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neural and evolutionary computing cs.ne

GeneTech 知识引擎共收录 107 篇相关科研实体，横跨 13 个垂直领域。数据来自 OpenAlex、arXiv、Crossref、PubMed、Europe PMC 等公开学术源，全部可溯源到原文。

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代表性文献（按质量分排序，前 60 条）

• A Bayes-Markov Neuromorphic Model of Cortical Orientation Selectivity: A Computational Re-implementation and Quantitative Simulation Study
  2026 · 生物计算 · The emergence of orientation selectivity in the primary visual cortex (V1) remains a central question in computational neuroscience. Shirazi's Bayes-Markov model proposed a probabilistic explanation for how orientation-s…
• What Makes a Bacterial Model a Good Reservoir Computer? Predicting Performance from Separability and Similarity
  2026 · 生物计算 · Biological systems are promising substrates for computation because they naturally process environmental information through complex internal dynamics. In this study, we investigate whether bacterial metabolic models can…
• Life as Plasmas: Autonomy and Interactivism in-materio
  2026 · 生物计算 · When is a material system a candidate for life at all? We argue that this question is prior to behavior, functional architecture, or computational capacity, and that at root it is one of physical admissibility. We develo…
• Cell-type-specific synaptic motifs generate coupled mean-variability dynamics in recurrent neural networks
  2026 · 生物计算 · Synaptic-resolution network connectomics has revealed that brain circuits feature fine-scale structural connectivity, such as pairs of correlated synaptic couplings known as second-order motifs. Large-scale recordings of…
• A Comprehensive Review of Bio-Inspired Approaches to Coordination, Communication, and System Architecture in Underwater Swarm Robotics
  2026 · 深海科技 · The increasing complexity of marine operations has intensified the need for intelligent robotic systems to support ocean observation, exploration, and resource management. Underwater swarm robotics offers a promising fra…
• A Novel Immune Algorithm for Multiparty Multiobjective Optimization
  2026 · 低空经济 · Traditional multiobjective optimization problems (MOPs) are insufficiently equipped for scenarios involving multiple decision makers (DMs), which are prevalent in many practical applications. These scenarios are categori…
• Task-free Adaptive Meta Black-box Optimization
  2026 · 低空经济 · Handcrafted optimizers become prohibitively inefficient for complex black-box optimization (BBO) tasks. MetaBBO addresses this challenge by meta-learning to automatically configure optimizers for low-level BBO tasks, the…
• Neural dynamical systems on ferroelectric compute-in-memory for real-time forecasting
  2026 · 类脑计算 · 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 den…
• Quadratic integrate-and-fire neurons exhibit less fragmented loss landscapes and outperform leaky integrate-and-fire neurons in spike-based gradient descent
  2026 · 类脑计算 · The ability to train spiking neural networks is essential for modeling biological neural networks as well as for neuromorphic computing. However, for the extensively used leaky integrate-and-fire (LIF) neurons, arbitrari…
• Spiking and Event-driven Neuromorphic Mamba Models for Efficient Speech Recognition
  2026 · 类脑计算 · Deep learning has greatly advanced automatic speech recognition (ASR), enabling widespread deployment on edge devices such as smartphones and smart home systems. However, the computational and energy demands of deep neur…
• A feedback control optimizer for online and hardware-aware training of Spiking Neural Networks
  2026 · 类脑计算 · Unlike traditional artificial neural networks (ANNs), biological neuronal networks solve complex cognitive tasks with sparse neuronal activity, recurrent connections, and local learning rules. These mechanisms serve as d…
• Stochastic Spiking Neuron Based SNN Can be Inherently Bayesian
  2026 · 类脑计算 · Uncertainty in biological neural systems appears to be computationally beneficial rather than detrimental. However, in neuromorphic computing systems, device variability often limits performance, including accuracy and e…
• Learning Alzheimer's Disease Signatures by bridging EEG with Spiking Neural Networks and Biophysical Simulations
  2026 · 类脑计算 · As the prevalence of Alzheimer's disease (AD) rises, improving mechanistic insight from non-invasive biomarkers is increasingly critical. Recent work suggests that circuit-level brain alterations manifest as changes in e…
• A neuromorphic model of the insect visual system for natural image processing
  2026 · 类脑计算 · Insect vision supports complex behaviors including associative learning, navigation, and object detection, and has long motivated computational models for understanding biological visual processing. However, many contemp…
• Energy-Efficient Neuromorphic Computing for Edge AI: A Framework with Adaptive Spiking Neural Networks and Hardware-Aware Optimization
  2026 · 类脑计算 · Edge AI applications increasingly require ultra-low-power, low-latency inference. Neuromorphic computing based on event-driven spiking neural networks (SNNs) offers an attractive path, but practical deployment on resourc…
• STAER: Temporal Aligned Rehearsal for Continual Spiking Neural Network
  2026 · 类脑计算 · Spiking Neural Networks (SNNs) are inherently suited for continuous learning due to their event-driven temporal dynamics; however, their application to Class-Incremental Learning (CIL) has been hindered by catastrophic f…
• Sleep-Based Homeostatic Regularization for Stabilizing Spike-Timing-Dependent Plasticity in Recurrent Spiking Neural Networks
  2026 · 类脑计算 · Spike-timing-dependent plasticity (STDP) provides a biologically-plausible learning mechanism for spiking neural networks (SNNs); however, Hebbian weight updates in architectures with recurrent connections suffer from pa…
• Energy-Efficient Eimeria Parasite Detection Using a Two-Stage Spiking Neural Network Architecture
  2026 · 类脑计算 · Coccidiosis, a disease caused by the Eimeria parasite, represents a major threat to the poultry and rabbit industries, demanding rapid and accurate diagnostic tools. While deep learning models offer high precision, their…
• ORBITALIF: An Efficient Spiking Federated Learning Framework for Onboard Cloud Removal
  2026 · 隐私计算与数据要素 · Low-earth-orbit (LEO) satellites enable high-resolution, large-scale Earth observation for applications such as disaster monitoring and environmental surveillance. However, cloud coverage often obscures the Earth's surfa…
• Neural Associative Skill Memories for safer robotics and modelling human sensorimotor repertoires
  2025 · 仿生智能 · Modern robots face challenges shared by humans, where machines must learn multiple sensorimotor skills and express them adaptively. Equipping robots with a human-like memory of how it feels to do multiple stereotypical m…
• Balancing Interpretability and Performance in Motor Imagery EEG Classification: A Comparative Study of ANFIS-FBCSP-PSO and EEGNet
  2025 · 仿生智能 · Achieving both accurate and interpretable classification of motor-imagery EEG remains a key challenge in brain-computer interface (BCI) research. In this paper, we compare a transparent fuzzy-reasoning approach (ANFIS-FB…
• Nauplius Optimisation for Autonomous Hydrodynamics
  2025 · 深海科技 · Autonomous Underwater vehicles must operate in strong currents, limited acoustic bandwidth, and persistent sensing requirements where conventional swarm optimisation methods are unreliable. This paper formulates an irrev…
• Fast Data Aware Neural Architecture Search via Supernet Accelerated Evaluation
  2025 · 边缘智能 · Tiny machine learning (TinyML) promises to revolutionize fields such as healthcare, environmental monitoring, and industrial maintenance by running machine learning models on low-power embedded systems. However, the comp…
• Bridging Brains and Machines: A Unified Frontier in Neuroscience, Artificial Intelligence, and Neuromorphic Systems
  2025 · 具身智能 · This position and survey paper identifies the emerging convergence of neuroscience, artificial general intelligence (AGI), and neuromorphic computing toward a unified research paradigm. Using a framework grounded in brai…
• I2E: Real-Time Image-to-Event Conversion for High-Performance Spiking Neural Networks
  2025 · 类脑计算 · 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 …
• Neuromorphic Wireless Split Computing with Resonate-and-Fire Neurons
  2025 · 类脑计算 · 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 sensi…
• ReLANCE: A Resource-Efficient Low-Latency Cortical Neural Acceleration Engine
  2025 · 类脑计算 · We present a Cortical Neural Pool (CNP) architecture featuring a high-speed, resource-efficient CORDIC based Hodgkin-Huxley (RCHH) neuron model. Unlike shared CORDIC-based DNN approaches, the proposed neuron leverages mo…
• FeNN-DMA: A RISC-V SoC for SNN acceleration
  2025 · 类脑计算 · Spiking Neural Networks (SNNs) are a promising, energy-efficient alternative to standard Artificial Neural Networks (ANNs) and are particularly well-suited to spatio-temporal tasks such as keyword spotting and video clas…
• Proxy Target: Bridging the Gap Between Discrete Spiking Neural Networks and Continuous Control
  2025 · 类脑计算 · Spiking Neural Networks (SNNs) offer low-latency and energy-efficient decision making on neuromorphic hardware, making them attractive for Reinforcement Learning (RL) in resource-constrained edge devices. However, most R…
• Bruno: Backpropagation Running Undersampled for Novel device Optimization
  2025 · 类脑计算 · Recent efforts to improve the efficiency of neuromorphic and machine learning systems have centred on developing of specialised hardware for neural networks. These systems typically feature architectures that go beyond t…
• Temporal Regularization Training: Unleashing the Potential of Spiking Neural Networks
  2025 · 类脑计算 · Spiking Neural Networks (SNNs) have received widespread attention due to their event-driven and low-power characteristics, making them particularly effective for processing neuromorphic data. Recent studies have shown th…
• Enabling Efficient Processing of Spiking Neural Networks with On-Chip Learning on Commodity Neuromorphic Processors for Edge AI Systems
  2025 · 类脑计算 · The rising demand for energy-efficient edge AI systems (e.g., mobile agents/robots) has increased the interest in neuromorphic computing, since it offers ultra-low power/energy AI computation through spiking neural netwo…
• QSViT: A Methodology for Quantizing Spiking Vision Transformers
  2025 · 类脑计算 · Vision Transformer (ViT)-based models have shown state-of-the-art performance (e.g., accuracy) in vision-based AI tasks. However, realizing their capability in resource-constrained embedded AI systems is challenging due …
• Neuromorphic Cybersecurity with Semi-supervised Lifelong Learning
  2025 · 类脑计算 · Inspired by the brain's hierarchical processing and energy efficiency, this paper presents a Spiking Neural Network (SNN) architecture for lifelong Network Intrusion Detection System (NIDS). The proposed system first emp…
• Energy-Efficient Digital Design: A Comparative Study of Event-Driven and Clock-Driven Spiking Neurons
  2025 · 类脑计算 · This paper presents a comprehensive evaluation of Spiking Neural Network (SNN) neuron models for hardware acceleration by comparing event driven and clock-driven implementations. We begin our investigation in software, r…
• LightSNN: Lightweight Architecture Search for Sparse and Accurate Spiking Neural Networks
  2025 · 类脑计算 · 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 architecture…
• CogniSNN: Enabling Neuron-Expandability, Pathway-Reusability, and Dynamic-Configurability with Random Graph Architectures in Spiking Neural Networks
  2025 · 类脑计算 · 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 …
• NeuromorphicRx: From Neural to Spiking Receiver
  2025 · 类脑计算 · In this work, we propose a novel energy-efficient spiking neural network (SNN)-based receiver for 5G-NR OFDM system, called neuromorphic receiver (NeuromorphicRx), replacing the channel estimation, equalization and symbo…
• Accuracy-Robustness Trade Off via Spiking Neural Network Gradient Sparsity Trail
  2025 · 类脑计算 · Spiking Neural Networks (SNNs) have attracted growing interest in both computational neuroscience and artificial intelligence, primarily due to their inherent energy efficiency and compact memory footprint. However, achi…
• Dynamic Weight Adaptation in Spiking Neural Networks Inspired by Biological Homeostasis
  2025 · 类脑计算 · Homeostatic mechanisms play a crucial role in maintaining optimal functionality within the neural circuits of the brain. By regulating physiological and biochemical processes, these mechanisms ensure the stability of an …
• Neuromorphic Astronomy: An End-to-End SNN Pipeline for RFI Detection Hardware
  2025 · 类脑计算 · Imminent radio telescope observatories provide massive data rates making deep learning based processing appealing while simultaneously demanding real-time performance at low-energy; prohibiting the use of many artificial…
• A High-Throughput Spiking Neural Network Processor Enabling Synaptic Delay Emulation
  2025 · 类脑计算 · Synaptic delay has attracted significant attention in neural network dynamics for integrating and processing complex spatiotemporal information. This paper introduces a high-throughput Spiking Neural Network (SNN) proces…
• Event-Driven Implementation of a Physical Reservoir Computing Framework for superficial EMG-based Gesture Recognition
  2025 · 类脑计算 · Wearable health devices have a strong demand in real-time biomedical signal processing. However traditional methods often require data transmission to centralized processing unit with substantial computational resources …
• Predicting Deterioration in Mild Cognitive Impairment with Survival Transformers, Extreme Gradient Boosting and Cox Proportional Hazard Modelling
  2024 · 医疗人工智能 · The paper proposes a novel approach of survival transformers and extreme gradient boosting models in predicting cognitive deterioration in individuals with mild cognitive impairment (MCI) using metabolomics data in the A…
• Continuous-Time Digital Twin with Analogue Memristive Neural Ordinary Differential Equation Solver
  2024 · 数字孪生 · Digital twins, the cornerstone of Industry 4.0, replicate real-world entities through computer models, revolutionising fields such as manufacturing management and industrial automation. Recent advances in machine learnin…
• When In-memory Computing Meets Spiking Neural Networks -- A Perspective on Device-Circuit-System-and-Algorithm Co-design
  2024 · 边缘智能 · This review explores the intersection of bio-plausible artificial intelligence in the form of Spiking Neural Networks (SNNs) with the analog In-Memory Computing (IMC) domain, highlighting their collective potential for l…
• Learning-to-learn enables rapid learning with phase-change memory-based in-memory computing
  2024 · 边缘智能 · There is a growing demand for low-power, autonomously learning artificial intelligence (AI) systems that can be applied at the edge and rapidly adapt to the specific situation at deployment site. However, current AI mode…
• Energy-Aware FPGA Implementation of Spiking Neural Network with LIF Neurons
  2024 · 边缘智能 · Tiny Machine Learning (TinyML) has become a growing field in on-device processing for Internet of Things (IoT) applications, capitalizing on AI algorithms that are optimized for their low complexity and energy efficiency…
• Wet TinyML: Chemical Neural Network Using Gene Regulation and Cell Plasticity
  2024 · 边缘智能 · In our earlier work, we introduced the concept of Gene Regulatory Neural Network (GRNN), which utilizes natural neural network-like structures inherent in biological cells to perform computing tasks using chemical inputs…
• Towards a tailored mixed-precision sub-8-bit quantization scheme for Gated Recurrent Units using Genetic Algorithms
  2024 · 边缘智能 · Despite the recent advances in model compression techniques for deep neural networks, deploying such models on ultra-low-power embedded devices still proves challenging. In particular, quantization schemes for Gated Recu…
• FastSpiker: Enabling Fast Training for Spiking Neural Networks on Event-based Data through Learning Rate Enhancements for Autonomous Embedded Systems
  2024 · 具身智能 · Autonomous embedded systems (e.g., robots) typically necessitate intelligent computation with low power/energy processing for completing their tasks. Such requirements can be fulfilled by embodied neuromorphic intelligen…
• Embodied Neuromorphic Artificial Intelligence for Robotics: Perspectives, Challenges, and Research Development Stack
  2024 · 具身智能 · Robotic technologies have been an indispensable part for improving human productivity since they have been helping humans in completing diverse, complex, and intensive tasks in a fast yet accurate and efficient way. Ther…
• TinySeg: Model Optimizing Framework for Image Segmentation on Tiny Embedded Systems
  2024 · 低空经济 · Image segmentation is one of the major computer vision tasks, which is applicable in a variety of domains, such as autonomous navigation of an unmanned aerial vehicle. However, image segmentation cannot easily materializ…
• Spiking Neural Networks for Radio Frequency Interference Detection in Radio Astronomy
  2024 · 类脑计算 · Spiking Neural Networks (SNNs) promise efficient and dynamic spatio-temporal data processing. This paper reformulates a significant challenge in radio astronomy, Radio Frequency Interference (RFI) detection, as a time-se…
• Noisy Spiking Actor Network for Exploration
  2024 · 类脑计算 · 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 rob…
• Improvement of Spiking Neural Network with Bit Planes and Color Models
  2024 · 类脑计算 · Spiking neural network (SNN) has emerged as a promising paradigm in computational neuroscience and artificial intelligence, offering advantages such as low energy consumption and small memory footprint. However, their pr…
• Digital twin brain: a bridge between biological intelligence and artificial intelligence
  2023 · 数字孪生 · In recent years, advances in neuroscience and artificial intelligence have paved the way for unprecedented opportunities for understanding the complexity of the brain and its emulation by computational systems. Cutting-e…
• Digital twin brain: a bridge between biological intelligence and artificial intelligence
  2023 · 边缘智能 · In recent years, advances in neuroscience and artificial intelligence have paved the way for unprecedented opportunities for understanding the complexity of the brain and its emulation by computational systems. Cutting-e…
• An Optimization Framework for Automated Assessment of Biological Plausibility of Spiking Neurons
  2026 · 生物计算 · 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 a…
• A 32-channel event-based bio-signal analog front-end with adaptive delta and pulse frequency encoding
  2026 · 仿生智能 · Low-power event-based Analog Front-Ends (AFEs) are essential for building efficient, end-to-end neuromorphic signal processing systems. In this paper, we present an event-based AFE Application-Specific Integrated Circuit…

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