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• BITLITE: Light Bit-wise Operative Vector Matrix Multiplication for Low-Resolution Platforms
  preprints 2024 置信度 0.74
• SAFMem: Accelerating Transformer Self-Attention Functionality via Memristor-Based Hardware
  preprints 2023 置信度 0.74
• Nonlinear Memristive Computational Spectrometer
  preprints 2024 置信度 0.74
• Comparative Analysis of Proposed Artificial Neural Network (ANN) Algorithm With Other Techniques
  The mortality rate among women is increasing progressively due to cancer. Generally, women around 45 years old are vulnerable from this disease. Early detection is hope for patients to survive otherwise it may reach to unrecoverable stage. Currently, there are…
  crossref Deepak Chatha, Alankrita Aggarwal, Rajender Kumar 2021-09-17T11:47:50Z 置信度 0.70
• Neural Network Approaches to Color Vision
  crossref ANYA C. HURLBERT 2014-07-01T11:41:47Z 置信度 0.70
• Flexible Neural Probe with an Optimized Electrode Density for Neural Network Investigations
  crossref 2025-06-11T15:21:50Z 置信度 0.70
• Global Mittag-Leffler synchronization of discontinuous memristor-based fractional-order fuzzy inertial neural networks with mixed delays
  crossref Haihe Pan, Chengdai Huang, Jinde Cao, Heng Liu 2025-01-24T03:56:51Z 置信度 0.70
• The influence of neural activity and intracortical connectivity on the periodicity of ocular dominance stripes
  crossref Geoffrey J Goodhill 2015-08-18T20:04:56Z 置信度 0.70
• Neural implementation of a method for solving systems of linear equations
  crossref A B Forbes, A J Mansfield 2015-08-18T20:04:03Z 置信度 0.70
• SmooNet: Smooth operator neural network and functional differential equation
  crossref Ruiyan Luo, Xin Qi 2026-02-12T16:43:47Z 置信度 0.70
• Tampa Electric Neural Network Sootblowing
  crossref Mark A. Rhode 2007-03-14T02:24:41Z 置信度 0.70
• 2004 Seventh Seminar on Neural Network Applications in Electrical Engineering - NEUREL 2004 - Title Page
  crossref 2011-06-01T13:01:21Z 置信度 0.70
• Benchmarking Convolutional Neural Network and Graph Neural Network Based Surrogate Models on a Real-World Car External Aerodynamics Dataset
  crossref Sam Jacob Jacob, Markus Mrosek, Carsten Othmer, Harald Köstler 2025-04-26T14:36:53Z 置信度 0.70
• Plant Leaf Perception Using Convolutional Neural Network
  crossref Eldho Paul 2020-04-30T17:30:42Z 置信度 0.70
• Embedding-Based Deep Neural Network and Convolutional Neural Network Graph Classifiers
  One of the most significant graph data analysis tasks is graph classification, as graphs are complex data structures used for illustrating relationships between entity pairs. Graphs are essential in many domains, such as the description of chemical molecules, …
  crossref Sarah G. Elnaggar, Ibrahim E. Elsemman, Taysir Hassan A. Soliman 2023-06-19T01:59:51Z 置信度 0.70
• Efficient Low-Bit Neural Network With Memristor-Based Reconfigurable Circuits
  crossref He Xiao, Xiaofang Hu, Tongtong Gao, Yue Zhou 等 2023-07-26T18:56:55Z 置信度 0.70
• Dual Memristor-Coupled Hopfield Neural Network With Any Multi-Scroll Amplitude Control and Its Application for Medical Image Classification
  crossref Sen Zhang, Dazhe He, Yongxin Li, Daorong Lu 等 2025-07-04T13:53:18Z 置信度 0.70
• Quantifying variability in neural responses and its application for the validation of model predictions
  crossref Anne Hsu, Alexander Borst, Frédéric Theunissen 2004-04-22T03:14:09Z 置信度 0.70
• Robustness of cellular neural network implementations
  crossref Kwok Fai Hui 2014-12-20T01:25:21Z 置信度 0.70
• Toward Efficient Rendering: A Neural Network Approach
  crossref Qiqi Hou 2023-05-04T22:38:56Z 置信度 0.70
• Practical Neural Network Recipies in C++
  crossref 2016-08-03T21:21:39Z 置信度 0.70
• Spreadsheet simulation of artificial neural network
  crossref R. Antonini 2002-12-09T23:24:26Z 置信度 0.70
• Vapnik-Chervonenkis Dimension Bounds for Neural Networks
  crossref 2010-03-02T18:08:05Z 置信度 0.70
• Convolutional neural network architectures for CAFA4
  Introduction The Critical Assessment of protein Function Annotation (CAFA) challenge concerns the prediction of annotated ontology terms for given protein sequences [Radivojac et al., 2013]. In the current CAFA 4 challenge, the goal is to predict terms from th…
  crossref Jari Björne 2025-11-21T21:17:08Z 置信度 0.70
• A neural-network-based approach for routing in a packet switching network
  crossref S. Cavalieri, A. di Stefano, O. Mirabella 2003-01-02T16:19:33Z 置信度 0.70
• Competitive learning, natural images and cortical cells
  crossref C Webber 2002-08-24T22:35:54Z 置信度 0.70
• Accelerating gas-network feasibility screening with a physics-informed graph neural network surrogate
  Large-scale gas-network scenario evaluation is a computational bottleneck in integrated energy-system planning, particularly when gas infrastructure interacts with power, heat, hydrogen, and sector-coupling pathways. Conventional nonlinear hydraulic solvers pr…
  crossref Dongrui Jiang 2026-06-04T12:43:42Z 置信度 0.70
• Towards an event-space self-configurable neural network
  crossref D.K.Y. Chiu 2002-12-30T17:49:31Z 置信度 0.70
• Comparison of Artificial Neural Network Architectures and Training Algorithms for Solving the Knight's Tours
  crossref R.G. Escalante, H.A. Malki 2006-10-30T17:35:23Z 置信度 0.70
• A New Unsupervised Neural Network for Pattern Recognition with Spiking Neurons
  crossref R. Lorenzo, R. Riccardo, C. Antonio 2008-07-18T15:34:22Z 置信度 0.70
• FPGA implementation of neural network as processing element in ice detector
  crossref Matteo Marouf, Jelena Popovic-Bozovic, Ivan Popovic 2013-01-31T12:22:27Z 置信度 0.70
• Analyzing Intraductal Papillary Mucinous Neoplasms Using Artificial Neural Network Methodologic Triangulation
  Intraductal papillary mucinous neoplasms (IPMN) are a type of mucinous pancreatic cyst. IPMN have been shown to be pre-malignant precursors to pancreatic cancer, which has an extremely high mortality rate with average survival less than 1 year. The purpose of …
  crossref Steven Walczak, Jennifer B. Permuth, Vic Velanovich 2021-09-17T11:47:50Z 置信度 0.70
• Neural network learning of optimal Kalman prediction and control
  crossref Ralph Linsker 2008-05-29T06:22:56Z 置信度 0.70
• Supplemental Information 1: Code for the Pix2Pix Neural Network.
  crossref 2024-09-23T03:33:33Z 置信度 0.70
• Supplemental Information 1: Working of Recurrent Neural Network (RNN).
  crossref 2025-08-22T08:06:20Z 置信度 0.70
• Neural Network Modeling of Executive Functioning with the Tower of Hanoi Test in Frontal Lobe-Lesioned Patients
  crossref 2018-12-14T02:49:52Z 置信度 0.70
• Computerised Tuberculosis Detection Using Artificial Neural Network
  crossref 2016-04-28T07:20:51Z 置信度 0.70
• COVID ‐19 vs influenza viruses: A cockroach optimized deep neural network classification approach
  crossref 2021-03-08T01:44:30Z 置信度 0.70
• Accelerating neural network training using weight extrapolations
  crossref S.V. Kamarthi, S. Pittner 2002-07-25T12:59:42Z 置信度 0.70
• Time Intervals Comparing Neural Network
  crossref JURAJ PAVLÁSEK, JURAJ POLEDNA, FEDOR JAGLA 2002-07-25T23:57:31Z 置信度 0.70
• Logarithmic learning for generalized classifier neural network
  crossref Buse Melis Ozyildirim, Mutlu Avci 2014-08-19T13:01:22Z 置信度 0.70
• A methodology to explain neural network classification
  crossref Raphael Féraud, Fabrice Clérot 2002-07-25T10:36:15Z 置信度 0.70
• Design and Implementation of Series-Parallel Connectable Memristor Simulators Based on Combination of Virtuality and Reality
  crossref Yijia Chen, Penghao Liu, Michel Kadoch 2025-04-23T17:50:59Z 置信度 0.70
• Cellular Nonlinear Networks with Memristor Synapses
  crossref Fernando Corinto, Alon Ascoli, Young-Su Kim, Kyeong-Sik Min 2019-11-12T22:03:43Z 置信度 0.70
• Neural Network with Principal Component Analysis for Malware Detection using Network Traffic Features
  crossref Ventje Jeremias Lewi Engel, Mychael Maoeretz Engel, Evan Joshua 2020-07-10T16:45:02Z 置信度 0.70
• Neural network accelerator for quantum control
  crossref David Xu, A. Barış Özgüler, Giuseppe Di Guglielmo, Nhan Tran 等 2023-03-08T03:26:52Z 置信度 0.70
• COVID ‐19 vs influenza viruses: A cockroach optimized deep neural network classification approach
  crossref 2021-03-07T20:45:23Z 置信度 0.70
• A Dynamic Neural Network-based Reaction Wheel Fault Diagnosis for Satellites
  crossref Z.Q. Li, L. Ma, K. Khorasani 2008-07-18T11:34:22Z 置信度 0.70
• Hybrid Convolutional Neural Network with Residual Neural Network for Breast Cancer Prediction Using Mammography Images
  crossref 2022-12-29T20:00:39Z 置信度 0.70
• Exploiting prior knowledge in network optimization: an illustration from medical prognosis
  crossref David Lowe, Andrew R Webb 2015-08-18T20:04:02Z 置信度 0.70
• Leap-frog is a robust algorithm for training neural networks
  crossref Johann E W Holm, Elizabeth C Botha 2015-08-18T20:03:49Z 置信度 0.70
• A Multi-layer ADaptive FUnction Neural Network (MADFUNN) for Analytical Function Recognition
  crossref Miao Kang, D. Palmer-Brown 2008-07-18T15:34:22Z 置信度 0.70
• Beats, kurtosis and visual coding
  crossref M.G.A. Thomson 2009-12-09T01:33:28Z 置信度 0.70
• Hybrid Tensor Network and Neural Network Quantum States for Quantum Chemistry
  crossref 2025-10-09T14:40:41Z 置信度 0.70
• Figure 3: Sleep scoring performance of artificial neural network.
  crossref 2021-09-09T03:43:31Z 置信度 0.70
• Workshop on Neural Network Applications and Tools
  crossref 2020-02-05T15:33:16Z 置信度 0.70
• A neural network model of Borderline Personality Disorder
  crossref Carl H. Berdahl 2009-11-12T05:35:33Z 置信度 0.70
• Demonstration of Neuromodulation‐inspired Stashing System for Energy‐efficient Learning of Spiking Neural Network using a Self‐Rectifying Memristor Array (Adv. Funct. Mater. 29/2022)
  crossref Woon Hyung Cheong, Jae Bum Jeon, Jae Hyun In, Geunyoung Kim 等 2022-07-18T08:39:23Z 置信度 0.70
• Towards Optical Memristor-Based Cellular Neural Networks
  crossref I. Messaris, D. Prousalis, A. S. Demirkol, R. Tetzlaff 等 2026-07-31T18:16:20Z 置信度 0.70
• Design of a memristor-based neuron for spiking neural networks
  The primary objective of neuromorphic system design is to surpass limitations in energy efficiency and scaling of classical von Neumann computing systems, through the emulation of animals’ nervous systems. This is achieved by conducting calculations in memory …
  crossref V. Yu. Ostrovskii, O. S. Druzhina, O. Kamal, T. I. Karimov 等 2024-05-06T08:05:41Z 置信度 0.70
• Non-ideal memristor synapse-coupled bi-neuron Hopfield neural network: Numerical simulations and breadboard experiments
  crossref Chengjie Chen, Han Bao, Mo Chen, Quan Xu 等 2019-08-31T10:58:38Z 置信度 0.70
• Dual-function Sb2S3/HfO2 memristor for reservoir computing and neural network learning via decoupled short- and long-term memory
  Conventional computing architectures typically rely on separate devices to achieve dynamic sensing and long-term storage, leading to low integration density, high energy consumption, and significant data movement bottlenecks. Here, a biomimetic dual-function m…
  crossref Mengru Song, Lele Li, Han Gu, Ziyang Hu 等 2026-03-09T13:16:47Z 置信度 0.70
• Oscillatory neural network and learning of continuously transformed patterns
  crossref Yukio Hayashi 2003-04-25T03:25:55Z 置信度 0.70
• A general regression neural network
  crossref D.F. Specht 2002-08-24T15:16:32Z 置信度 0.70
• Attractor neural networks with excitatory neurons and fast inhibitory interneurons at low spike rates
  crossref Anthony N Burkitt 2015-08-18T16:04:14Z 置信度 0.70
• Learning stable, regularised latent models of neural population dynamics
  crossref Lars Buesing, Jakob H. Macke, Maneesh Sahani 2018-04-30T12:13:42Z 置信度 0.70
• Cellular Nonlinear Networks with Memristor Synapses
  crossref Fernando Corinto, Alon Ascoli, Young-Su Kim, Kyeong-Sik Min 2013-12-18T10:27:01Z 置信度 0.70
• Memristor-based Reservoir Computing
  crossref Manjari Kulkarni 2017-01-20T20:14:44Z 置信度 0.70
• Tampa Electric Neural Network Sootblowing
  crossref Mark A. Rhode 2007-04-09T17:10:21Z 置信度 0.70
• Table 3: Performance comparison with other neural network methods.
  crossref 2022-08-30T03:45:01Z 置信度 0.70
• Figure 5: The neural network architecture of E-MFNN.
  crossref 2024-04-19T03:43:31Z 置信度 0.70
• Neural Network: A to Z
  An artificial neural network is a basic building block for deep learning. Understanding the neural network and making intuitive sense of them is a major challenge for anyone who wants to use them. This is partly due to incomplete articles and highly technical …
  crossref Ayush Singh 2021-04-02T23:03:45Z 置信度 0.70
• Figure 4: Simple neural network with activation function “relu”.
  crossref 2025-04-07T04:48:57Z 置信度 0.70
• MLNAS: Meta-learning based neural architecture search for automated generation of deep neural networks for plant disease detection tasks
  crossref Sahil Verma, Prabhat Kumar, Jyoti Prakash Singh 2024-07-12T06:09:53Z 置信度 0.70
• Dynamics of neural networks with non-monotone activation function
  crossref P De Felice, C Marangi, G Nardulli, G Pasquariello 等 2002-08-24T22:35:54Z 置信度 0.70
• Memristor-Based Neural Network Circuit of Learning Conflict and Context-Dependent Memory and Its Application in Intelligent Nursing
  crossref Kefan Tao, Yanfeng Wang 2026-03-23T20:07:18Z 置信度 0.70
• Neural Network-Based Decoding Input Stimulus Data Based on Recurrent Neural Network Neural Activity Pattern
  Abstract The paper reports the assessment of the possibility to recover information obtained using an artificial neural network via inspecting neural activity patterns. A simple recurrent neural network forms dynamic excitation patterns for storing data on inp…
  crossref S. I. Bartsev, P. M. Baturina, G. M. Markova 2022-03-17T04:04:56Z 置信度 0.70
• Stability criteria for the contextual emergence of macrostates in neural networks
  crossref Peter beim Graben, Adam Barrett, Harald Atmanspacher 2009-09-03T22:56:54Z 置信度 0.70
• Function matrix projection synchronization for the multi-time delayed fractional order memristor-based neural networks with parameter uncertainty
  crossref Jin-Man He, Li-Jun Pei 2023-05-17T13:27:48Z 置信度 0.70
• Passivity analysis of memristor-based recurrent neural networks with time-varying delays
  crossref Shiping Wen, Zhigang Zeng, Tingwen Huang, Yiran Chen 2013-06-05T00:04:00Z 置信度 0.70
• The importance of different timings of excitatory and inhibitory pathways in neural field models
  crossref Carlo Laing, Stephen Coombes 2006-05-25T20:08:33Z 置信度 0.70
• Retrieval properties of attractor neural networks that obey Dale's law using a self-consistent signal-to-noise analysis
  crossref Anthony Burkitt 2002-08-24T22:35:54Z 置信度 0.70
• CONTRIBUTORS
  crossref 2014-07-01T08:04:18Z 置信度 0.70
• Dedication
  crossref 2014-07-01T04:02:55Z 置信度 0.70
• Memristor Models for Pattern Recognition Systems
  crossref Fernando Corinto, Alon Ascoli, Marco Gilli 2012-06-27T17:03:30Z 置信度 0.70
• Tampa Electric Neural Network Sootblowing
  crossref Mark A. Rhode 2007-08-03T13:32:47Z 置信度 0.70
• Table 5: Convolutional neural network summary on blink detection.
  crossref 2025-01-14T03:30:26Z 置信度 0.70
• Federated graph neural network-based recommender systems
  crossref Liang Qu 2024-11-18T17:28:11Z 置信度 0.70
• Pinning synchronization of memristor-based neural networks with time-varying delays
  crossref Zhanyu Yang, Biao Luo, Derong Liu, Yueheng Li 2017-05-18T14:02:16Z 置信度 0.70
• A neural network approach to speech recognition
  crossref Y.C. Lee, H.H. Chen, G.Z. Sun 2003-04-25T05:05:53Z 置信度 0.70
• Image Steganography of convolutional neural network based on neural architecture search
  Abstract Recent studies show that the performance of deep convolutional neural network (CNN) applied to Steganography is better than that of traditional methods. We propose NAS-Stego to solve the problem of static network structure of the model in steganograph…
  crossref Yanger Meng, Jingtao Li 2022-11-07T14:41:15Z 置信度 0.70
• Orthogonal RBF Neural Network Approximation
  crossref Péter András 2003-02-19T20:24:24Z 置信度 0.70
• Memristor-Based Multilayer Neural Networks With Online Gradient Descent Training
  crossref Daniel Soudry, Dotan Di Castro, Asaf Gal, Avinoam Kolodny 等 2015-01-14T19:43:06Z 置信度 0.70
• ON NEURAL NETWORK ALGORITHM FOR GRAPH MATCHING
  crossref Igor Yu. POTERYAIKO 2014-07-01T02:49:16Z 置信度 0.70
• Linear conductance update improvement of CMOS-compatible second-order memristors for fast and energy-efficient training of a neural network using a memristor crossbar array
  The linear conductance update of a CMOS-compatible HfO 2 memristor is improved by introducing a second-order memristor effect and connecting a voltage divider to the device, which makes the memristor crossbar array more energy- and time-efficient.
  crossref See-On Park, Taehoon Park, Hakcheon Jeong, Seokman Hong 等 2023-06-27T02:02:25Z 置信度 0.70
• H_∞ State Estimation of Memristor-based Recurrent Neural Networks with Mixed Delay
  crossref Xiangxiang Wang, Yongbin Yu, Nijing Yang, Haowen Tang 等 2019-08-23T00:18:44Z 置信度 0.70
• New Criteria of Event-triggered Exponential State Estimation for Delayed semi-Markovian Memristor-based Neural Networks
  crossref Xiaoman Liu, Lianglin Xiong, Haiyang Zhang, Jinde Cao 2023-03-27T02:01:15Z 置信度 0.70
• Adaptive Synchronization for Delayed Chaotic Memristor-Based Neural Networks
  crossref Youming Xin, Zunshui Cheng 2021-07-26T21:27:21Z 置信度 0.70
• A neural net model of the adaptation of binocular vertical eye alignment
  crossref Jeffrey W Mccandless, Clifton M Schor 2015-08-18T20:05:00Z 置信度 0.70
• Fault simulation of a wafer-scale integrated neural network
  crossref N. May, D. Hammerstrom 2003-04-25T01:05:53Z 置信度 0.70