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• Incremental Gain Analysis of Chaotic Recurrent Neural Network and Applications in Pattern Association
  crossref Wu Yilei, Song Qing, Liu Sheng 2006-10-30T17:35:23Z 置信度 0.70
• Recurrent Neural Network Based Gating for Natural Gas Load Prediction System
  crossref P. Musilek, E. Pelikan, T. Brabec, M. Simunek 2006-10-30T17:35:23Z 置信度 0.70
• Neural Network Black Box Modeling of Nonlinear Dynamical Systems: Aircraft Controlled Motion
  crossref Yury V. Tiumentsev, Mikhail V. Egorchev 2019-06-21T11:36:07Z 置信度 0.70
• Behavior of Multiple Memristor Circuits
  crossref Ram Kaji Budhathoki, Maheshwar Pd. Sah, Shyam Prasad Adhikari, Hyongsuk Kim 等 2019-11-12T17:03:43Z 置信度 0.70
• Functional Capabilities of Coupled Memristor-Based Reactance-Less Oscillators
  New functionalities of reactance-less memristor based oscillators are discussed which arise when two elementary oscillators are connected. It is shown that the system of coupled memristor based oscillators can be used for converting analog and analog-digital s…
  crossref Vladimir V. Rakitin, Sergey G. Rusakov 2021-05-28T08:19:49Z 置信度 0.70
• Hebbian learning, its correlation catastrophe, and unlearning
  crossref J van Hemmen 2002-09-18T03:15:26Z 置信度 0.70
• HYBRID NEURAL NETWORK-PARTICLE SWARM ALGORITHM TO DESCRIBE CHAOTIC TIME SERIES
  crossref Juan A. Lazzús, Ignacio Salfate, Sonia Montecinos 2015-01-22T04:02:26Z 置信度 0.70
• Memristor-Based Immune Neural Network Circuit With Neuromorphic Learning and Self-Repairing and its Application in Industrial Fault Diagnosis
  crossref Kefan Tao, Yanfeng Wang, Junwei Sun 2026-05-13T19:53:30Z 置信度 0.70
• Methods for the selection of parameters and structure of the neural network model
  crossref Dmitriy Tarkhov, Alexander Vasilyev 2019-11-29T11:14:11Z 置信度 0.70
• A new neural network-intelligence increasing neural network
  crossref Ni Zheng, Su Guang-da, Wang Jun-yan 2004-07-08T20:06:22Z 置信度 0.70
• Artificial Neural Network for Pre-Simulation Training of Air Traffic Controller
  In this chapter, the four layers neural network model for evaluating correctness and timeliness of decision making by the specialist of air traffic services during the pre-simulation training has been presented. The first layer (input) includes exercises that …
  crossref Tetiana Shmelova, Yuliya Sikirda, Togrul Rauf Oglu Jafarzade 2021-09-17T11:47:50Z 置信度 0.70
• Stability analysis of stochastic Lyapunov functions: Applications to memristor neural networks
  This paper investigates the mean square exponential stability of stochastic neural networks relying on memristor with leakage delay with different types of activation functions. To this aim, we introduce a new suitable stochastic Lyapunov‐Krasovskii functional…
  crossref Vaz'he Rahimi, Davood Ahmadian 2025-01-09T05:11:04Z 置信度 0.70
• Training, Programming, and Correction Techniques of Memristor-Crossbar Neural Networks with Non-Ideal Effects such as Defects, Variation, and Parasitic Resistance
  crossref Tien Van Nguyen, Jiyong An, Seokjin Oh 2021-12-01T20:53:36Z 置信度 0.70
• 忆阻神经网络自适应滑模控制及其应用
  crossref 林俤 LIN Di, 吴易明 WU Yiming, 杨森 YANG Sen, 张垠 ZHANG Yin 等 2025-11-14T08:00:42Z 置信度 0.70
• Do cortical maps adapt to optimize information density?
  crossref M Plumbley 2002-08-24T22:35:54Z 置信度 0.70
• Neuroanatomical algorithms for dendritic modelling
  crossref Giorgio A Ascoli 2015-08-18T16:03:55Z 置信度 0.70
• Comparative study of artificial neural network and physics-informed neural network application in sheet metal forming
  Abstract. Accurate prediction of the resultant geometry in sheet metal forming simulation is necessary to achieve zero-defect production. To quantify the effect of process parameters on the final geometry, numerical methods are used to simulate the process out…
  crossref Francesco MUNZONE 2024-04-19T16:10:26Z 置信度 0.70
• Global dynamics of a network of stochastic neurons maximizes local mutual information
  crossref F.B. Rodrguez, R. Huerta, V. Lpez 2009-12-08T20:33:27Z 置信度 0.70
• A switching control for finite-time synchronization of memristor-based BAM neural networks with stochastic disturbances
  This paper deals with the finite-time stochastic synchronization for a class of memristorbased bidirectional associative memory neural networks (MBAMNNs) with time-varying delays and stochastic disturbances. Firstly, based on the physical property of memristor…
  crossref Liangchen Li, Rui Xu, Qintao Gan, Jiazhe Lin 2020-11-01T08:05:47Z 置信度 0.70
• Connectionist technique for on-line parsing
  crossref Ronan Reilly 2015-08-18T20:04:17Z 置信度 0.70
• Noise modulation of synaptic weights in a biological neural network
  crossref Daniel Gardner 2003-04-25T05:05:53Z 置信度 0.70
• Medical Image Segmentation using a Self-organizing Neural Network and Clifford Geometric Algebra
  crossref J. Rivera-Rovelo, E. Bayro-Corrochano 2006-10-30T12:35:23Z 置信度 0.70
• Decision letter for "In-Situ Detection of Microplastic Particles on Food Using Hyperspectral Imaging with one-dimensional convolutional neural network (1D-CNN) and artificial neural network (ANN)"
  crossref 2026-01-23T21:04:57Z 置信度 0.70
• Implementing Synaptic Plasticity in a VLSI Spiking Neural Network Model
  crossref J. Schemmel, A. Grubl, K. Meier, E. Mueller 2008-07-18T15:27:21Z 置信度 0.70
• Forecasting Time Series with a New Architecture for Polynomial Artificial Neural Network
  crossref A. Flores-Mendez, E. Gomez-Ramirez 2008-07-18T15:34:22Z 置信度 0.70
• Using computation to help relate neurobiology and behaviour
  crossref J Movshon 2002-09-18T03:15:26Z 置信度 0.70
• Minimum-entropy coding with Hopfield networks
  crossref H Hentschel, H Barlow 2002-08-24T22:35:54Z 置信度 0.70
• Multilayer Neural Network based on Multi-Valued Neurons and the Blur Identification Problem
  crossref I. Aizenberg, D. Paliy, J.T. Astola 2006-10-30T12:35:23Z 置信度 0.70
• Hebbian learning, its correlation catastrophe, and unlearning
  crossref J van Hemmen 2002-08-25T02:35:54Z 置信度 0.70
• Power transformer differential protection scheme based on symmetrical component and artificial neural network
  crossref H. Khorashadi-Zadeh 2005-04-12T10:25:58Z 置信度 0.70
• DNNA: A Digital Neural Network Architecture
  crossref Max Stanford Tomlinson, Dennis J. Walker 2013-12-09T03:06:39Z 置信度 0.70
• Mechanism for automated neural network based transport system with learning
  crossref T. Srinivasan, J.B.S. Jonathan, A. Chandrasekhar 2005-04-12T10:25:58Z 置信度 0.70
• A cell assembly model of language
  crossref Friedemann Pulvermüller, Hubert Preibl 2002-08-24T22:35:54Z 置信度 0.70
• A Neural Network Architecture for Visual Selection
  This article describes a parallel neural net architecture for efficient and robust visual selection in generic gray-level images. Objects are represented through flexible star-type planar arrangements of binary local features which are in turn star-type planar…
  crossref Yali Amit 2002-07-27T11:57:56Z 置信度 0.70
• Control for neural prostheses: neural networks for determining biological synergies
  crossref P.B. Dejan, P.B. Mirjana 2003-06-26T00:51:07Z 置信度 0.70
• Automatic spleen segmentation in MRI images using a combined neural network and recursive watershed transform
  crossref Alireza Behrad, Hassan Masoumi 2010-12-09T15:34:50Z 置信度 0.70
• Alzheimer’s disease
  crossref Adam Gazzaley, Scott A. Small 2018-04-30T12:15:08Z 置信度 0.70
• The pi-sigma network: an efficient higher-order neural network for pattern classification and function approximation
  crossref Y. Shin, J. Ghosh 2002-12-09T18:24:26Z 置信度 0.70
• Kruskal Szekeres generative adversarial network augmented deep autoencoder for colorectal cancer detection
  crossref Suresh Kumar Krishnamoorthy, Vanitha CN 2024-11-17T01:25:58Z 置信度 0.70
• A model of cortical associative memory based on a horizontal network of connected columns
  crossref Erik Fransén, Anders Lansner 2015-08-18T16:04:57Z 置信度 0.70
• Global dissipativity and finite-time synchronization of mixed time-varying delayed memristor-based neural networks with discontinuous activations
  In this paper, the matters of dissipativity and finite time synchronization for memristor-based neural networks (MNNs) with mixed time-varying discontinuities are investigated. Firstly, under the framework of extending Filippov differential inclusion theory, s…
  crossref Kaifang Fei, Minghui Jiang, Yadan Zhang 2020-10-20T10:53:38Z 置信度 0.70
• Globally asymptotic stability analysis for memristor‐based competitive systems of reaction–diffusion delayed neural networks
  The main aim of this investigation is to present a mathematical criterion that guarantees the global asymptotic stability of special class of nonlinear neural systems. Indeed, a memristor‐based competitive nonlinear reaction–diffusion Cohen–Grossberg neural ne…
  crossref Yousef Gholami 2023-06-26T10:01:22Z 置信度 0.70
• Learning viewpoint-invariant face representations from visual experience in an attractor network
  crossref Marian Stewart Bartlett, Terrence J Sejnowski 2015-08-18T20:04:53Z 置信度 0.70
• Parallel neural network simulation machine: Neuman
  crossref Nobuki Kajihara, Satoshi Matsushita, Toshiyuki Nakata, Nobuhiko Koike 2003-04-25T05:05:53Z 置信度 0.70
• Using Neural Networks to Classify Objects
  crossref Igor Livshin 2019-04-12T15:05:25Z 置信度 0.70
• Resource allocation using a constraint optimizing adaptive neural network
  crossref George W. Earle, Harold Szu 2003-04-25T01:05:53Z 置信度 0.70
• A neural network-like critic for reinforcement learning
  crossref Hiroshi Yamakawa, Yoichi Okabe 2002-07-25T09:54:11Z 置信度 0.70
• Study of real-time weld seam tracking visual image analysis using a neural network
  crossref 2003-04-25T05:05:53Z 置信度 0.70
• On the match tracking anomaly of the ARTMAP neural network
  crossref Guszti Bartfai 2002-07-25T23:57:31Z 置信度 0.70
• Autowaves in a Lattice of Memristor-Based Cells
  crossref Viet-Thanh Pham, Arturo Buscarino, Mattia Frasca, Luigi Fortuna 2019-11-12T22:03:43Z 置信度 0.70
• A Neural Network with Evolutionary Neurons
  crossref Alberto Alvarez 2003-03-15T13:06:01Z 置信度 0.70
• Global Mean Square Exponential Stability of Memristor-Based Stochastic Neural Networks with Time-Varying Delays
  crossref Xiao-Lin Xu 2017-12-22T22:20:11Z 置信度 0.70
• Understanding Travel Behavior: A Deep Neural Network and SHAP Approach to Mode Choice Determinants
  Understanding individual travel behavior is crucial for developing effective travel demand management strategies and informed transportation policies. This study investigates the factors influencing individuals’ mode choices by analyzing data from a comprehens…
  crossref Halil Çevik, Ondřej Přibyl, Shoaib Samandar 2024-12-27T13:28:39Z 置信度 0.70
• The Modified Differential Evolution and the RBF (MDE-RBF) Neural Network for Time Series Prediction
  crossref H. Dhahri, Adel.M. Alimi 2006-10-30T12:35:23Z 置信度 0.70
• Neural-Network-based Metalearning for Distributed Text Information Retrieval
  crossref Kin Keung Lai, Lean Yu, Shouyang Wang, Wei Huang 2008-07-18T15:34:22Z 置信度 0.70
• Intelligent Driver System Based on Convolutional Neural Network for Detecting Unsafe Driving Conditions
  crossref Prawira Putra, Yunianita Rahmawati 2025-12-05T06:30:59Z 置信度 0.70
• A memristor SPICE model for designing memristor circuits
  crossref Mohammad Mahvash, Alice C. Parker 2010-08-19T10:51:39Z 置信度 0.70
• Convergence properties of three spike-triggered analysis techniques
  crossref Liam Paninski12 2004-01-09T05:18:59Z 置信度 0.70
• Random field and tonotopy: Simulation of an auditory neural network
  crossref T. Herve, J. Demongeot 2003-04-25T05:05:53Z 置信度 0.70
• Coupled convolution layer for convolutional neural network
  crossref Kazutaka Uchida, Masayuki Tanaka, Masatoshi Okutomi 2018-05-16T12:11:24Z 置信度 0.70
• Behavior of Multiple Memristor Circuits
  crossref Ram Kaji Budhathoki, Maheshwar P. Sah, Shyam Prasad Adhikari, Hyongsuk Kim 等 2013-12-18T10:27:01Z 置信度 0.70
• A Memristor-Based Chaotic System with Boundary Conditions
  crossref Xiaofang Hu, Guanrong Chen, Shukai Duan, Gang Feng 2019-11-12T17:03:43Z 置信度 0.70
• Perception neural network versus fuzzy neural network for controlling the inverted pendulum
  crossref Mohamed A. Belal 2010-05-08T11:30:25Z 置信度 0.70
• The Time Adaptive Self-Organizing Map is a Neural Network Based on Artificial Immune System
  crossref H. Shah-Hosseini 2008-07-18T11:34:22Z 置信度 0.70
• On the classification of learning machines
  crossref Giorgio Parisi 2015-08-18T16:04:20Z 置信度 0.70
• Sensory coding in the natural environment
  crossref B Olshausen, P Reinagel 2004-01-09T05:18:59Z 置信度 0.70
• Improvement the classification of a nanocomposite using nanoparticules based on a meta-analysis study, Recurrent Neural Network and Recurrent Neural Network Monte-Carlo algorithms
  This paper may be the first meta-analysis that presents a comprehensive synthesis of scientific works spanning the last five years, focusing on methodologies and results related to the analysis of nanocomposite using nanoparticules. The primary objective is to…
  crossref Rania LOUKIL, Wejdene GAZEHI, Mongi BESBES 2024-04-14T08:17:05Z 置信度 0.70
• Decision letter for "Amorphous Ta<sub>2</sub>O<sub>5</sub> memristor with excellent self-selective and artificial synaptic properties for artificial neural networks"
  crossref 2025-05-16T17:06:47Z 置信度 0.70
• Global Stabilization of Fractional-Order Memristor-Based Neural Networks With Time Delay
  crossref Jia Jia, Xia Huang, Yuxia Li, Jinde Cao 等 2019-06-03T15:23:21Z 置信度 0.70
• Learning Hough Transform: A Neural Network Model
  A single-layered Hough transform network is proposed that accepts image coordinates of each object pixel as input and produces a set of outputs that indicate the belongingness of the pixel to a particular structure (e.g., a straight line). The network is able …
  crossref Jayanta Basak 2002-07-27T11:55:01Z 置信度 0.70
• Feedforward Neural Network Construction Using Cross Validation
  This article presents an algorithm that constructs feedforward neural networks with a single hidden layer for pattern classification. The algorithm starts with a small number of hidden units in the network and adds more hidden units as needed to improve the ne…
  crossref Rudy Setiono 2002-07-27T11:56:30Z 置信度 0.70
• A feedforward unitary equivariant neural network
  crossref Pui-Wai Ma, T.-H. Hubert Chan 2023-02-01T11:37:47Z 置信度 0.70
• Neocognitron: A hierarchical neural network capable of visual pattern recognition
  crossref Kunihiko Fukushima 2003-04-25T01:05:53Z 置信度 0.70
• Structural Properties of Proteins Predicted by Neural Networks
  crossref H. Bohr 2011-12-26T11:23:28Z 置信度 0.70
• Global asymptotic stability of Hopfield neural network involving distributed delays
  crossref Hongyong Zhao 2003-05-19T18:45:52Z 置信度 0.70
• A model-based neural network for transient signal processing
  crossref Leonid I. Perlovsky 2003-04-24T23:25:55Z 置信度 0.70
• Pattern classification by a condensed neural network
  crossref A Mitiche, M Lebidoff 2002-10-14T22:58:33Z 置信度 0.70
• A neural network model of Parkinson's disease bradykinesia
  crossref Vassilis Cutsuridis, Stavros Perantonis 2005-12-15T18:00:20Z 置信度 0.70
• Wavelet Differential Neural Network Observer
  crossref I. Chairez 2009-08-12T14:56:52Z 置信度 0.70
• A neural network model of causality
  crossref R. Sun 2002-08-24T19:16:32Z 置信度 0.70
• State space neural network. Properties and application
  crossref Jesús M. Zamarreño, Pastora Vega 2002-07-25T23:57:31Z 置信度 0.70
• A probabilistic neural network for earthquake magnitude prediction
  crossref Hojjat Adeli, Ashif Panakkat 2009-05-22T11:20:19Z 置信度 0.70
• Generic and Practical Emulators for the Current-Controlled Memristor Models
  crossref Abdullah G. Alharbi, Masud H. Chowdhury 2020-09-01T19:06:16Z 置信度 0.70
• Constraint optimization neural network for adaptive early vision
  crossref B. Furman, J. Liang, H. Szu 2003-04-25T01:05:53Z 置信度 0.70
• Analytical Calculation of Inference in Memristor-based Stochastic Artificial Neural Networks
  crossref Nicolas Bogun, Emilio Perez-Bosch Quesada, Eduardo Perez, Christian Wenger 等 2022-07-29T15:38:30Z 置信度 0.70
• Cluster-Type Conductive Path-Based Selector-Less 1r Memristor Array for Spiking Neural Networks
  crossref Ji Eun Kim, Suman Hu, Ju Young Kwon, Suk Yeop Chun 等 2025-01-28T07:45:48Z 置信度 0.70
• Memory capacity in neural network models: Rigorous lower bounds
  crossref Charles M Newman 2003-04-25T05:05:53Z 置信度 0.70
• Rational Function Neural Network
  In this paper we observe that a particular class of rational function (RF) approximations may be viewed as feedforward networks. Like the radial basis function (RBF) network, the training of the RF network may be performed using a linear adaptive filtering alg…
  crossref Henry Leung, Simon Haykin 2008-04-04T19:26:28Z 置信度 0.70
• Spoken Digits Classification Based on Spiking Neural Networks with Memristor-Based STDP
  crossref Danila Vlasov, Yury Davydov, Alexey Serenko, Roman Rybka 等 2023-08-25T17:17:05Z 置信度 0.70
• Decision letter for "Amorphous Ta<sub>2</sub>O<sub>5</sub> memristor with excellent self-selective and artificial synaptic properties for artificial neural networks"
  crossref 2025-05-16T17:06:47Z 置信度 0.70
• Ziksa: On-chip learning accelerator with memristor crossbars for multilevel neural networks
  crossref Abdullah M. Zyarah, Nicholas Soures, Lydia Hays, Robin B Jacobs-Gedrim 等 2017-09-28T16:33:32Z 置信度 0.70
• Novel impulse neural circuits for pulsed neural network
  crossref Jong-Han Shin 2005-08-24T17:15:33Z 置信度 0.70
• Unsupervised learning in hexagonal boron nitride memristor-based spiking neural networks
  Abstract Resistive random access memory (RRAM) is an emerging non-volatile memory technology that can be used in neuromorphic computing hardware to exceed the limitations of traditional von Neumann architectures by merging processing and memory units. Two-dime…
  crossref Sahra Afshari, Jing Xie, Mirembe Musisi-Nkambwe, Sritharini Radhakrishnan 等 2023-07-31T18:22:08Z 置信度 0.70
• Oscillatory Neural Network-Based Ising Machine Using 2D Memristors.
  europepmc 2024 置信度 0.80
• A neuromorphic processor with on-chip learning for beyond-CMOS device integration.
  europepmc 2025 置信度 0.80
• TCAD Simulation of Resistive Switching Devices: Impact of ReRAM Configuration on Neuromorphic Computing.
  europepmc 2024 置信度 0.80
• Layer ensemble averaging for fault tolerance in memristive neural networks.
  europepmc 2025 置信度 0.80
• Human somatosensory systems based on sensor-memory-integrated technology.
  europepmc 2024 置信度 0.80
• Towards mixed physical node reservoir computing: light-emitting synaptic reservoir system with dual photoelectric output.
  europepmc 2024 置信度 0.80
• Electronically Reconfigurable Memristive Neuron Capable of Operating in Both Excitation and Inhibition Modes.
  europepmc 2024 置信度 0.80