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• Challenges and Opportunities of Upconversion Nanoparticles for Emerging NIR Optoelectronic Devices.
  europepmc 2025 置信度 0.80
• Hardware implementation of memristor-based artificial neural networks.
  europepmc 2024 置信度 0.80
• Two-dimensional material-based memristive devices for alternative computing.
  europepmc 2024 置信度 0.80
• A Design Methodology for Fault-Tolerant Neuromorphic Computing Using Bayesian Neural Network.
  europepmc 2023 置信度 0.80
• Memristive patch attention neural network for facial expression recognition and edge computing.
  europepmc 2024 置信度 0.80
• Computing high-degree polynomial gradients in memory.
  europepmc 2024 置信度 0.80
• Ultra-Transparent and Multifunctional IZVO Mesh Electrodes for Next-Generation Flexible Optoelectronics.
  europepmc 2024 置信度 0.80
• The effectiveness of analogue ‘neural network’ hardware
  crossref J J Hopfield 2015-08-18T16:03:59Z 置信度 0.70
• A four-dimensional memristor-coupled neural network chaotic dynamical system based on multi-level logic pulse stimulation
  Abstract In this paper, we propose a chaotic dynamics system based on a three-neuron cosine magnetically controlled memristor synapse-coupled Hopfield neural network. The system consists of a line equilibrium set composed of an infinite number of points, these…
  crossref Manhong Fan, Shiqi Xu, Qingsong Liu, Qian Xiao 2025-04-08T22:51:21Z 置信度 0.70
• Memristor-Based Neural Network Circuit of Delay and Simultaneous Conditioning
  crossref Xinyu Xu, Weilin Xu, Baolin Wei, Fangrong Hu 2021-10-27T19:43:32Z 置信度 0.70
• A logic device based on memristor-diode crossbar and CMOS periphery as spike router for hardware neural network
  crossref A.N. Busygin, S. Yu Udovichenko, A.D. Pisarev, A.H.A. Ebrahim 等 2024-05-08T03:26:27Z 置信度 0.70
• Automatic road sign detection and recognition based on neural network
  Abstract Road sign detection and recognition is an integral part of intelligent transportation sys-tems (ITS). It increases protection by reminding the driver of the current condition of the route, such as notices, bans, limitations and other valuable driving …
  crossref Redouan Lahmyed, Mohamed El Ansari, Zakaria Kerkaou 2021-06-04T23:04:09Z 置信度 0.70
• Review of: "Synthetic Data Generation of Body Motion Data by Neural Gas Network for Emotion Recognition"
  crossref Muhammad Naveed Riaz 2025-05-02T15:39:32Z 置信度 0.70
• Review for "SVIFNN: Robust Inpainting Fourier Neural Network for SST Scientific Visualization Image Leveraging Significant Stability and Nonsignificant Anomalies"
  crossref 2025-10-21T22:53:22Z 置信度 0.70
• Reviewer #1 (Public Review): When and why does motor preparation arise in recurrent neural network models of motor control?
  crossref 2023-08-10T15:39:42Z 置信度 0.70
• Reviewer #2 (Public Review): When and why does motor preparation arise in recurrent neural network models of motor control?
  crossref 2024-05-20T13:26:22Z 置信度 0.70
• A physics-guided graph neural network for interpretable multiscale modelling of concrete properties
  Abstract Hierarchical materials derive macroscopic performance from interactions among phases and interfaces, yet most machine-learning models represent concrete as a flat mixture vector. Here we develop HiCon-GNN, a physics-guided graph neural network that mi…
  crossref Ye Li, Fangying Wang 2026-07-22T03:16:32Z 置信度 0.70
• Memristor-Based Neural Network Circuit of Associative Memory with Multimodal Synergy
  crossref Juntao Han, Xiao Xiao, Xiangwei Chen, Junwei Sun 2021-03-31T08:02:49Z 置信度 0.70
• A dual-neuron second-order memristor-based Hopfield neural network with controllable extreme multistability and its application in image encryption
  crossref Yan Wang, Kangdi Yin, Jie Jin, Hongyan Li 2026-03-27T08:08:24Z 置信度 0.70
• Artificial Neural Network: A tool for Rapid Quantitative Elemental Analysis Using Neutron Activation Analysis
  Abstract This paper presents a methodology for rapid quantitative elemental analysis using Neutron Activation Analysis (NAA) coupled with an Artificial Neural Network (ANN). A three-layer feed-forward ANN with back-propagation algorithm was developed to determ…
  crossref M. E. Medhat 2026-04-30T04:05:20Z 置信度 0.70
• Review for "<b>SynCat</b> : Molecule-Level Attention Graph Neural Network for Precise Reaction Classification"
  crossref 2025-11-06T21:07:36Z 置信度 0.70
• Reviewer #2 (Public Review): When and why does motor preparation arise in recurrent neural network models of motor control?
  crossref 2024-08-13T11:26:10Z 置信度 0.70
• Review for "Research on short‐term output power forecast model of wind farm based on neural network combination algorithm"
  crossref 2022-06-22T17:02:21Z 置信度 0.70
• Atrial Fibrillation Detection Using Feedforward Neural Network
  Abstract Atrial fibrillation is one of the most common arrhythmias in clinics, which has a great impact on people's physical and mental health. Electrocardiogram (ECG) based arrhythmia detection is widely used in early atrial fibrillation detection. However, E…
  crossref Yunfan Chen, Chong Zhang, Chengyu Liu, Yiming Wang 等 2021-09-15T21:43:30Z 置信度 0.70
• Forecasting Gold Price using Hybrid Deep Neural Network LSTM-Autoencoder
  Abstract Gold prices hold a significant place in the global economy as they reflect the economic health, which influences markets, investments, and currency values. Industries that rely on commodities, investors and decision-makers, need accurate forecasting g…
  crossref Agampreet Saini, Rahul Kumar Singh, Puneet Sinha 2025-05-13T02:28:13Z 置信度 0.70
• Peer Review #2 of "A deep crowd density classification model for Hajj pilgrimage using fully convolutional neural network (v0.1)"
  crossref 2022-03-30T02:30:37Z 置信度 0.70
• Repair Instead of Retraining: A Constraint-Guided Framework for Neural Network Repair
  Abstract Deep neural networks remain vulnerable to adversarial perturbations and backdoor attacks, yet repairing a deployed model without full retraining must balance interpretability, behavioral fidelity, and computational cost. We present a constraint-guided…
  crossref Ting Yu Liu, Fang Yu 2026-07-22T13:58:58Z 置信度 0.70
• neural network
  crossref 2011-08-01T14:24:22Z 置信度 0.70
• Internal Mechanics of Neural Network Processing
  crossref Igor Livshin 2021-10-18T21:30:54Z 置信度 0.70
• Review for "Incorporating Neural Network in the AMOEBA Polarizable Force Field for Ligand Field Effects of Cu 2+ Ion"
  crossref 2026-07-23T13:11:05Z 置信度 0.70
• Effectiveness of Parallel Computer Data and Video English Course Based on Neural Network
  Abstract With the expansion of the scale of deep learning network and the rapid increase of the number of network training parameters, the network training time is getting longer and longer. In deep learning, convolutional neural network reduces the number of …
  crossref Min She, Fen Zhang 2023-04-10T17:42:51Z 置信度 0.70
• Review for "Temporal lobe epilepsy alters neural responses to human and avatar facial expressions in the face perception network"
  crossref 2021-05-07T17:23:49Z 置信度 0.70
• Review for "Instance segmentation of on-line wear debris using deep convolutional neural network with transfer learning"
  crossref 2024-12-17T16:01:54Z 置信度 0.70
• THE DEEP NEURAL NETWORK-A REVIEW
  Deep neural networks are considered the backbone of artificial intelligence, we will present a review of an article about the importance of neural networks and their role in other sciences, their characteristic, networks architecture, types, mathematical defin…
  crossref Eman Jawad 2023-09-23T07:45:52Z 置信度 0.70
• Reviewer #1 (Public Review): When and why does motor preparation arise in recurrent neural network models of motor control?
  crossref 2024-05-20T13:26:22Z 置信度 0.70
• Review for "Fault diagnosis for wind turbines with graph neural network model based on one-shot learning"
  crossref 2023-07-06T17:06:12Z 置信度 0.70
• TrustFedKG-Health: Explainability-Aware Personalized Federated Knowledge Graph Neural Network with Uncertainty-Guided Clinical Reasoning
  Abstract During preliminary experiments with federated graph learning on MIMIC-IV, we observed a consistent failure mode: hospitals with large patient volumes systematically dominated model aggregation even when their EHR records contained substantially higher…
  crossref ARITRIK GHOSH 2026-08-26T18:10:26Z 置信度 0.70
• Review for "Understanding the volatile memristor via direct observation of surface diffusion-regulated Cu-based conductive filaments"
  crossref 2026-04-25T21:02:46Z 置信度 0.70
• Analysis of Memristor Neural Networks for fault Tolerant Computing
  crossref Bhagya, Sharana Basaveshweshwar G Hiremath, C N Vijayakumar 2024-08-07T17:29:50Z 置信度 0.70
• Exponential synchronization of memristor-based recurrent neural networks with time delays
  crossref Ailong Wu, Zhigang Zeng, Xusheng Zhu, Jine Zhang 2011-06-03T13:12:06Z 置信度 0.70
• Memristor logic gates
  crossref 2018-03-24T08:06:28Z 置信度 0.70
• Peer Review #2 of "A deep crowd density classification model for Hajj pilgrimage using fully convolutional neural network (v0.2)"
  crossref 2022-03-30T02:30:40Z 置信度 0.70
• Convolutional neural network classifier incorporating misclassification information
  Abstract In this paper we introduce misclassification information for the improved training of convolutional neural network classifiers (CNNCs) for image recognition. We construct a additional autoencoder neural network, called tutor, that forces the CNNCs to …
  crossref Junying Hu, Rongrong Fei, Fang Du, Peiju Chang 等 2023-05-02T12:28:08Z 置信度 0.70
• Application of Interactive information system in College Personnel Management by using BP Neural Network Algorithm
  Abstract The BP neural network algorithm has flexible modeling ability and data parallel processing ability. While processing data, it learns through self-learning and adaptive algorithms and associative functions. In the calculation mode of the bp neural netw…
  crossref Lou Minsheng 2023-04-17T14:48:57Z 置信度 0.70
• Neural network smoothing of American options payoff with grid refinement strategies
  Abstract For an American call or put option, at the expiry time, the value function is a ramp function, the Delta sensitivity is a Heaviside function and Gamma is a Dirac delta measure. In addition, the first derivative with respect to the early exercise bound…
  crossref Chinonso Nwankwo, Tony Ware, Weizhong Dai 2025-09-17T03:17:57Z 置信度 0.70
• Artificial Neural Network Approach versus Analytical Solutions for Relativistic Polytropes
  Abstract Over the last few decades, artificial neural networks (ANN) have played an important role in many areas of human activity and have found application in many branches of natural sciences. ANNs have been widely used to tackle problems related to linear …
  crossref Mohamed Nouh, Emad Abdel-Salam, Yosry Azzam 2022-06-06T15:09:50Z 置信度 0.70
• Review for "Neural Network-Based Inverse Design for Multi-Objective Performance Optimization of 70 kHz Ultrasonic Transducers"
  crossref 2026-04-11T21:11:18Z 置信度 0.70
• Physics-informed Fourier Basis Neural Network for Fluid Mechanics
  Abstract Conventional machine learning approaches struggle to capture periodic patterns and solve quasi-periodic boundary problems in fluid mechanics. This study proposes a physics-informed Fourier basis neural network (PIFBNN) that integrates adaptive Fourier…
  crossref Chao Wang, Shilong Li, Zelong Yuan, Chunyu Guo 2025-10-30T03:57:12Z 置信度 0.70
• Forecast of SO2 Air Contamination utilizing Artificial Neural Network: Sample of City Meerut
  Abstract SO2 is among the air poisons that assume the best part in air contamination. In this study, using data from 2019 to 2023, estimates of how this contaminant was affecting human health and the environment were made using artificial neural networks, a we…
  crossref Lokesh kumar, Gaurav Kumar 2024-02-13T19:06:19Z 置信度 0.70
• Review for "Physics-Inspired Neural Network for Joint Inversion of Multialtitude 3-D Gravity and Vertical Gradient"
  crossref 2025-10-21T22:59:05Z 置信度 0.70
• Review for "Fault diagnosis for wind turbines with graph neural network model based on one-shot learning"
  crossref 2023-07-06T17:06:12Z 置信度 0.70
• Convolutional Neural Network
  Machine learning is the study of algorithms and models for computing systems to do tasks based on pattern identification and inference. When it is difficult or infeasible to develop an algorithm to do a particular task, machine learning algorithms can provide …
  crossref Mário Pereira Véstias 2021-09-17T11:47:50Z 置信度 0.70
• Automatic Detection of Pneumonia using Concatenated Convolutional Neural Network
  Abstract Pneumonia is a life-threatening disease and early detection can save lives, many automated systems have contributed to the detection of this disease and currently deep learning models have become one of the most widely used models for building these s…
  crossref Ahmad T. Al-Taani, Ishraq T. Al-Dagamseh 2022-11-07T19:28:31Z 置信度 0.70
• Review for "Modelling a chemical plant using grey‐box models employing the support vector regression and artificial neural network"
  crossref 2024-07-24T17:09:51Z 置信度 0.70
• An Optimal Approach for Heart Sound Classification Using Artificial Neural Network
  Abstract Heart sound auscultation is one of the most widely used approaches for detecting cardiovascular disorders. Diagnosing abnormalities of heart sound using a stethoscope depends on the physician’s skill and judgement. Several studies have shown promising…
  crossref Yunendah Nur Fu’adah, Ki Moo Lim 2021-07-30T15:48:14Z 置信度 0.70
• PIPxResNet: Penalty Induced Prototype-Based eXplainable Residual Neural Network for Heartbeat Classification
  Abstract Early stage heartbeat classification using the electrocardiogram signals can prevent cardiovascular diseases that causes millions of deaths annually around the world. In the past, researchers have used deep neural networks to achieve significant perfo…
  crossref Deepankar Nankani, Rashmi Dutta Baruah 2021-08-30T16:59:49Z 置信度 0.70
• Review for "Fault detection and classification in overhead transmission lines through comprehensive feature extraction using temporal convolution neural network"
  crossref 2024-07-03T17:08:45Z 置信度 0.70
• Graph Neural Network for Integrated Water Network Partitioning and Dynamic District Metered Areas
  Abstract Water distribution systems (WDSs) are used to transmit and distribute water resources in cities. Water distribution networks (WDNs) are partitioned into district metered areas (DMAs) by water network partitioning (WNP), which can be used for leak cont…
  crossref KEZHEN RONG, Minglei Fu, JIAWEI CHEN, LEJIN ZHENG 等 2021-10-11T20:16:09Z 置信度 0.70
• DCNN: A Novel Binary and Multi-Class Network Intrusion Detection Model via Deep Convolutional Neural Network
  Abstract Network security has become imperative in the context of our interconnected networks and everyday communications. Recently, many deep learning models have been proposed to tackle the problem of predicting intrusions and malicious activities in interco…
  crossref Ahmed Shebl, Sayed Elsedimy, Amr Ismail, Ahmed Salama 等 2024-04-01T06:00:18Z 置信度 0.70
• Neural network
  crossref 2015-07-10T15:46:54Z 置信度 0.70
• N-Net: A Convolutional Neural Network for Medical Image Segmentation
  Abstract This paper presents a novel supervised convolutional neural network architecture, "N-Net", capable of effectively learning and generalizing from small amounts of medical images to perform accurate segmentation tasks. Our model utilizes an encoder-deco…
  crossref Razvan-Gabriel Dumitru, Darius Peteleaza, Catalin Craciun 2023-01-30T17:03:30Z 置信度 0.70
• Developing the Optimal Hybrid Neural Network for Predicting the Factor of Air Pollutants
  Abstract Urban air pollution can be reduced via precise air pollutant forecasts.For that, the air quality index (AQI) quantifies air quality.In this manner, accurate and trustworthy air quality index (AQI) estimates are essential for preserving the natural env…
  crossref Neduncheliyan S, Priya Viswanathan 2024-02-12T05:56:12Z 置信度 0.70
• Segmenting ancient cemetery under forests using synthesized LiDAR-derived data and deep convolutional neural network
  Abstract The investigation and identification of spatial distribution of archaeological remains is full of challenges in forested areas, deep learning (DL) methods and light-detection and ranging (LiDAR) make it possible to quickly and automatically identify r…
  crossref Hong Yang 2024-11-06T18:05:20Z 置信度 0.70
• Review for "Combining three-dimensional acoustic coring and a convolutional neural network to quantify species contributions to benthic ecosystems"
  crossref 2024-06-20T17:06:39Z 置信度 0.70
• Review of: "Automated detection of superficial fungal infections from microscopic images through a regional convolutional neural network"
  crossref Enes Ayan 2021-10-29T17:26:51Z 置信度 0.70
• Asymptotical synchronization of memristor-based neural networks with time-varying delays via adaptive control
  crossref Yueheng Li, Zhanyu Yang, Zhe Dong 2017-09-29T19:54:00Z 置信度 0.70
• Review for "<b>SynCat</b> : Molecule-Level Attention Graph Neural Network for Precise Reaction Classification"
  crossref 2025-11-06T21:07:36Z 置信度 0.70
• Reviewer #1 (Public Review): When and why does motor preparation arise in recurrent neural network models of motor control?
  crossref 2024-08-13T11:26:10Z 置信度 0.70
• Review for "Modelling thermal characteristics of cocoa butter using a feed‐forward artificial neural network based on multilayer perceptron"
  crossref 2024-06-21T17:09:36Z 置信度 0.70
• Convolutional Neural Network and Clustering-Based Codebook Design Method for Massive MIMO Systems
  Abstract In this paper, we propose a convolutional neural network(CNN) and clustering based codebook design method. Specifically, we train two different CNN networks, i.e., CNN1 and CNN2, to compress the channel state information(CSI) matrices into the channel…
  crossref Jing Xing, Die Hu 2021-11-30T22:41:17Z 置信度 0.70
• ReLU-type memristor-based Hopfield neural network
  crossref Chengjie Chen, Fuhong Min 2022-08-04T09:03:38Z 置信度 0.70
• Memristor-based synapse design and training scheme for neuromorphic computing architecture
  crossref Hui Wang, Hai Li, Robinson E. Pino 2012-08-01T16:47:51Z 置信度 0.70
• Review for "Understanding the volatile memristor via direct observation of surface diffusion-regulated Cu-based conductive filaments"
  crossref 2026-04-25T21:02:46Z 置信度 0.70
• Perception of Groundnuts Leaf Disease by Neural Network with Progressive Re-Sizing
  Abstract India is the world's second-largest groundnut producer after Brazil. An major crop of oilseeds is groundnuts. Because of this, the crop's quality and yield have declined, which has had a detrimental effect on the agricultural economy. This is partly b…
  crossref Usikela Naresh, T. Bhaskara Reddy 2023-09-29T22:11:15Z 置信度 0.70
• Review for "Spectral-Directed Electrostatics Strategy Integrated within a Graph Neural Network Approach for the Prediction of Nanocluster Structures"
  crossref 2026-08-03T11:54:42Z 置信度 0.70
• Reviewer #2 (Public Review): When and why does motor preparation arise in recurrent neural network models of motor control?
  crossref 2024-09-24T10:16:12Z 置信度 0.70
• Review for "Performance enhancement of the artificial neural network–based reinforcement learning for wind turbine yaw control"
  crossref 2019-11-26T06:09:51Z 置信度 0.70
• Review for "Modelling a chemical plant using grey‐box models employing the support vector regression and artificial neural network"
  crossref 2024-07-24T17:09:51Z 置信度 0.70
• Review for "A medium‐weight deep convolutional neural network‐based approach for onset epileptic seizures classification in EEG signals"
  crossref 2022-10-05T17:02:17Z 置信度 0.70
• Breast cancer segmentation and classification in ultrasound images using convolutional neural network
  Abstract Breast most cancers is one of the main reasons of mortality in ladies throughout the world. Early detection contributes to a discount withinside the quantity of untimely fatalities. Using ultrasound (US) pics, we gift deep studying (DL) strategies for…
  crossref Shima Baniadam Dizaj, Pourya Valizadeh 2021-10-04T23:38:22Z 置信度 0.70
• The role of dimensionality in a threshold-controlled neural network
  crossref A Hartstein 2002-08-25T02:35:54Z 置信度 0.70
• Sparsity-aware ternary neural networks for memristor crossbar computing
  crossref Tien Nguyen Van 2026-06-15T10:31:03Z 置信度 0.70
• Heart Disease Prediction Using Scaled Conjugate Gradient Back Propagation of Artificial Neural Network
  Abstract Heart disease is a deadly disease in human life. The mortality rate from any disease is the highest in the world. Therefore, before reaching the final stage of this heart disease, all precautionary measures must be taken. For this reason without the h…
  crossref BANIBRATA PAUL, Bhaskar Karn 2022-03-31T15:32:26Z 置信度 0.70
• Review for "Instance segmentation of on-line wear debris using deep convolutional neural network with transfer learning"
  crossref 2024-12-17T16:01:54Z 置信度 0.70
• Reviewer #3 (Public Review): When and why does motor preparation arise in recurrent neural network models of motor control?
  crossref 2024-08-13T11:26:10Z 置信度 0.70
• Review for "Cetyltrimethylammonium bromide Modified Magnetic Apricot Shells for Removing Congo Red Dye and its Artificial Neural Network Model"
  crossref 2025-02-21T16:14:11Z 置信度 0.70
• Review for "An improved custom convolutional neural network based hand sign recognition using machine learning algorithm"
  crossref 2024-03-20T17:19:55Z 置信度 0.70
• Review for "An adding‐points strategy surrogate model for well control optimization based on radial basis function neural network"
  crossref 2024-04-25T17:08:23Z 置信度 0.70
• Review for "Modelling a chemical plant using grey‐box models employing the support vector regression and artificial neural network"
  crossref 2024-07-24T17:09:51Z 置信度 0.70
• Peer Review #1 of "Ultrasonic based concrete defects identification via wavelet packet transform and GA-BP neural network (v0.2)"
  crossref 2021-09-06T12:43:57Z 置信度 0.70
• Fully parallel programming on 1k graphene interfacial memristor crossbar array for edge computing
  Abstract Fine-tuning pre-trained neural networks in resource-constrained environments demands ultra-low-power hardware capable of real-time response. Filamentary memristors show great promise in neural networks inference but suffer from stochastic switching, u…
  crossref Tania Roy 2026-01-08T17:43:27Z 置信度 0.70
• Step Network: A Neural Network that Takes Into Account Spatial Structure and Texture Features for Human Pose Transfer
  Abstract Portrait synthesis guided by pose presents a challenging frontier in image generation. In our latest research, we have introduced an innovative network called the Step network, specifically designed to overcome the limitations identified in previous w…
  crossref Han Mo, Yang Xu, Caideng Zhang, Yongdan Zhang 2024-03-19T20:24:36Z 置信度 0.70
• Wafer‐Scale 2D Hafnium Diselenide Based Memristor Crossbar Array for Energy‐Efficient Neural Network Hardware
  Abstract Memristor crossbar with programmable conductance could overcome the energy consumption and speed limitations of neural networks when executing core computing tasks in image processing. However, the implementation of crossbar array (CBA) based on ultra…
  crossref Sifan Li, Mei‐Er Pam, Yesheng Li, Li Chen 等 2021-09-12T13:27:53Z 置信度 0.70
• Network Architecture Search Method on Hyperparameter Optimization of Convolutional Neural Network: Review
  crossref Hudalizaman, Igi Ardiyanto, Sunu Wibirama 2022-03-17T20:52:50Z 置信度 0.70
• Classifying Artificial Neural Network Architecture
  crossref J. P. Evans 2013-12-08T22:06:39Z 置信度 0.70
• Efficient Techniques for Extending Service Time for Memristor-based Neural Networks
  crossref Yu Ma, Chengrui Zhang, Pingqiang Zhou 2022-02-02T22:03:05Z 置信度 0.70
• Performance of Artificial Neural Network and Physics-Informed Neural Networks for Flexural Strength Using Sugarcane Bagasse Ash and Distilled Sewage Water 
  Abstract An increasing number of eco-conscious construction projects are looking to agricultural waste products, such as sugarcane bagasse ash (SCBA) and Distilled Sewage Water, to partially replace cement and Pure Water in their mixes. This study evaluates th…
  crossref Mayuri Ahirrao, Rakesh Patel, Chaitanya Mishra 2026-03-26T04:51:15Z 置信度 0.70
• Neural network models of list learning
  crossref Neil Burgess, J Shapiro, M Moore 2002-08-25T02:35:54Z 置信度 0.70
• Neural Network Reliability
  crossref 2007-10-28T04:36:19Z 置信度 0.70
• Enhancing Neural Network Prediction against Unknown Disturbances with Neural Network Disturbance Observer
  crossref Maxime Pouilly-Cathelain, Philippe Feyel, Gilles Duc, Guillaume Sandou 2019-08-09T05:20:20Z 置信度 0.70