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• Extension of neuron machine neurocomputing architecture for spiking neural networks
  crossref Jerry B. Ahn 2014-01-10T15:08:44Z 置信度 0.70
• Training recurrent spiking neural networks in strong coupling regime
  Abstract Recurrent neural networks trained to perform complex tasks can provide insights into the dynamic mechanism that underlies computations performed by cortical circuits. However, due to a large number of unconstrained synaptic connections, the recurrent …
  crossref Christopher M. Kim, Carson C. Chow 2020-06-29T19:15:16Z 置信度 0.70
• Spiking Neural Networks for Mental Workload Classification with a Multimodal Approach
  crossref Jiahui An, Sara Irina Fabrikant, Giacomo Indiveri, Elisa Donati 2025-09-30T17:36:59Z 置信度 0.70
• Adaptive LIF Spiking Neural Networks for Satellite Anomaly Detection
  crossref Andrea La Gala, Mattia Tambaro, Lorenzo Stevenazzi, Gianluca Furano 等 2025-12-09T18:31:34Z 置信度 0.70
• Coding properties of spiking neurons: reverse and cross-correlations
  crossref Wulfram Gerstner 2002-10-14T18:58:33Z 置信度 0.70
• Decision letter for "Spiking neural networks compensate weight drift in organic neuromorphic device networks"
  crossref 2023-04-18T17:03:24Z 置信度 0.70
• An Exploration of Linear Classifiers for Unsupervised Spiking Neural Networks with Event-Driven Data
  crossref Wesley Chavez 2018-09-20T13:33:09Z 置信度 0.70
• Decision letter for "Spiking neural networks compensate weight drift in organic neuromorphic device networks"
  crossref 2023-04-18T17:03:24Z 置信度 0.70
• Efficient Spiking Neural Networks with Biologically Similar Lithium-Ion Memristor Neurons
  crossref 2024-03-05T10:00:40Z 置信度 0.70
• A Sophisticated Iterative Weighted Feature Selection (IWFS) Based Spiking Imperialist Competitive Recurrent Neural Network (SICRNN) Classification Model for Credit Card Fraud Detection
  crossref S. Sobana, V. Diana Earshia, R. Suganthi, K. Ayyappa Swamy 2025-02-26T11:58:33Z 置信度 0.70
• A Novel Approach for Target Attraction and Obstacle Avoidance of a Mobile Robot in Unknown Environments Using a Customized Spiking Neural Network
  In recent years, implementing reinforcement learning in autonomous mobile robots (AMRs) has become challenging. Traditional methods face complex trials, long convergence times, and high computational requirements. This paper introduces an innovative strategy u…
  crossref Brwa Abdulrahman Abubaker, Jafar Razmara, Jaber Karimpour 2023-12-11T06:56:00Z 置信度 0.70
• Epileptic Seizure Classification Using Spiking Neural Network from EEG Signals
  crossref Irshed Hussain, Dalton Meitei Thounaojam 2022-04-03T09:02:40Z 置信度 0.70
• LKSVC: A Novel VANET Caching Method by Integrating Location-Based K-Means Clustering into Spiking Neural Network
  crossref Yuanchen Li, Lin Guan, Ziyang Zhang, George Vogiatzis 2025-04-28T02:22:36Z 置信度 0.70
• An Augmented OxRAM Synapse for Spiking Neural Network (SNN) Circuits
  crossref H. Aziza, H. Bazzi, J. Postel-Pellerin, P. Canet 等 2019-06-13T22:34:52Z 置信度 0.70
• Automatic Bird Species Recognition Based on Spiking Neural Network
  crossref Ricky Mohanty, Bandi Kumar Mallik, Sandeep Singh Solanki 2020-04-01T17:03:07Z 置信度 0.70
• A progressive surrogate gradient learning for memristive spiking neural network
  In recent years, spiking neural networks (SNNs) have received increasing attention of research in the field of artificial intelligence due to their high biological plausibility, low energy consumption, and abundant spatio-temporal information. However, the non…
  crossref Shu Wang, Tao Chen, Yu Gong, Fan Sun 等 2023-02-08T07:26:01Z 置信度 0.70
• DA-LIF: Dual Adaptive Leaky Integrate-and-Fire Model for Deep Spiking Neural Networks
  crossref Tianqing Zhang, Kairong Yu, Jian Zhang, Hongwei Wang 2025-03-12T13:52:43Z 置信度 0.70
• FIST: A Framework to Interleave Spiking Neural Networks on CGRAs
  crossref Tuan Ngyen, Syed M.A.H. Jafri, Masoud Daneshtalab, Ahmed Hemani 等 2015-04-24T21:13:52Z 置信度 0.70
• Bayesian Optimization of Spiking Neural Network Parameters to Solving the Time Series Classification Task
  crossref Alexey Chernyshev 2016-03-30T03:25:57Z 置信度 0.70
• HypoxSpike: Ternary Spiking Neural Network for Opioid Overdose Detection
  Opioid overdose is a growing global health crisis that claims more than 120,000 lives annually, of which more than half use opioids alone, without access to bystander intervention. Fatal overdose events are marked by motionlessness, respiratory depression, and…
  crossref Anush Lingamoorthy, Abhishek Kumar Mishra, Olumuyiwa Oni, Jacob S Brenner 等 2026-03-18T07:05:47Z 置信度 0.70
• Spiking Neural Network with RRAM: Can We Use It for Real-World Application?
  crossref Tianqi Tang, Lixue Xia, Boxun Li, Rong Luo 等 2015-05-02T04:17:53Z 置信度 0.70
• Spike representation of depth image sequences and its application to hand gesture recognition with spiking neural network
  crossref Daisuke Miki, Kento Kamitsuma, Taiga Matsunaga 2023-04-24T11:02:35Z 置信度 0.70
• Natural Language to Verilog: Design of a Recurrent Spiking Neural Network using Large Language Models and ChatGPT
  crossref Paola Vitolo, George Psaltakis, Michael Tomlinson, Gian Domenico Licciardo 等 2024-12-02T13:37:03Z 置信度 0.70
• Statement of Retraction
  crossref 2024-07-31T10:24:07Z 置信度 0.70
• Statement of Retraction
  crossref 2024-08-03T07:04:47Z 置信度 0.70
• MF-DSNN:An Energy-efficient High-performance Multiplication-free Deep Spiking Neural Network Accelerator
  crossref Yue Zhang, Shuai Wang, Yi Kang 2023-07-07T18:24:30Z 置信度 0.70
• Spiking Neural Network Linear Equalization: Experimental Demonstration of 2km 100Gb/s IM/DD PAM4 Optical Transmission
  crossref Georg Böcherer, Florian Strasser, Elias Arnold, Youxi Lin 等 2023-05-19T17:26:19Z 置信度 0.70
• Spiking Neural Network Based Classification of Task-Evoked EEG Signals
  crossref Piyush Goel, Honghai Liu, David J. Brown, Avijit Datta 2006-10-09T13:29:42Z 置信度 0.70
• Study of the Influence of Macroparameters of a Spiking Neural Network on the Quality of Image Recognition
  crossref Sergey V. Stasenko, Andrey A. Lebedev, Tatiana A. Levanova, Victor B. Kazantsev 2024-10-09T17:45:45Z 置信度 0.70
• A novel enhanced spiking sheaf attention neural network for real-time health monitoring based on internet of things
  crossref P. Chinnaraj, Deepak Chandra Uprety, Sandeep Raj, Lakshmana Phaneendra Maguluri 2026-03-07T06:55:33Z 置信度 0.70
• WITHDRAWN: Time Series Analysis of Volleyball Spiking Posture Based on Quality-Guided Cyclic Neural Network
  crossref Chuanchang Zhang, Huan Tang, Zhigang Duan 2019-10-13T01:22:29Z 置信度 0.70
• Traffic Scheduling based on Spiking Neural Network in Hybrid E/O Switching Intra-Datacenter Networks
  crossref Ao Yu, Hui Yang, Qiuyan Yao, Kaixuan Zhan 等 2020-07-27T22:26:45Z 置信度 0.70
• Event-Based Hough Transform in a Spiking Neural Network for Multiple Line Detection and Tracking Using a Dynamic Vision Sensor
  crossref Sajjad Seifozzakerini, Wei-Yun Yau, Bo Zhao, Kezhi Mao 2017-05-29T04:11:16Z 置信度 0.70
• Effects of Multi-clustered Structure on the Enhancement of Reservoir Computing of Spiking Neural Network
  crossref Fangzheng Xue, Anguo Zhang, Xiumin Li 2016-01-29T09:31:07Z 置信度 0.70
• Neurocomputer architecture based on spiking neural network and its optoelectronic implementation
  crossref Oleh K. Kolesnytskyj, Vladislav V. Kutsman, Krzysztof Skorupski, Mukaddas Arshidinova 2019-11-06T21:53:00Z 置信度 0.70
• Background
  crossref Muhammad Arsalan 2024-09-01T06:02:42Z 置信度 0.70
• Spatiotemporal Decoupled Learning for Spiking Neural Networks_supp1-3671461.pdf
  crossref Jibin Wu 2026-03-16T20:16:06Z 置信度 0.70
• Flyintel – a Platform for Robot Navigation based on a Brain-Inspired Spiking Neural Network
  crossref Yao Huang-Yu, Hsuan-Pei Huang, Yu-Chi Huang, Chung-Chuan Lo 2019-07-25T19:57:53Z 置信度 0.70
• Memristor-Spikelearn: A Spiking Neural Network Simulator for Studying Synaptic Plasticity under Realistic Device and Circuit Behaviors
  crossref Yuming Liu, Angel Yanguas-Gil, Sandeep Madireddy, Yanjing Li 2023-06-02T19:32:57Z 置信度 0.70
• XNOR-BSNN: In-Memory Computing Model for Deep Binarized Spiking Neural Network
  crossref Van-Tinh Nguyen, Quang-Kien Trinh, Renyuan Zhang, Yasuhiko Nakashima 2022-01-03T15:17:48Z 置信度 0.70
• Spiking neural network reinforcement learning method based on temporal coding and STDP
  crossref Alexander Sboev, Danila Vlasov, Roman Rybka, Alexey Serenko 2018-12-11T07:40:11Z 置信度 0.70
• OneSpike: Ultra-low latency spiking neural networks
  crossref Kaiwen Tang, Zhanglu Yan, Weng-Fai Wong 2024-09-09T17:35:05Z 置信度 0.70
• Fast Sigmoidal Networks via Spiking Neurons
  We show that networks of relatively realistic mathematical models for biological neurons in principle can simulate arbitrary feedforward sigmoidal neural nets in a way that has previously not been considered. This new approach is based on temporal coding by si…
  crossref Wolfgang Maass 2011-02-24T01:43:19Z 置信度 0.70
• Introduction
  crossref Muhammad Arsalan 2024-09-01T06:02:42Z 置信度 0.70
• Analysis of Learning Mechanisms in Spiking Neural Networks with R(t) Elements and Memristive Synapses
  As Moore's law ends, the conventional von Neumann computer architecture with binary-coded data representation has reached its bottleneck because of having separate computing and memory modules. In this architecture, continuous power is required due to sequenti…
  crossref Farhana Afrin 2025-09-11T19:57:47Z 置信度 0.70
• Mutual Lateral Prediction for Locally Trained Spiking Neural Networks
  Abstract Spiking neural networks (SNNs) offer low-energy inference on neuromorphic hardware, but the most accurate SNNs are trained with backpropagation through time, which requires error signals that neuromorphic chips cannot broadcast and that have no biolog…
  crossref Nitesh Kamanuru Purushotham, Pranav Kulkarni 2026-08-19T12:52:28Z 置信度 0.70
• Optimized Resource Management Using Binarized Spiking Neural Network With Pyramid Attention and Smart Contract Blockchain for Sustainable Spectrum Allocation in 6G
  ABSTRACT The rapid expansion of connected devices and the need for high‐speed communication make sustainable spectrum allocation and resource management crucial issues in 6G networks. Traditional spectrum management methods often rely on static or centralized …
  crossref S. K. Jameer Basha, Singamaneni Krishnapriya, G. Kirubasri, Gunjan Varshney 等 2025-07-31T05:45:00Z 置信度 0.70
• SparseProp: Efficient Event-Based Simulation and Training of Sparse Recurrent Spiking Neural Networks
  crossref Rainer Engelken 2026-03-02T13:18:04Z 置信度 0.70
• Deep Phasor Networks: Connecting Conventional and Spiking Neural Networks
  crossref Wilkie Olin-Ammentorp, Maxim Bazhenov 2022-09-30T19:56:04Z 置信度 0.70
• Review for "Energy-aware spike budgeting for continual learning in spiking neural networks for neuromorphic vision"
  crossref 2026-07-03T23:27:36Z 置信度 0.70
• Application of Neural Network Algorithm in Network Engineering Design
  crossref Min Yang, Jiajie Zhang 2025-09-23T10:51:18Z 置信度 0.70
• A Methodology to Study the Impact of Spiking Neural Network Parameters Considering Event-Based Automotive Data
  crossref Iqra Bano, Rachmad Vidya Wicaksana Putra, Alberto Marchisio, Muhammad Shafique 2025-01-09T19:36:27Z 置信度 0.70
• A biologically-inspired locally-connected spiking network for efficient and robust ground reaction force estimation in a legged robot
  crossref Paolo Arena, Maria Francesca Pia Cusimano, Luca Patané, Poramate Manoonpong 2023-08-02T13:30:03Z 置信度 0.70
• <i>S</i> <sup>3</sup>Net: a Synthesis-Segmentation-Spiking Network for Alzheimer's disease detection and segmentation.
  europepmc 2026 置信度 0.80
• Synergistic Short-Term Synaptic Plasticity Mechanisms for Working Memory.
  Working memory (WM) is essential for almost every cognitive task. The neural and synaptic mechanisms supporting the rapid encoding and maintenance of memories in diverse tasks are the subject of an ongoing debate. The traditional view of WM as stationary persi…
  europepmc 2026 置信度 0.80
• Functional implications of atypical action potential generation in the (patho)physiological brain: from developmental program to glioma.
  europepmc 2026 置信度 0.80
• Quantum-enhanced spiking intelligence framework for real-time anomaly detection in industrial internet of things.
  europepmc 2026 置信度 0.80
• Spark: modular spiking neural networks.
  europepmc 2026 置信度 0.80
• A mean-field model of neural networks with PV and SOM interneurons reveals connectivity-based mechanisms of gamma oscillations.
  europepmc 2026 置信度 0.80
• Structure-Engineered Nanoporous Vanadium Oxide Memristors for Reconfigurable Synapse-Neuron Integration and Synergistic Robotic Motion.
  europepmc 2026 置信度 0.80
• Topology-aware design of spiking neural networks via modular graph architectures.
  Spiking Neural Networks (SNNs) offer a biologically plausible and energy-efficient alternative to traditional artificial neural networks (ANNs), yet their design remains constrained by limited architectural flexibility and slow training dynamics. In this work,…
  europepmc Farideh Motaghian, Soheila Nazari, Juan P. Dominguez-Morales, Reza Jafari 2026 置信度 0.80
• Tabletop Testbed for Low-Power Metamaterial Field Manipulation: A YIG Based Prototype with Retrocausal Control
  This paper presents a fully buildable tabletop-scale testbed for investigating low-power spacetime eld manipulation using a ceramic-YIG (yttrium iron garnet) metamaterial hull integrated with neuromorphic control architecture. The design combines hexagonal YIG…
  datacite Barker, Christian 2025 置信度 0.66
• International Conference on New Interfaces for Musical Expression NIME2025 Sessions
  This repository contains video of all sessions from NIME2025 that were streamed during the conference. This includes paper sessions, remote poster videos, concerts, keynotes and town hall plenary. NIME2025 took place at The Australian National University, Ngun…
  datacite Martin, Charles 2025 置信度 0.66
• International Conference on New Interfaces for Musical Expression NIME2025 Sessions
  This repository contains video of all sessions from NIME2025 that were streamed during the conference. This includes paper sessions, remote poster videos, concerts, keynotes and town hall plenary. NIME2025 took place at The Australian National University, Ngun…
  datacite Martin, Charles 2025 置信度 0.66
• Neural network modelling of the primate ventral visual pathway
  The aim of this doctoral research is to advance understanding of how the primate brain learns to process the detailed spatial form of natural visual scenes. Neurons in successive stages of the primate ventral visual pathway encode the spatial structure of visu…
  datacite Eguchi, Akihiro 2017 置信度 0.66
• CogniSNN: An Exploration to Random Graph Architecture based Spiking Neural Networks with Enhanced Depth-Scalability and Path-Plasticity
  Currently, most spiking neural networks (SNNs) still mimic the chain-like hierarchical architecture in traditional artificial neural networks (ANNs). This method significantly differs from random connections between neurons found in biological brains, limiting…
  datacite Huang, Yongsheng, Duan, Peibo, Liu, Zhipeng, Sun, Kai 等 2025 置信度 0.66 Neural and Evolutionary Computing (cs.NE)FOS: Computer and information sciencesFOS: Computer and information sciences
• SYNtzulA: Open-Source Hardware for Energy-Efficient Spiking Neural Network Inference
  Spiking Neural Networks (SNNs) represent a promising class of neural networks that emulate the behavior of biological neurons,offering significant advantages in terms of energy efficiency and computational power. These networks achieve optimal performance on n…
  datacite Martis, Luca, Leone, Gianluca, Raffo, Luigi, MELONI, PAOLO 2025 置信度 0.66
• SYNtzulA: Open-Source Hardware for Energy-Efficient Spiking Neural Network Inference
  Spiking Neural Networks (SNNs) represent a promising class of neural networks that emulate the behavior of biological neurons,offering significant advantages in terms of energy efficiency and computational power. These networks achieve optimal performance on n…
  datacite Martis, Luca, Leone, Gianluca, Raffo, Luigi, MELONI, PAOLO 2025 置信度 0.66
• SYNtzulu, SNN at the Micro-Edge: The Evolution of the Mosquito.
  SYNtzulu is an ultra-low power Spiking Neural Network inference engine designed for near-sensor processing at the edge. We describe the architectural progression that enables Syntzulu to support online artificial intelligence data analysis locally on a range o…
  datacite Leone, Gianluca 2025 置信度 0.66
• The CollectiveOS Architecture: A Unified Standard for Lawful Intelligence, Metabolic Computing, and Neuro-Homeostasis (v1.0)
  The CollectiveOS Architecture: A Unified Standard for Lawful Intelligence, Metabolic Computing, and Neuro-Homeostasis (v1.0) Executive Summary The early twenty-first century has been dominated by a singular, pervasive paradigm in artificial intelligence and ci…
  datacite Brewer, Mark Anthony 2025 置信度 0.66
• The CollectiveOS Architecture: A Unified Standard for Lawful Intelligence, Metabolic Computing, and Neuro-Homeostasis (v1.0)
  The CollectiveOS Architecture: A Unified Standard for Lawful Intelligence, Metabolic Computing, and Neuro-Homeostasis (v1.0) Executive Summary The early twenty-first century has been dominated by a singular, pervasive paradigm in artificial intelligence and ci…
  datacite Brewer, Mark Anthony 2025 置信度 0.66
• Closed-loop coupling of both physiological spindle model and spinal pathways for sensorimotor control of human center-out reaching
  The development of new studies that consider different structures of the hierarchical sensorimotor control system is essential to enable a more holistic understanding about movement. The incorporation of more biological proprioceptive and neuronal circuit mode…
  datacite Chacon, Pablo Filipe Santana, Wochner, Isabell, Hammer, Maria, Eppler, Jochen Martin 等 2025 置信度 0.66 570
• Rockpool Documentation
  Rockpool is a Python machine-learning package for designing, building and deploying event-driven neural network applications, particularly for Neuromorphic computing hardware. Rockpool provides a simple and comfortable API for working with spiking neural netwo…
  datacite Muir, Dylan, Bauer, Felix, Weidel, Philipp 2025 置信度 0.66 machine learningspiking neural networkspythonopen sourcepytorch
• Rockpool Documentation
  Rockpool is a Python machine-learning package for designing, building and deploying event-driven neural network applications, particularly for Neuromorphic computing hardware. Rockpool provides a simple and comfortable API for working with spiking neural netwo…
  datacite Muir, Dylan, Bauer, Felix, Weidel, Philipp 2025 置信度 0.66 machine learningspiking neural networkspythonopen sourcepytorch
• Neuro-Dimensional Architecture of Brain Waves: A Unified Theoretical Framework for Macroscopic Neural Dynamics
  We propose a novel theoretical synthesis, the theory of Neuro-Dimensional Ar- chitecture (NDA), which reframes canonical brain wave activity (Delta, Theta, Al- pha, Beta, Gamma) as emergent, low-dimensional projections of a brain navigating a high-dimensional,…
  datacite Ashfaq, Muhammad Bilal 2025 置信度 0.66 Brain WavesNeural oscillatorEEGManifoldConnectome
• Neuro-Dimensional Architecture of Brain Waves: A Unified Theoretical Framework for Macroscopic Neural Dynamics
  We propose a novel theoretical synthesis, the theory of Neuro-Dimensional Ar- chitecture (NDA), which reframes canonical brain wave activity (Delta, Theta, Al- pha, Beta, Gamma) as emergent, low-dimensional projections of a brain navigating a high-dimensional,…
  datacite Ashfaq, Muhammad Bilal 2025 置信度 0.66 Brain WavesNeural oscillatorEEGManifoldConnectome
• LightSNN: Lightweight Architecture Search for Sparse and Accurate Spiking Neural Networks
  Spiking Neural Networks (SNNs) are highly regarded for their energy efficiency, inherent activation sparsity, and suitability for real-time processing in edge devices. However, most current SNN methods adopt architectures resembling traditional artificial neur…
  datacite Abdennadher, Yesmine, Perin, Giovanni, Mazzieri, Riccardo, Pegoraro, Jacopo 等 2025 置信度 0.66 Neural and Evolutionary Computing (cs.NE)Artificial Intelligence (cs.AI)Signal Processing (eess.SP)FOS: Computer and information sciencesFOS: Computer and information sciences
• Model data for: Task success in trained spiking neural network models coincides with emergence of cross-stimulus-modulated inhibition
  Zip files of a sample experiment in each major experimental category are listed below. base.zip: baseline model (single readout unit), dual-training (task and rate) rate.zip: baseline model, rate-only training remove_ee.zip: baseline model without recurrent e-…
  datacite Zhu, Yuqing 2025 置信度 0.66
• Model data for: Task success in trained spiking neural network models coincides with emergence of cross-stimulus-modulated inhibition
  Zip files of a sample experiment in each major experimental category are listed below. base.zip: baseline model (single readout unit), dual-training (task and rate) rate.zip: baseline model, rate-only training remove_ee.zip: baseline model without recurrent e-…
  datacite Zhu, Yuqing 2025 置信度 0.66
• Routing Spiking Neural Networks onto Field Programmable Spiking Neuron Array
  This thesis presents the routing of small-world spiking neural networks(SNN) onto a neuromorphic hardware platform known as FPSNA, a field-programmable spiking neuron array featuring a 32×32 grid architecture. The primary objectives are to optimize routing tim…
  datacite Bhat, Achaladi Manoj, :unav 2025 置信度 0.66
• CogniSNN: Enabling Neuron-Expandability, Pathway-Reusability, and Dynamic-Configurability with Random Graph Architectures in Spiking Neural Networks
  Spiking neural networks (SNNs), regarded as the third generation of artificial neural networks, are expected to bridge the gap between artificial intelligence and computational neuroscience. However, most mainstream SNN research directly adopts the rigid, chai…
  datacite Huang, Yongsheng, Duan, Peibo, Wu, Yujie, Sun, Kai 等 2025 置信度 0.66 Neural and Evolutionary Computing (cs.NE)Artificial Intelligence (cs.AI)FOS: Computer and information sciencesFOS: Computer and information sciences
• Savas et al 2025: Leucokinin Drosophila
  This repository contains new synapse detection data (‘Princeton synapses')[https://www.biorxiv.org/content/10.1101/2025.07.11.664377v1] for v783 FAFB FlyWire, structured to be used with the spiking neural network model Brian2 for FlyWire [https://www.nature.co…
  datacite Chang, Zeyu, Zandawala, Meet 2025 置信度 0.66
• Savas et al 2025: Leucokinin Drosophila
  This repository contains new synapse detection data (‘Princeton synapses')[https://www.biorxiv.org/content/10.1101/2025.07.11.664377v1] for v783 FAFB FlyWire, structured to be used with the spiking neural network model Brian2 for FlyWire [https://www.nature.co…
  datacite Chang, Zeyu, Zandawala, Meet 2025 置信度 0.66
• Rosetta Stone of Neural Mass Models
  Brain dynamics dominate every level of neural organization—from single-neuron spiking to the macroscopic waves captured by fMRI, MEG, and EEG—yet the mathematical tools used to interrogate those dynamics remain scattered across a patchwork of traditions. Neura…
  datacite Castaldo, Francesca, de Palma Aristides, Raul, Clusella, Pau, Garcia-Ojalvo, Jordi 等 2025 置信度 0.66
• Rosetta Stone of Neural Mass Models
  Brain dynamics dominate every level of neural organization—from single-neuron spiking to the macroscopic waves captured by fMRI, MEG, and EEG—yet the mathematical tools used to interrogate those dynamics remain scattered across a patchwork of traditions. Neura…
  datacite Castaldo, Francesca, de Palma Aristides, Raul, Clusella, Pau, Garcia-Ojalvo, Jordi 等 2025 置信度 0.66
• Geometric Metabolism: Holographic Reconstruction of Temporal Memory via Superconducting Attractor Dynamics
  Standard Deep Learning models function primarily as statistical filters, often failing to preserve structural integrity when subjected to high-entropy noise (the "Garbage In, Garbage Out" problem). This study demonstrates a novel Chrono-Biological Architecture…
  datacite Jagdev, Hemanth kumar 2025 置信度 0.66 Spiking Neural Networks, Geometric Intelligence, Attractor Dynamics, Chaos Theory, Memory Reconstruction, Holographic Memory, Adversarial Defense, Neuromorphic Computing, STDP, Physics-Informed AI, Temporal Coding, Surface Tension, Superconductivity, Chrono-Bio-Architecture, Geometric MetabolismArtificial Intelligence, Computational Neuroscience, Complex Systems ,Condensed Matter Physics ,Spiking Neural Networks
• Geometric Metabolism: Holographic Reconstruction of Temporal Memory via Superconducting Attractor Dynamics
  Standard Deep Learning models function primarily as statistical filters, often failing to preserve structural integrity when subjected to high-entropy noise (the "Garbage In, Garbage Out" problem). This study demonstrates a novel Chrono-Biological Architecture…
  datacite Jagdev, Hemanth kumar 2025 置信度 0.66 Spiking Neural Networks, Geometric Intelligence, Attractor Dynamics, Chaos Theory, Memory Reconstruction, Holographic Memory, Adversarial Defense, Neuromorphic Computing, STDP, Physics-Informed AI, Temporal Coding, Surface Tension, Superconductivity, Chrono-Bio-Architecture, Geometric MetabolismArtificial Intelligence, Computational Neuroscience, Complex Systems ,Condensed Matter Physics ,Spiking Neural Networks
• Spontaneous synchronization in recurrent neural networks: From mathematical analysis to flexible information processing in spiking networks
  The brain is a highly complex distributed system that not only continuously performs demanding computational tasks but also flexibly adapts its processing to changing requirements on short time scales. A prime example of this flexibility is provided by selecti…
  datacite Schünemann, Maik 2023 置信度 0.66 Neurosciencedynamical systems
• The role of long-range connections in contextual processing and spontaneous activity of primary visual cortex
  The aim of this work is to set the basis for the development of a theoretical framework to investigate how artificial signals can be successfully introduced into primary visual cortex through electrical stimulation. This goal is approached by focusing on two d…
  datacite Capparelli, Federica 2020 置信度 0.66 NeuroscienceVisual ProcessingElectrical Stimulation
• طراحی و ساخت مدل های زبانی بزرگ هوشمند هوش کوانتومی نسل چهاردهم و بدون نیاز به داده های ورودی با تانسور ۱۶۵ بُعدی معادله حمزه.LLM
  LLM هوشمند آگاه تانسور حمزه ۱۶۵D (HQI-165D) نه یک مدل زبان بزرگ (LLM) کلاسیک، بلکه یک ساختار شناختی کوانتومی فوق-هوش عمومی (Post-AGI) است که بر پایه‌های فیزیک کوانتومی پیشرفته و اصول اخلاق آگاهانه بنا شده است. این سیستم، که ما آن را نسل ۱۴ هوش مصنوعی (۱۳ نسل ج…
  datacite JALALI, SEYED RASOUL 2025 置信度 0.66
• طراحی و ساخت مدل های زبانی بزرگ هوشمند هوش کوانتومی نسل چهاردهم و بدون نیاز به داده های ورودی با تانسور ۱۶۵ بُعدی معادله حمزه.LLM
  LLM هوشمند آگاه تانسور حمزه ۱۶۵D (HQI-165D) نه یک مدل زبان بزرگ (LLM) کلاسیک، بلکه یک ساختار شناختی کوانتومی فوق-هوش عمومی (Post-AGI) است که بر پایه‌های فیزیک کوانتومی پیشرفته و اصول اخلاق آگاهانه بنا شده است. این سیستم، که ما آن را نسل ۱۴ هوش مصنوعی (۱۳ نسل ج…
  datacite JALALI, SEYED RASOUL 2025 置信度 0.66
• Noisy Spiking Actor Network for Exploration
  As a general method for exploration in deep reinforcement learning (RL), NoisyNet can produce problem-specific exploration strategies. Spiking neural networks (SNNs), due to their binary firing mechanism, have strong robustness to noise, making it difficult to…
  datacite Chen, Ding, Peng, Peixi, Huang, Tiejun, Tian, Yonghong 2024 置信度 0.66 Machine Learning (cs.LG)Neural and Evolutionary Computing (cs.NE)FOS: Computer and information sciencesFOS: Computer and information sciences
• A Spiking Neural Network Implementation of Gaussian Belief Propagation
  Bayesian inference offers a principled account of information processing in natural agents. However, it remains an open question how neural mechanisms perform their abstract operations. We investigate a hypothesis where a distributed form of Bayesian inference…
  datacite Adamiat, Sepideh, Kouw, Wouter M., de Vries, Bert 2025 置信度 0.66 Neural and Evolutionary Computing (cs.NE)FOS: Computer and information sciencesFOS: Computer and information sciences
• Neuromorphic Processor Employing FPGA Technology with Universal Interconnections
  Neuromorphic computing, inspired by biological neural systems, holds immense promise for ultra-low-power and real-time inference applications. However, limited access to flexible, open-source platforms continues to hinder widespread adoption and experimentatio…
  datacite Harlikar, Pracheta, Badawy, Abdel-Hameed A., Date, Prasanna 2025 置信度 0.66 Hardware Architecture (cs.AR)FOS: Computer and information sciencesFOS: Computer and information sciences
• Assessing Neuromorphic Computing for Fingertip Force Decoding from Electromyography
  High-density surface electromyography (HD-sEMG) provides a noninvasive neural interface for assistive and rehabilitation control, but mapping neural activity to user motor intent remains challenging. We assess a spiking neural network (SNN) as a neuromorphic a…
  datacite Shahrooei, Abolfazl, Arthur, Luke, Patel, Om, Kamper, Derek 2025 置信度 0.66 Machine Learning (cs.LG)Signal Processing (eess.SP)FOS: Computer and information sciencesFOS: Computer and information sciencesFOS: Electrical engineering, electronic engineering, information engineering
• Time to Spike? Understanding the Representational Power of Spiking Neural Networks in Discrete Time
  Recent years have seen significant progress in developing spiking neural networks (SNNs) as a potential solution to the energy challenges posed by conventional artificial neural networks (ANNs). However, our theoretical understanding of SNNs remains relatively…
  datacite Nguyen, Duc Anh, Araya, Ernesto, Fono, Adalbert, Kutyniok, Gitta 2025 置信度 0.66
• Neural Network Models of Cognitive Conflict Paradigms
  In recent years, some areas of cognitive psychology have proposed formal models in the form of computer simulations, using Back-Propagation Artificial Neural Networks (BP-ANNs). Such models represent an improvement in plausibility, and they allow quantitative …
  datacite Luna-Rodriguez, Aquiles 2009 置信度 0.66 Cellular AutomateSpiking Neural NetworkJellyfish Simulation150 Psychologie
• Population Encoding in Artificial and Biological Spiking Neural Systems
  Variability in neural responses to stimuli is a core property of neural systems. In this dissertation, I explore how variability in neural responses can be exploited at the population level, through both temporal and rate coding, to achieve encoding schemes. I…
  datacite Costa, Filippo 2025 置信度 0.66 570 Life sciences; biology
• Synchrony-Gated Plasticity with Dopamine Modulation for Spiking Neural Networks
  While surrogate backpropagation proves useful for training deep spiking neural networks (SNNs), incorporating biologically inspired local signals on a large scale remains challenging. This difficulty stems primarily from the high memory demands of maintaining …
  datacite Tian, Yuchen, Tensingh, Samuel, Eshraghian, Jason, Truong, Nhan Duy 等 2025 置信度 0.66 Neural and Evolutionary Computing (cs.NE)FOS: Computer and information sciencesFOS: Computer and information sciences
• Neuro-Vesicles: Neuromodulation Should Be a Dynamical System, Not a Tensor Decoration
  We introduce Neuro-Vesicles, a framework that augments conventional neural networks with a missing computational layer: a dynamical population of mobile, discrete vesicles that live alongside the network rather than inside its tensors. Each vesicle is a self c…
  datacite Li, Zilin, Xu, Weiwei, Kane, Vicki 2025 置信度 0.66 Neural and Evolutionary Computing (cs.NE)FOS: Computer and information sciencesFOS: Computer and information sciences