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• Memory by a thousand rules: Automated discovery of multi-type plasticity rules reveals variety & degeneracy at the heart of learning
  preprints 2025 置信度 0.74
• Femto-joule threshold reconfigurable all-optical nonlinear activators for picosecond spiking neural networks
  preprints 2025 置信度 0.74
• Spontaneous Dynamics Predict the Effects of Targeted Intervention in Hippocampal Neuronal Cultures
  preprints 2025 置信度 0.74
• Neuromorphic circuit based on the un-supervised learning of biologically inspired spiking neural network for pattern recognition
  crossref Soheila Nazari, Alireza Keyanfar, Marc M. Van Hulle 2022-09-15T18:44:26Z 置信度 0.70
• A spiking neural network model of the midbrain superior colliculus that generates saccadic motor commands
  crossref Bahadir Kasap, A. John van Opstal 2017-05-20T13:18:36Z 置信度 0.70
• Homeostatically Regulated Adaptive Threshold Spiking Neural Networks for Energy-Efficient Inference
  Spiking Neural Networks (SNNs) represent a biologically grounded computational paradigm in which information is carried by discrete spike events, conferring structural compatibility with low-power, event-driven neuromorphic hardware. A persistent impediment to…
  crossref Gripsy Paul Mannickathan, Yeldo K. Varghese, Sahala Mariyam P. S., Nimal K. G. 等 2026-07-28T09:17:11Z 置信度 0.70
• Study of a Multi-modal Neurorobotic Prosthetic Arm Control System based on Recurrent Spiking Neural Network
  The use of robotic arms in various fields of human endeavor has increased over the years, and with recent advancements in artificial intelligence enabled by deep learning, they are increasingly being employed in medical applications like assistive robots for p…
  crossref Mark Ikechukwu Ogbodo, Khanh N. Dang, Abderazek Ben Abdallah 2022-05-13T07:59:15Z 置信度 0.70
• Self-Learning Cascade Spiking Neural Network for Fuzzy Clustering Based on Group Method of Data Handling
  crossref Yevgeniy .V. Bodyanskiy, Elena A. Vynokurova, Artem I. Dolotov 2013-06-07T06:34:14Z 置信度 0.70
• NeuroCoreX: An Open-Source FPGA-Based Spiking Neural Network Emulator with On-Chip Learning
  crossref Ashish Gautam, Prasanna Date, Shruti Kulkarni, Ian Mulet 等 2026-06-22T19:52:43Z 置信度 0.70
• Stochastic and asynchronous spiking dynamic neural fields
  crossref Benoit Chappet de Vangel, Cesar Torres-Huitzil, Bernard Girau 2015-10-01T17:48:02Z 置信度 0.70
• Astrocytes Stabilize Neural Simplices Against Noise in STDP-based Spiking Neural Networks
  crossref Yuliya Tsybina, Susanna Gordleeva 2025-09-30T17:36:47Z 置信度 0.70
• A Supervised Multi-Spike Learning Algorithm for Spiking Neural Networks
  crossref Yu Miao, Huajin Tang, Gang Pan 2018-10-19T22:25:09Z 置信度 0.70
• A critical survey of STDP in Spiking Neural Networks for Pattern Recognition
  crossref Alex Vigneron, Jean Martinet 2020-09-30T00:40:33Z 置信度 0.70
• Spiking Neural Networks: Background, Recent Development and the NeuCube Architecture
  crossref Clarence Tan, Marko Šarlija, Nikola Kasabov 2020-08-13T09:03:47Z 置信度 0.70
• Working memory capacity of spiking neural network model
  crossref Natalia S. Kovaleva, Valery V. Matrosov, Mikhail A. Mishchenko 2022-11-03T22:16:08Z 置信度 0.70
• Spiking Neural Network Based Object Pose Alignment
  crossref Sushant Yadav, Chandarjeet Singh Chundawat, Santosh Chaudhary, Rajesh Kumar 2025-08-31T17:09:32Z 置信度 0.70
• Integrating predictive coding with reservoir computing in spiking neural network model of cultured neurons
  crossref Yoshitaka Ishikawa, Takumi Shinkawa, Takuma Sumi, Hideyuki Kato 等 2024-03-31T22:15:54Z 置信度 0.70
• Global–Local Feature Fusion Network Based on Nonlinear Spiking Neural Convolutional Model for MRI Brain Tumor Segmentation
  Due to the differences in size, shape, and location of brain tumors, brain tumor segmentation differs greatly from that of other organs. The purpose of brain tumor segmentation is to accurately locate and segment tumors from MRI images to assist doctors in dia…
  crossref Junjie Li, Hong Peng, Bing Li, Zhicai Liu 等 2025-04-11T09:40:47Z 置信度 0.70
• Spiking Neural Networks and fMRI-Constrained Spiking Neural Networks for Speech Recognition and Biological Signal Processing: A Comprehensive Review
  crossref Pandula Pallewatta, Samantha Mathara Arachchi, Sanam Rizvan, Kasun Karunanayaka 等 2026-04-13T19:35:30Z 置信度 0.70
• Breast Cancer Recognition Using Saliency‐Based Spiking Neural Network
  The spiking neural networks (SNNs) use event‐driven signals to encode physical information for neural computation. SNN takes the spiking neuron as the basic unit. It modulates the process of nerve cells from receiving stimuli to firing spikes. Therefore, SNN i…
  crossref Qiang Fu, Hongbin Dong 2022-03-24T19:43:26Z 置信度 0.70
• Hardware Aware Spiking Neural Network Training and Its Mixed-Signal Implementation for Non-Volatile In-Memory Computing Accelerators
  crossref Alptekin Vardar, Aamir Munir, Nellie Laleni, Sourav De 等 2024-01-10T19:38:25Z 置信度 0.70
• Spiking Neural Network Based Intrusion Detection Framework for Manet Security Using White Shark Optimization
  crossref R. Ramya, S. Rosaline, K S Kavin, P. Saranya 等 2026-08-21T19:10:05Z 置信度 0.70
• A Sensor Fusion Horse Gait Classification by a Spiking Neural Network on SpiNNaker
  crossref Antonio Rios-Navarro, Juan Pedro Dominguez-Morales, Ricardo Tapiador-Morales, Manuel Dominguez-Morales 等 2016-08-12T15:20:33Z 置信度 0.70
• Computational Effects of Free-Flowing Ion Concentrations in Spiking Neural Networks
  crossref Rafael Afonso Rodrigues, Simon O’Keefe 2024-09-09T17:35:05Z 置信度 0.70
• Musical notes classification with neuromorphic auditory system using FPGA and a convolutional spiking network
  crossref E. Cerezuela-Escudero, A. Jimenez-Fernandez, R. Paz-Vicente, M. Dominguez-Morales 等 2015-10-01T17:48:02Z 置信度 0.70
• Development of a Centralized Conflict Free Greedy Assignment Learning Spiking Neural Network for Solving a Perimeter Defense Problem
  In this paper, a Centralized Conflict-free Assignment Learning Spiking neural network (C2ALS) is formulated for solving a Perimeter Defense Problem (PDP). Here, the region between the perimeter and the sensing range of the defender is divided into two layers. …
  crossref Mohammed Thousif, Shridhar Velhal, Suresh Sundaram, Narasimhan Sundararajan 2025-01-03T05:21:06Z 置信度 0.70
• EESCN: A novel spiking neural network method for EEG-based emotion recognition
  europepmc FeiFan Xu, Deng Pan, Haohao Zheng, Yu Ouyang 等 2023-11-20T18:46:11Z 置信度 0.80
• Event-based Video Reconstruction via Potential-assisted Spiking Neural Network
  crossref Lin Zhu, Xiao Wang, Yi Chang, Jianing Li 等 2022-09-27T15:56:41Z 置信度 0.70
• Calibrating Bayesian decoders of neural spiking activity
  Abstract Accurately decoding external variables from observations of neural activity is a major challenge in systems neuroscience. Bayesian decoders, that provide probabilistic estimates, are some of the most widely used. Here we show how, in many common setti…
  crossref Ganchao Wei, Zeinab Tajik Mansouri, Xiaojing Wang, Ian H. Stevenson 2023-11-16T21:10:21Z 置信度 0.70
• Continual Learning with Columnar Spiking Neural Networks
  crossref D. Larionov, N. Bazenkov, M. Kiselev 2025-12-19T16:34:47Z 置信度 0.70
• A bio-inspired spiking neural network with adaptive spatiotemporal filtering and direction-modulated synaptic plasticity for robust collision detection
  crossref Yumeng Ren, Ye Zhao, Long Chen, Qihang Jiang 等 2025-09-05T14:42:02Z 置信度 0.70
• A Compressed Sensing Spiking Neural Network System for Radar-Based HGR
  crossref Liyu Qian, Zikai Zhu, Yuhan He, Jie Lu 等 2026-01-19T20:51:17Z 置信度 0.70
• CalibraSNN: Fair and Calibrated Convolutional Spiking Neural Network for High-Stakes Industry Applications
  crossref Dylan Perdigão, Francisco Antunes, Catarina Silva, Bernardete Ribeiro 2025-12-08T18:41:50Z 置信度 0.70
• Synapses mediate the effects of different types of stress on working memory: a brain-inspired spiking neural network study
  Acute stress results from sudden short-term events, and individuals need to quickly adjust their physiological and psychological to re-establish balance. Chronic stress, on the other hand, results in long-term physiological and psychological burdens due to the…
  europepmc Chengcheng Du, Yinqian Sun, Jihang Wang, Qian Zhang 等 2025 置信度 0.80
• Novel Spiking Neural Network Model for Gear Fault Diagnosis
  crossref Yasir Hassan Ali, Falah Y. H. Ahmed, Ahmed M. Abdelrhman, Salah M. Ali 等 2022-11-07T23:01:10Z 置信度 0.70
• Monitor-Based Spiking Recurrent Network for the Representation of Complex Dynamic Patterns
  Neural networks are powerful computation tools for mimicking the human brain to solve realistic problems. Since spiking neural networks are a type of brain-inspired network, called the novel spiking system, Monitor-based Spiking Recurrent network (MbSRN), is d…
  crossref Ruihan Hu, Qijun Huang, Hao Wang, Jin He 等 2019-02-08T03:03:46Z 置信度 0.70
• Brain-Inspired Hardware for Artificial Intelligence: Accelerated Learning in a Physical-Model Spiking Neural Network
  crossref Timo Wunderlich, Akos F. Kungl, Eric Müller, Johannes Schemmel 等 2019-09-08T19:02:47Z 置信度 0.70
• Energy–Accuracy Trade-offs in Spiking Neural Networks: A Pareto Analysis on Fashion-MNIST
  Abstract We tested a directly-trained, rate-coded SNN for Fashion-MNIST [28] (60,000 training images / 10,000 test images, each 28×28 greyscale, 10 classes) for varying numbers of simulation timesteps T = {1, 2, 4, 8, 16, 32, 64} over three randomly seeded run…
  crossref Hassan Farooq 2026-06-19T04:12:00Z 置信度 0.70
• Spiking neural networks take control
  Brain-inspired neural network architecture overcomes unsolved classical control theory problem for telerobotics.
  crossref Travis DeWolf 2021-09-08T19:02:21Z 置信度 0.70
• Multidimensional Encoding Strategy of Spiking Neurons
  Neural responses in sensory systems are typically triggered by a multitude of stimulus features. Using information theory, we study the encoding accuracy of a population of stochastically spiking neurons characterized by different tuning widths for the differe…
  crossref Christian W. Eurich, Stefan D. Wilke 2002-07-27T11:56:30Z 置信度 0.70
• Relaxation LIF: A gradient-based spiking neuron for direct training deep spiking neural networks
  crossref Jianxiong Tang, Jian-Huang Lai, Wei-Shi Zheng, Lingxiao Yang 等 2022-06-15T11:53:19Z 置信度 0.70
• Learning Method of Recurrent Spiking Neural Networks to Realize Various Firing Patterns using Particle Swarm Optimization
  crossref Yasuaki Kuroe, Hitoshi Iima, Yutaka Maeda 2019-10-02T13:03:52Z 置信度 0.70
• Constraints on Hebbian and STDP learned weights of a spiking neuron
  crossref Dominique Chu, Huy Le Nguyen 2021-01-02T05:57:49Z 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
• Reinforcement Learning with Spiking Neural Networks for Robotic Applications: A Survey
  Spiking Neural Networks (SNNs) have long been positioned as a biologically plausible and energy-efficient alternative to conventional deep learning models. Reinforcement Learning (RL), on the other hand, provides a framework for autonomous decision-making base…
  crossref Katerina Maria Oikonomou, Ioannis Kansizoglou, Antonios Gasteratos 2025-06-19T18:43:21Z 置信度 0.70
• E6.4 - Biological Neural Coding for Adaptive Spiking Analog to Digital Conversion
  crossref H. Abd, A. König 2023-06-26T13:32:37Z 置信度 0.70
• Implementation of configurable and multipurpose spiking neural networks on GPUs
  crossref Antonio Arista-Jalife, Roberto A. Vazquez 2012-08-01T16:47:51Z 置信度 0.70
• Temporal Effective Batch Normalization in Spiking Neural Networks
  crossref Chaoteng Duan, Jianhao Ding, Shiyan Chen, Zhaofei Yu 等 2026-03-02T13:17:52Z 置信度 0.70
• Online Evolving Spiking Neural Networks for Incremental Air Pollution Prediction
  crossref Piotr S. Maciag, Marzena Kryszkiewicz, Robert Bembenik 2020-09-29T20:40:33Z 置信度 0.70
• Spiking Depth: Depth estimation from sparse events with spiking neural networks
  crossref Dongze Liu, Yimeng Fan, Wenrui Lu, Changsong Liu 等 2025-10-10T06:41:45Z 置信度 0.70
• A Signal-Harmonizing Hybrid Neural Pathway Enabled by Bipolar-Chemo-Synapse Spiking Interneuron
  crossref 2025-03-14T00:20:21Z 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
• Spike-to-excite: photosensitive seizures in biologically-realistic spiking neural networks
  Abstract Photosensitive Epilepsy (PE) is a neurological disorder characterized by seizures triggered by harmful visual stimuli, such as flashing lights and high-contrast patterns. The mechanisms underlying PE remain poorly understood, and to date, no computati…
  crossref Luke Taylor, Melissa Claire Maaike Fasol 2024-08-07T20:20:22Z 置信度 0.70
• On Some Classes of Sequential Spiking Neural P Systems
  Spiking neural P systems (SN P systems) are a class of distributed parallel computing devices inspired by the way neurons communicate by means of spikes; neurons work in parallel in the sense that each neuron that can fire should fire, but the work in each neu…
  crossref Xingyi Zhang, Xiangxiang Zeng, Bin Luo, Linqiang Pan 2014-02-20T16:12:03Z 置信度 0.70
• Highly scalable hardware architecture for real-time execution of spiking neural networks applied to neural cognitive applications
  (English) This thesis contributes to the field of neuromorphic hardware. In particular, to the significant improvement of a scalable hardware architecture, named Hardware Emulator of Evolvable Neural Spiking Systems (HEENS), for the real-time execution of spik…
  crossref Bernardo Javier Vallejo Mancero 2025-04-11T01:22:18Z 置信度 0.70
• Adaptive spiking neural P systems
  crossref Hong Peng, Jun Wang 2010-09-29T18:03:07Z 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
• Sleep-Mediated Replay Prevents Catastrophic Forgetting in Spiking Neural Networks Trained on Sequential Tasks
  Catastrophic forgetting is a fundamental challenge in sequential learning for artificial neural networks, particularly spiking neural networks (SNNs), which aim to emulate biologically plausible neuronal dynamics. In this study, we investigate the role of slee…
  crossref Yeteesh Sabbineni, Ethan Qiu 2026-02-27T13:47:40Z 置信度 0.70
• Spatiotemporal Coding in the Cortex: Information Flow-Based Learning in Spiking Neural Networks
  We introduce a learning paradigm for networks of integrate-and-fire spiking neurons that is based on an information-theoretic criterion. This criterion can be viewed as a first principle that demonstrates the experimentally observed fact that cortical neurons …
  crossref Gustavo Deco, Bernd Schürmann 2002-07-27T11:55:01Z 置信度 0.70
• A Point Process Framework for Relating Neural Spiking Activity to Spiking History, Neural Ensemble, and Extrinsic Covariate Effects
  Multiple factors simultaneously affect the spiking activity of individual neurons. Determining the effects and relative importance of these factors is a challenging problem in neurophysiology. We propose a statistical framework based on the point process likel…
  crossref Wilson Truccolo, Uri T. Eden, Matthew R. Fellows, John P. Donoghue 等 2004-09-08T20:25:28Z 置信度 0.70
• SGSSA: Spatio-temporal granular-threshold spiking self-attention for spiking neural networks
  crossref Heng Zhang, LiQing Geng, GengHuang Yang, Yongfeng Zheng 2026-02-07T15:57:15Z 置信度 0.70
• Dynamic Quantum-Inspired Particle Swarm Optimizationas Feature and Parameter Optimizer for Evolving Spiking Neural Networks
  crossref Haza Nuzly Abdull Hamed, Nikola Kasabov, Siti Mariyam Shamsuddin 2013-11-18T04:14:49Z 置信度 0.70
• Adaptive Spiking TD3+BC for Offline-to-Online Spiking Reinforcement Learning
  crossref Xiangfei Yang, Jian Song, Xuetao Zhang, Donglin Wang 2024-09-09T17:35:05Z 置信度 0.70
• A Biologically Plausible Speech Recognition Framework Based on Spiking Neural Networks
  crossref Jibin Wu, Yansong Chua, Haizhou Li 2018-10-19T22:25:09Z 置信度 0.70
• Stochastic Spiking Neural Networks at the EDGE of CHAOS
  crossref J.L. Rossello, V. Canals, A. Oliver, A. Morro 2014-09-10T10:30:33Z 置信度 0.70
• Minimal Spiking Neuron for Solving Multilabel Classification Tasks
  The multispike tempotron (MST) is a powersul, single spiking neuron model that can solve complex supervised classification tasks. It is also internally complex, computationally expensive to evaluate, and unsuitable for neuromorphic hardware. Here we aim to und…
  crossref Jakub Fil, Dominique Chu 2020-05-20T23:03:41Z 置信度 0.70
• A Unified Approach to Building and Controlling Spiking Attractor Networks
  Extending work in Eliasmith and Anderson (2003), we employ a general framework to construct biologically plausible simulations of the three classes of attractor networks relevant for biological systems: static (point, line, ring, and plane) attractors, cyclic …
  crossref Chris Eliasmith 2005-04-11T19:24:40Z 置信度 0.70
• A Bio-Inspired Computational Astrocyte Model for Spiking Neural Networks
  crossref Jacob Kiggins, J. David Schaffer, Cory Merkel 2023-08-02T17:30:03Z 置信度 0.70
• Spiking Neural PID Controllers
  crossref Andrew Webb, Sergio Davies, David Lester 2011-11-10T18:56:48Z 置信度 0.70
• Biologically-Plausible Spiking Neural Networks For Object Recognition
  crossref Milad Mozafari, Saeed Reza Kheradpisheh 2018-10-19T16:42:07Z 置信度 0.70
• Think local, act global: robust and real-time movement encoding in spiking neural networks using neuromorphic hardware
  crossref Carlo Michaelis 2022-03-08T14:00:08Z 置信度 0.70
• Multimodal Representation Learning in a Spiking Neural Networks Framework
  Multimodal representation learning aims to integrate heterogeneous modalities—such as text, image, audio, and video—into a unified representation. However, modality imbalance and inter-modal interference often lead to modality collapse, limiting generalization…
  crossref yuping zhang, Yan Liu, Chunfang Yang, Zilin zhang 2026-02-23T12:42:35Z 置信度 0.70
• Spiking Neural Networks for Cortical Neuronal Spike Train Decoding
  Recent investigation of cortical coding and computation indicates that temporal coding is probably a more biologically plausible scheme used by neurons than the rate coding used commonly in most published work. We propose and demonstrate in this letter that sp…
  crossref Huijuan Fang, Yongji Wang, Jiping He 2009-11-19T00:59:10Z 置信度 0.70
• BS4NN: Binarized Spiking Neural Networks with Temporal Coding and Learning
  crossref Saeed Reza Kheradpisheh, Maryam Mirsadeghi, Timothée Masquelier 2021-11-10T21:02:55Z 置信度 0.70
• Modelling Strength-Based Representations in Memory Using Spiking Neural Networks
  crossref Patrick Tsapoitis, Jakeb Chouinard, Myra Fernandes 2026-05-11T01:19:47Z 置信度 0.70
• Green Neuromorphic Computing: Quantifying the Energy Efficiency of Spiking Neural Networks for Edge AI Applications
  crossref Aashish Dhakal 2026-01-26T16:06:51Z 置信度 0.70
• Introducing the Dendrify framework for incorporating dendrites to spiking neural networks
  Abstract Computational modeling has been indispensable for understanding how subcellular neuronal features influence circuit processing. However, the role of dendritic computations in network-level operations remains largely unexplored. This is partly because …
  crossref Michalis Pagkalos, Spyridon Chavlis, Panayiota Poirazi 2022-05-04T13:35:28Z 置信度 0.70
• Robustness to Noisy Synaptic Weights in Spiking Neural Networks
  crossref Chen Li, Runze Chen, Christoforos Moutafis, Steve Furber 2020-09-30T00:40:33Z 置信度 0.70
• Latent Diffusion for Neural Spiking Data
  crossref Jaivardhan Kapoor, Auguste Schulz, Julius Vetter, Felix Pei 等 2025-11-03T11:20:56Z 置信度 0.70
• Object Detection with Spiking Neural Networks on Automotive Event Data
  crossref Loic Cordone, Benoit Miramond, Philippe Thierion 2022-09-30T15:56:04Z 置信度 0.70
• Elucidating the Theoretical Underpinnings of Surrogate Gradient Learning in Spiking Neural Networks
  Abstract Training spiking neural networks to approximate universal functions is essential for studying information processing in the brain and for neuromorphic computing. Yet the binary nature of spikes poses a challenge for direct gradient-based training. Sur…
  crossref Julia Gygax, Friedemann Zenke 2025-03-20T18:41:15Z 置信度 0.70
• Bioplausible Unsupervised Delay Learning for Extracting Spatiotemporal Features in Spiking Neural Networks
  Abstract The plasticity of the conduction delay between neurons plays a fundamental role in learning temporal features that are essential for processing videos, speech, and many high-level functions. However, the exact underlying mechanisms in the brain for th…
  crossref Alireza Nadafian, Mohammad Ganjtabesh 2024-05-22T22:53:02Z 置信度 0.70
• Time series prediction and anomaly detection with recurrent spiking neural networks
  crossref Yann Cherdo, Benoit Miramond, Alain Pegatoquet 2023-08-02T17:30:03Z 置信度 0.70
• A Signal-Harmonizing Hybrid Neural Pathway Enabled by Bipolar-Chemo-Synapse Spiking Interneuron
  crossref 2025-03-14T00:20:21Z 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
• S <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e2582" altimg="si15.svg"> <mml:msup> <mml:mrow/> <mml:mrow> <mml:mn>3</mml:mn> </mml:mrow> </mml:msup> </mml:math> NN: Time step reduction of spiking surrogate gradients for training energy efficient single-step spiking neural networks
  crossref Kazuma Suetake, Shin-ichi Ikegawa, Ryuji Saiin, Yoshihide Sawada 2022-12-19T11:29:06Z 置信度 0.70
• Learning methods of recurrent Spiking Neural Networks based on adjoint equations approach
  crossref Yasuaki Kuroe, Tomokazu Ueyama 2010-10-19T14:58:15Z 置信度 0.70
• Effective Conversion of a Convolutional Neural Network into a Spiking Neural Network for Image Recognition Tasks
  Due to energy efficiency, spiking neural networks (SNNs) have gradually been considered as an alternative to convolutional neural networks (CNNs) in various machine learning tasks. In image recognition tasks, leveraging the superior capability of CNNs, the CNN…
  crossref Huynh Cong Viet Ngu, Keon Myung Lee 2022-06-06T10:08:24Z 置信度 0.70
• Fast Temporal Encoding and Decoding with Spiking Neurons
  We propose a simple theoretical structure of interacting integrate-and-fire neurons that can handle fast information processing and may account for the fact that only a few neuronal spikes suffice to transmit information in the brain. Using integrate-and-fire …
  crossref David Horn, Sharon Levanda 2002-07-27T11:55:01Z 置信度 0.70
• Capacity of a Single Spiking Neuron Channel
  crossref Shiro Ikeda, Jonathan H. Manton 2009-02-02T18:54:21Z 置信度 0.70
• Mechanisms That Modulate the Transfer of Spiking Correlations
  Correlations between neuronal spike trains affect network dynamics and population coding. Overlapping afferent populations and correlations between presynaptic spike trains introduce correlations between the inputs to downstream cells. To understand network ac…
  crossref Robert Rosenbaum, Krešimir Josić 2011-02-07T22:27:58Z 置信度 0.70
• INXS: Bridging the throughput and energy gap for spiking neural networks
  crossref Surya Narayanan, Ali Shafiee, Rajeev Balasubramonian 2017-07-10T21:41:30Z 置信度 0.70
• Trial matching: capturing variability with data-constrained spiking neural networks
  crossref Christos Sourmpis, Carl Petersen, Wulfram Gerstner, Guillaume Bellec 2026-03-02T13:18:04Z 置信度 0.70
• Spatiotemporal Conditional Inference and Hypothesis Tests for Neural Ensemble Spiking Precision
  The collective dynamics of neural ensembles create complex spike patterns with many spatial and temporal scales. Understanding the statistical structure of these patterns can help resolve fundamental questions about neural computation and neural dynamics. Spat…
  crossref Matthew T. Harrison, Asohan Amarasingham, Wilson Truccolo 2014-11-07T19:42:44Z 置信度 0.70
• Compact silicon neuron circuit with spiking and bursting behaviour
  crossref Jayawan H.B. Wijekoon, Piotr Dudek 2008-02-12T15:20:47Z 置信度 0.70
• Online Training Through Time for Spiking Neural Networks
  crossref Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Di He 等 2026-03-02T13:17:52Z 置信度 0.70
• Fundamentals of spiking neural networks
  crossref Hong Qu, Xiaoling Luo, Zhang Yi 2024-06-28T07:47:34Z 置信度 0.70
• Spiking Neural Algorithms for Markov Process Random Walk
  crossref William Severa, Rich Lehoucq, Ojas Parekh, James B. Aimone 2018-10-19T18:25:09Z 置信度 0.70
• SpikingLab: modelling agents controlled by Spiking Neural Networks in Netlogo
  crossref Cristian Jimenez-Romero, Jeffrey Johnson 2016-06-07T15:55:24Z 置信度 0.70
• Toward One-Shot Learning in Neuroscience-Inspired Deep Spiking Neural Networks
  Abstract Conventional deep neural networks capture essential information processing stages in perception. Deep neural networks often require very large volume of training examples, whereas children can learn concepts such as hand-written digits with few exampl…
  crossref Faramarz Faghihi, Hossein Molhem, Ahmed A. Moustafa 2019-11-05T01:51:20Z 置信度 0.70