynamics for Event-Based Vision
  Spiking Neural Networks (SNNs) have emerged as a promising paradigm for energy-efficient neuromorphic computing, particularly when processing asynchronous event streams from dynamic vision sensors (DVS). However, SNNs often suffer from limited representational…
  preprints 2026 置信度 0.74
• Critical Review of Neural Network Generations and Models Design
  europepmc 2026 置信度 0.80
• Ionic Driven Waveguide Integrated Memristor
  europepmc 2026 置信度 0.80
• Information Abstraction for Data Transmission Networks based on Large Language Models
  Abstract Biological systems, particularly the human brain, achieve remarkable energy efficiency by abstracting information across multiple hierarchical levels. In contrast, modern artificial intelligence and communication systems often consume significant ener…
  preprints 2026 置信度 0.74
• Evolutionarily Optimized Network Topology as a Structural Prior for Data-Efficient Sparse Neural Classification
  Biological neural systems have been refined over millions of years of evolutionary optimization to maximize information processing under metabolic and developmental constraints, yielding network topologies with characteristic structural signatures: sparse conn…
  preprints 2026 置信度 0.74
• Electric field switching of chiral phonons
  preprints 2026 置信度 0.74
• High Storage and Energy Efficient Memory for Cryogenic Computing
  preprints 2023 置信度 0.74
• Signal Filtering Using Neuromorphic Measurements
  preprints 2023 置信度 0.74
• Emergent nonlinear modes in coherent magnon circuits detected at ultrahigh frequency resolution
  preprints 2023 置信度 0.74
• Neuromorphic Dendritic Computation with Silent Synapses for Visual Motion Perception
  preprints 2023 置信度 0.74
• The neuromorphic Mosaic: in-memory computing and routing for small-world graphical networks
  preprints 2023 置信度 0.74
• Ultrafast neuromorphic computing driven by polariton nonlinearities
  Abstract Neuromorphic computing offers a promising approach to artificial intelligence by mimicking biological neural networks to perform complex tasks efficiently. While software-based simulations have demonstrated the potential of neuromorphic architectures,…
  crossref Yusong Gan, Ying Shi, Sanjib Ghosh, Haiyun Liu 等 2025-06-01T19:04:03Z 置信度 0.70
• 1026 Light-matter interaction: photodetectors, solar cells, LEDs, lasers, and meta-structures
  crossref 2026-07-06T19:15:47Z 置信度 0.70
• Electrode‐Engineered Dual‐Mode Multifunctional Lead‐Free Perovskite Optoelectronic Memristors for Neuromorphic Computing
  ABSTRACT Memristive devices based on halide perovskites hold strong promise to provide energy‐efficient systems for the Internet of Things (IoT); however, lead (Pb) element should be minimized or ideally replaced. Herein, we introduce a multifunctional device …
  crossref Michalis Loizos, Konstantinos Rogdakis, Konstantinos Chatzimanolis, Katerina Anagnostou 等 2026-01-26T09:02:36Z 置信度 0.70
• Distributed Power Distribution Management in AC Microgrids Using Game Theoretical Approach
  crossref Leping Sun, Weidong Chen, Xiaoxuan Guo, Shuai Han 等 2024-03-19T18:09:52Z 置信度 0.70
• Neuromorphic Near-Sensor Computing: From Event-Based Sensing to Edge Learning
  crossref Ali Safa, Jonah Van Assche, Mark Daniel Alea, Francky Catthoor 等 2022-08-04T20:34:37Z 置信度 0.70
• Finite-Level Quantized Iterative Learning Control for a Class of Fuzzy Cellular Neural Networks Based on Encoding-Decoding Mechanism
  crossref Yuhan Yang, Dan Ma, Wenjun Xiong, Xichen Li 2024-03-19T18:09:52Z 置信度 0.70
• Reconfigurable Cascaded Thermal Neuristors for Neuromorphic Computing (Adv. Mater. 6/2024)
  crossref Erbin Qiu, Yuan‐Hang Zhang, Massimiliano Di Ventra, Ivan K. Schuller 2024-02-08T03:50:42Z 置信度 0.70
• Advances in photonic neuromorphic computing (Conference Presentation)
  crossref Volker J. Sorger, Jonathan K. George, Armin Mehrabian, Bhavin Shastri 等 2019-03-04T16:56:12Z 置信度 0.70
• Intelligent machines work in unstructured environments by differential neuromorphic computing
  Abstract Efficient operation of intelligent machines in the real world requires methods that allow them to understand and predict the uncertainties presented by the unstructured environments with good accuracy, scalability and generalization, similar to humans…
  preprints Luigi Occhipinti, Shengbo Wang, Shuo Gao, Chenyu Tang 等 2023 置信度 0.74
• Continuous adaptive nonlinear model predictive control using spiking neural networks and real-time learning
  Abstract Model predictive control (MPC) is a prominent control paradigm providing accurate state prediction and subsequent control actions for intricate dynamical systems with applications ranging from autonomous driving to star tracking. However, there is an …
  crossref Raz Halaly, Elishai Ezra Tsur 2024-04-23T22:25:55Z 置信度 0.70