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• A Neural Network Approach to Rainfall Forecasting in Urban Environments
  crossref 2021-03-06T08:48:56Z 置信度 0.70
• Neural network models for vision
  crossref K. Fukushima 2004-06-22T16:27:43Z 置信度 0.70
• Convergence properties of a pulsed neural network
  crossref Mian, Cotter 2003-01-13T13:46:33Z 置信度 0.70
• Upgrading the JANET neural network by introducing a new storage buffer of working memory
  Recurrent neural networks (RNNs), along with long short-term memory networks (LSTMs), have been successfully used on a wide range of sequential data problems and have been entitled as extraordinarily powerful tools for learning and processing such data. Howeve…
  crossref Antonio Tolic, Biljana Mileva Boshkoska, Sandro Skansi 2024-02-27T07:58:30Z 置信度 0.70
• Designing receptive fields for highest fidelity
  crossref Daniel L Ruderman 2015-08-18T20:04:15Z 置信度 0.70
• Detection of Pathological Myopia Using Convolutional Neural Network
  crossref Ananth Kalyanasundaram 2020-04-28T14:58:51Z 置信度 0.70
• Neural-network prediction with noisy predictors
  crossref A.A. Ding 2002-08-24T19:16:32Z 置信度 0.70
• System Identification Using Discrete-Time Neural Networks
  System identification is the process of determining a dynamic model for an unknown system that can subsequently be used for feedback control purposes. On the other hand, state estimation involves determining the unknown internal states of a dynamic system. Sys…
  crossref 2020-12-02T00:22:01Z 置信度 0.70
• Nitrogenase Iron Protein Classification using CNN Neural Network
  crossref Amer Rez 2022-01-11T00:31:47Z 置信度 0.70
• NEUROEVOLUTION: A NEURAL NETWORK-ORIENTED OPTIMIZATION APPROACH
  NeuroEvolution refers to the use of evolutionary algorithms to optimize neural network parameters and, in some cases, network architectures. The provided document outlines the fundamental components of evolutionary computation when applied to neural networks, …
  crossref Kishu Gupta 2026-01-13T01:41:02Z 置信度 0.70
• New delay-dependent uniform stability criteria for fractional-order BAM neural networks with discrete and distributed delays
  crossref Shafiya Muthu 2025-03-26T10:27:47Z 置信度 0.70
• Improved neural network for checking the stability of multidimensional systems
  In this paper, the author's previous work is extended and a new neural network is utilized to solve the stability problem of multidimensional systems. In the original authors work the problem is transformed into an optimization problem. Using the DeCarlo-Strin…
  crossref Nikos E. Mastorakis, Valeri M. Mladenov, M. N. S. Swamy 2010-12-09T10:34:50Z 置信度 0.70
• In defence of single-electrode recordings
  As a physicist observing the empirical struggle of neurophysiology to penetrate the computational secrets of neo-cortex, one is struck by the coexistence of two extreme positions. One has it that the computations performed in neo-cortex are too complex to be a…
  crossref Daniel J Amit 2015-08-18T20:04:12Z 置信度 0.70
• PREDICTING THE DAILY TRAFFIC VOLUME FROM HOURLY TRAFFIC DATA USING ARTIFICIAL NEURAL NETWORK
  crossref Mohammed Saiful Alam Siddique, Shamsul Hoque 2017-07-13T08:13:38Z 置信度 0.70
• A simple white noise analysis of neuronal light responses
  A white noise technique is presented for estimating the response properties of spiking visual system neurons. The technique is simple, robust, efficient and well suited to simultaneous recordings from multiple neurons. It provides a complete and easily interpr…
  crossref E. J. Chichilnisky 2007-07-08T00:00:06Z 置信度 0.70
• Diagnostics of printed circuit boards based on neural network models
  crossref 2026-07-02T08:21:08Z 置信度 0.70
• Neural network integration in control system structures: a case study towards intelligent control by neural network integration
  crossref J. Zaprianov, T. Atanasova 2002-11-23T00:49:27Z 置信度 0.70
• Localized activity patterns in excitatory neuronal networks
  The existence of localized activity patterns, or bumps, has been investigated in a variety of spatially distributed neuronal network models that contain both excitatory and inhibitory coupling between cells. Here we show that a neuronal network with purely exc…
  crossref Jonathan Rubin, Amitabha Bose 2004-05-05T03:14:19Z 置信度 0.70
• Statistics of natural image categories
  In this paper we study the statistical properties of natural images belonging to different categories and their relevance for scene and object categorization tasks. We discuss how second-order statistics are correlated with image categories, scene scale and ob…
  crossref Antonio Torralba, Aude Oliva 2015-08-18T16:03:53Z 置信度 0.70
• Fig. 4. Cluster N 1 of the sensorimotor neural network
  crossref 2024-11-08T05:20:05Z 置信度 0.70
• Evolving Neural Network Architecture
  This work investigates the application of a stochastic search technique, evolutionary programming, for developing self-organizing neural networks. The chosen stochastic search method is capable of simultaneously evolving both network architecture and weights. …
  crossref John R. McDonnell, Don Waagen 2017-09-05T15:54:36Z 置信度 0.70
• Neural network channel equalization
  The authors present computer simulation results of the performance of conventional and perceptron-based equalizers in the presence of intersymbol interference (ISI), additive noise and co-channel interference (CCI). They show that a three-layer perceptron equa…
  crossref N.W.K. Lo, H.M. Hafez 2003-01-02T11:19:33Z 置信度 0.70
• Neural network techniques for multi-user demodulation
  Adaptive methods for demodulating multi-user communication in a direct-sequence spread-spectrum multiple-access (DS/SSMA) environment are investigated. Adaptive radial basis function (RBF) networks that operate with knowledge of only a subset of the system par…
  crossref U. Mitra, H.V. Poor 2002-12-30T22:49:31Z 置信度 0.70
• Neural signatures of motor memories emerge in neural network models
  Abstract Animals can learn and seamlessly perform a great number of behaviors. However, it is unclear how neural activity can accommodate new behaviors without interfering with those an animal has already acquired. Recent studies in monkeys performing motor an…
  crossref Joanna C Chang, Claudia Clopath, Juan A Gallego 2025-08-27T14:31:12Z 置信度 0.70
• Theory of the backpropagation neural network
  The author presents a survey of the basic theory of the backpropagation neural network architecture covering architectural design, performance measurement, function approximation capability, and learning. The survey includes previously known material, as well …
  crossref Hecht-Nielsen 2003-01-13T13:46:33Z 置信度 0.70
• A neural network that embeds its own meta-levels
  A recurrent neural network is presented which (in principle) can, besides learning to solve problems posed by the environment, also use its own weights as input data and learn new (arbitrarily complex) algorithms for modifying its own weights in response to th…
  crossref J. Schmidhuber 2002-12-30T17:49:31Z 置信度 0.70
• Memristor SPICE Modeling
  crossref Chris Yakopcic, Tarek M. Taha, Guru Subramanyam, Robinson E. Pino 2012-06-27T13:03:30Z 置信度 0.70
• On nonlinearity in neural encoding models applied to the primary visual cortex
  Within the regression framework, we show how different levels of nonlinearity influence the instantaneous firing rate prediction of single neurons. Nonlinearity can be achieved in several ways. In particular, we can enrich the predictor set with basis expansio…
  crossref Diego Vidaurre, Concha Bielza, Pedro Larrañaga 2018-04-30T12:15:08Z 置信度 0.70
• Probable networks and plausible predictions — a review of practical Bayesian methods for supervised neural networks
  Bayesian probability theory provides a unifying framework for data modelling. In this framework the overall aims are to find models that are well-matched to the data, and to use these models to make optimal predictions. Neural network learning is interpreted a…
  crossref David J C Mackay 2015-08-18T16:04:29Z 置信度 0.70
• A Hardware Emulator for Binary Neural Networks
  crossref Marcin Skubiszewski 2013-12-09T03:06:39Z 置信度 0.70
• On Fields of Inhibitory Influence in a Neural Network
  crossref F. Ratliff 2012-04-26T22:20:23Z 置信度 0.70
• Neural Network Simulation on the MasPar MP-1 Massively Parallel Processor
  crossref K. A. Grajski, G. Chinn, C. Chen, C. Kuszmaul 等 2013-12-08T22:06:39Z 置信度 0.70
• Protein classification using a neural network database system
  Neural networks are being applied to a widely expanding area of applications, including the biological applications of protein structure prediction and DNA sequence
  crossref Cathy H. Wu, Adisorn Epidemiology, Tzx-Chung Chang 2004-02-05T16:00:56Z 置信度 0.70
• An Innovative Air Purification Method and Neural Network Algorithm Applied to Urban Streets
  In the present work, multiphysics modeling was used to investigate the feasibility of a photocatalysis-based outdoor air purifying solution that could be used in high polluted streets, especially street canyons. The article focuses on the use of a semi-active …
  crossref Meryeme Boumahdi, Chaker El Amrani, Siegfried Denys 2021-09-17T11:47:50Z 置信度 0.70
• A Fuzzified Neural Fuzzy Inference Network that Learns from Linguistic Information
  A Fuzzified Takagi-Sugeno-Kang (TSK)-type Neural Fuzzy Inference Network (FTNFIN) for handling linguistic information is proposed in this paper. The inputs and outputs of FTNFIN may be fuzzy numbers with any shapes. The α-cut technique is used in input fuzzifi…
  crossref Chia-Feng Juang, C.-I. Lee, Tung-Jung Chan 2006-10-30T12:35:23Z 置信度 0.70
• Image Compression Using Back Propagation Neural Network
  Image compression technique is used to reduce the number of bits required in representing image, which helps to reduce the storage space and transmission cost. In the present research work back propagation neural network training algorithm has been used. Back …
  crossref Neha Jaiswal 2024-12-07T07:36:09Z 置信度 0.70
• Multivariate Parametrized Logistic Neural Network Approximation over Infinite Domains
  crossref George A. Anastassiou 2026-02-14T08:42:21Z 置信度 0.70
• On derivation of stagewise second-order backpropagation by invariant imbedding for multi-stage neural-network learning
  We present a simple, intuitive argument based on "invariant imbedding" in the spirit of dynamic programming to derive a stagewise second-order backpropagation (BP) algorithm. The method evaluates the Hessian matrix of a general objective function efficiently b…
  crossref E. Mizutani, S. Dreyfus 2006-10-30T17:35:23Z 置信度 0.70
• An Improved Myocardial Infarction Detection using Convolutional Neural Network and Graph Neural Network Algorithm
  Myocardial infarction (MI) is a crucial health problem and its mortality rate is higher than that of cancer. It is the damage and death of heart muscle from the sudden blockage of a coronary artery by a blood clot. Although lots of researches have been carried…
  crossref Opeyemi Aderiike Abisoye 2024-09-02T06:47:53Z 置信度 0.70
• Nonlinear System Identification Based on B-Spline Neural Network and Modified Particle Swarm Optimization
  Artificial neural networks, in particular, feedforward multilayer networks and basis function networks, have gradually established themselves as a usual tool in approximating complex nonlinear systems. B-spline networks, a type of basis function neural network…
  crossref L. dos Santos Coelho, R.A. Krohling 2006-10-30T17:35:23Z 置信度 0.70
• Rotated General Regression Neural Network
  A rotated general regression neural network is presented as an enhancement to the general regression neural network. A variable kernel estimate for multivariate densities is considered. A coordinate transformation is adopted which circumvent the difficulty of …
  crossref M. Gholamrezaei, K. Ghorbanian 2007-11-06T20:35:49Z 置信度 0.70
• Review for "The nonlinear autoregressive network with exogenous inputs (NARX) neural network to damp power system oscillations"
  crossref 2020-07-27T17:06:47Z 置信度 0.70
• Twofold type of backpropagation neural network
  Various types of neural networks have been introduced and those have been used in various areas. In some areas, those operate in a very good manner, but in another they don't. For example, Boltzmann machine and Hopfield network have better estimation and analo…
  crossref S. Sugiyama 2002-11-19T13:30:57Z 置信度 0.70
• Systolic Simulation of Hamming Neural Network
  The paper describes the systolic simulation of Hamming net algorithm. Systolic arrays creation methodology is based on Data Dependence Graphs analysis. The proposed implementation is focused on completely digital circuits. Input data is passed through the neur…
  crossref Jacek Mazurkiewicz 2013-03-11T00:11:40Z 置信度 0.70
• Feature Extraction Using an Unsupervised Neural Network
  crossref Nathan Intrator 2018-12-26T09:22:20Z 置信度 0.70
• Parallel neural network architectures
  Several parallel neural network (PNN) architectures are presented in this paper. PNNs can work parallelly and coordinately. The implementation of their training is much easier than that of a single NN. And there are many other attractive characteristics of PNN…
  crossref Wang Guoyin, Shi Hongbao 2002-11-19T13:30:57Z 置信度 0.70
• Review of Recently Progress on Neural Electronics and Memcomputing Applications in Intrinsic SiOx-Based Resistive Switching Memory
  crossref Cheng-Chih Hsieh, Yao-Feng Chang, Ying-Chen Chen, Xiaohan Wu 等 2018-04-05T06:33:36Z 置信度 0.70
• The projection neural network
  A novel neural network model, the projection neural network, is developed to overcome three key drawbacks of backpropagation-trained neural networks (BPNN), i.e., long training times, the large number of nodes required to form closed regions for classification…
  crossref G.D. Wilensky, N. Manukian 2003-01-02T11:19:33Z 置信度 0.70
• Inverse recall neural network model and feedback pattern recognition
  An inverse recall neural network model and a feedback pattern recognition method based on the model are proposed. The inverse recall neural network model is trained by the same method as that used for a typical multilayer feedforward model. The model can produ…
  crossref K. Yamada 2002-12-30T22:49:31Z 置信度 0.70
• A Structure for Neural Network Pattern Classifiers
  crossref Terrence L. Fine, Thomas W. Parks 2013-12-09T03:06:39Z 置信度 0.70
• Sequence learning in differentially activated dendrites
  Differentially activated areas of a dendrite permit the existence of zones with distinct rates of synaptic modification, and such areas can be individually accessed using a reference signal which localizes synaptic plasticity and memory trace retrieval to cert…
  crossref Bjørn Gilbert Nielsen 2015-08-18T20:03:55Z 置信度 0.70
• Neural Network Models
  The most recent development in distributional semantics is represented by models based on artificial neural networks. In this chapter, we focus on the use of neural networks to build static embeddings. Like random encoding models, neural networks incrementally…
  crossref 2023-09-07T00:06:44Z 置信度 0.70
• Table 3: The default neural network training parameters in AIMOS.
  crossref 2025-09-01T08:12:20Z 置信度 0.70
• Figure 5: A neural network that has a hidden layer.
  crossref 2025-04-07T04:48:57Z 置信度 0.70
• Medical Image Segmentation using a Self-organizing Neural Network and Clifford Geometric Algebra
  In this paper we present a method based on self-organizing neural networks to extract the shape of an object which is useful for segmentation tasks. For that, the method uses a set of transformations expressed as versors in the conformal geometric algebra fram…
  crossref J. Rivera-Rovelo, E. Bayro-Corrochano 2008-07-18T15:34:22Z 置信度 0.70
• Designing a Muscle like System Based on PID Controller and Tuned by Neural Network
  This paper presents a study on a muscle like system based on a PID controller tuned by a neural network. The approach is based on a non linear muscle model using system identification based on a NNARX (neural network autoregressive exogenous) structure. This m…
  crossref H.J. Serhan, C.G. Nasr, P. Henaff 2006-10-30T12:35:23Z 置信度 0.70
• CM-Net: a point cloud upsampling network based on adversarial neural network
  In the real-life application scenarios, the collected point clouds are often sparse, noisy and non-uniform, especially if the application is unable to capture the local spatial layout due to the lack of points. Thus, point cloud upsampling aims to transform sp…
  crossref Xiaomeng Li, Chung-Ming Own, Kaizhen Wu, Qian Sun 2021-09-20T21:27:41Z 置信度 0.70
• Content-based Video Adaptation in Low/Variable Bandwidth Communication Networks Using Adaptable Neural Network Structures
  In this paper, an adaptable neural network model is used for real time video delivery over communication networks of low and variable bandwidth, such as the wireless ones. The scheme performs video delivery in content domain in contrast to the previous approac…
  crossref A. Doulamis, G. Tziritas 2008-07-18T11:34:22Z 置信度 0.70
• Artificial Neural Network (ANN) in Network Reconfiguration for Improvement of Voltage Stability
  Issues related to power system voltage levels have become increasingly important issue during last two and half decades. In power networks, low voltage situations may result in the loss of stability, voltage collapse and eventually to cascading power outages. …
  crossref Dipu Sarkar, Joyanta Kumar Roy 2019-09-18T13:52:17Z 置信度 0.70
• Analysis of Stability in Rulkov Neural Networks with Fractional Orders and Asymmetric Memristor Synapses
  Fractional-order models effectively capture memory and hereditary effects in neural and nonlinear dy namical systems. Memristors are ideal components for modeling synaptic connections due to their ability to emulate plasticity and memory effects. Discrete mode…
  crossref Leila Eftekhari, Moein Khalighi, Saeid Abbasbandy 2026-07-04T01:08:59Z 置信度 0.70
• Algorithm 2 : Multi-swarm PSO for neural network weight update.
  crossref 2025-11-14T08:33:07Z 置信度 0.70
• GLOSSARY
  crossref 2014-07-01T08:04:20Z 置信度 0.70
• Evolving Neural Network Connectivity
  crossref J. R. McDonnell, D. Waagen 2017-08-31T18:15:42Z 置信度 0.70
• Intelligent Neural Network Systems and Evolutionary Learning
  Although several conventional methods (e.g., pruning techniques) exist that may be used to automatically determine neural network con€guration and weights, they are often susceptible to trapping at local optima and characteristically dependent on the initial n…
  crossref 2020-12-11T12:22:47Z 置信度 0.70
• A neural network for the evaluation of hemodynamic variables
  crossref Tom Pike, Robert A Mustard 2004-11-26T05:22:41Z 置信度 0.70
• A neural network to diagnose liver cancer
  A backpropagation neural network is designed to diagnose five classifications of hepatic masses: metastatic carcinoma, hepatoma (HCC), cavernous hemangioma, abscess, and cirrhosis. BrainMaker Professional version 2.5 software is used in this research. The inpu…
  crossref P.S. Maclin, J. Dempsey 2002-12-30T22:49:31Z 置信度 0.70
• A Neural Network Based DTMF Decoder
  Communications systems frequently use a technique known as dual-tone multifrequency dialing (DTMF). Many possible solutions have been proposed for the design of DTMF decoders. Hardware-based solutions use filter banks to separate signals into low-band and high…
  crossref 2010-06-25T16:01:43Z 置信度 0.70
• Most Neural Networks Compute in Steps
  crossref Armand de Callataÿ 2013-12-09T03:06:39Z 置信度 0.70
• Forms of Neural Network Learning
  We will explain linear networks and discuss the limitations imposed by their simple structures. For our purposes, linear networks are easier to teach, they perform certain tasks very well, and their results are easy to analyze. Chapter 6 will cover the more co…
  crossref 2014-08-07T22:25:43Z 置信度 0.70
• Analogical reasoning by neural network
  Summary form only given, as follows. Analogical reasoning by neural network is discussed. The proposed method uses a template to create a network for analogical reasoning, and this can be done by an interactive activation and competition process. Computer simu…
  crossref M. Hagiwara, Y. Anzai 2002-12-09T18:24:26Z 置信度 0.70
• DEFUZZIFICATION OF ARTIFICIAL NEURAL NETWORK METHOD FOR LAND USE CLASSIFICATION
  crossref 2021-08-30T04:22:07Z 置信度 0.70
• Neural network based detection of EEG abnormalities.
  crossref Leon Lipoth 2018-10-04T20:10:16Z 置信度 0.70
• Figure 1: The schematic diagram of fuzzy neural network structure.
  crossref 2026-02-04T08:10:26Z 置信度 0.70
• Artificial neural network for studying human performance
  The vast majority of products and processes in industry and academia require human interaction. Thus, digital human models (DHMs) are becoming critical for improved designs, injury prevention, and a better understanding of human behavior. Although many capabil…
  crossref Mohammad Hindi Bataineh 2018-11-29T22:03:45Z 置信度 0.70
• Table 4: Configuration of neural network structure for E-MFNN.
  crossref 2024-04-19T03:43:31Z 置信度 0.70
• Finite-time stability for memristor based uncertain neural networks with time-varying delays- via average dwell time approach
  crossref M. Syed Ali, S. Saravanan 2017-08-24T09:21:39Z 置信度 0.70
• Recurrent Neural Network Based Predictions of Elephant Migration in a South African Game Reserve
  A large portion of South Africa's elephant population can be found on small wildlife reserves. When confined to enclosed reserves the elephant densities are much higher than observed in the wild. The large nutritional demands and destructive foraging behavior …
  crossref P. Palangpour, G.K. Venayagamoorthy, K. Duffy 2006-10-30T17:35:23Z 置信度 0.70
• A shape-recognition model using dynamical links
  A shape-recognition method is proposed, inspired from the dynamic-link theory of von der Malsburg (1981). The quality of a match between two images is assessed through an elastic cost functional; the minimal value reached by the cost over a suitably-defined sp…
  crossref Elie Bienenstock, René Doursat 2002-08-24T22:35:54Z 置信度 0.70
• Randomly connected sigma–pi neurons can form associator networks
  A set of sigma–pi units randomly connected to two input vectors forms a type of hetero-associator related to convolution- and matrix-based associative memories. Associations are represented as patterns of activity rather than connection strengths. Decoding the…
  crossref Tony Plate 2002-08-25T02:58:05Z 置信度 0.70
• Recurrent Neural Network Based Gating for Natural Gas Load Prediction System
  Prediction of natural gas consumption is an important element in gas load management aimed to better utilize the facilities of a gas distribution system. The major challenges faced by developers of prediction systems are the variety and volatility of consumer …
  crossref P. Musilek, E. Pelikan, T. Brabec, M. Simunek 2008-07-18T11:34:22Z 置信度 0.70
• Artificial Neural Network Training Algorithms in Modeling of Radial Overcut in EDM
  This chapter describes with the comparison of the most used back propagations training algorithms neural networks, mainly Levenberg-Marquardt, conjugate gradient and Resilient back propagation are discussed. In the present study, using radial overcut predictio…
  crossref Raja Das, Mohan Kumar Pradhan 2021-09-17T11:47:50Z 置信度 0.70
• Mono/multi-periodicity generated by impulses control in time-delayed memristor-based neural networks
  crossref Zuowei Cai, Lihong Huang, Zengyun Wang 2020-01-16T05:29:34Z 置信度 0.70
• Detecting dynamical changes within a simulated neural ensemble using a measure of representational quality
  Technological advances allowing simultaneous recording of neuronal ensembles have led to many developments in our understanding of how the brain performs neural computations. One key technique for extracting information from neural populations has been populat…
  crossref Jadin C Jackson, A David Redish 2015-08-18T20:04:06Z 置信度 0.70
• An external network model of the hippocampal formation
  crossref 2003-04-25T01:05:53Z 置信度 0.70
• Recent Advances in Neural Network Applications in Process Control
  crossref 2020-11-19T00:12:42Z 置信度 0.70
• 2005 International Neural Network Society Officers
  crossref 2011-06-07T18:33:07Z 置信度 0.70
• Useful Results
  crossref 2010-03-02T18:08:05Z 置信度 0.70
• Supplemental Information 1: ROC, BP neural network and SVM data
  crossref 2023-08-30T04:01:33Z 置信度 0.70
• Portfolio Selection with Convolutional Neural Network
  <p>In this work, we applied Convolutional Neural network (CNN) models to select the portfolio weights that lead to the highest realized return in one time-step ahead. In fact, given four possible portfolio optimization methods, the CNN is used to forecas…
  crossref Fahimeh Saei Manesh 2024-05-06T19:13:08Z 置信度 0.70
• ELECTRICITY PRICE FORECASTING USING A CONVOLUTIONAL NEURAL NETWORK
  Many methods have been used to forecast real-time electricity prices in various regions around the world. The problem is difficult because of market volatility affected by a wide range of exogenous variables from weather to natural gas prices, and accurate pri…
  crossref Elliott Winicki 2023-08-01T18:14:06Z 置信度 0.70
• On the dynamics of neural networks realizing associative memories of first and higher order
  This paper presents a new study on the dynamics of neural networks realizing associative memories of first and higher order. This is accomplished by focusing on the dynamics of a system of coupled differential equations that is shown to be equivalent to the ne…
  crossref Nicolaos B Karayiannis, Anastasios N Venetsanopoulos 2015-08-18T20:04:06Z 置信度 0.70
• Analysis of neural coding through quantization with an information-based distortion measure
  We discuss an analytical approach through which the neural symbols and corresponding stimulus space of a neuron or neural ensemble can be discovered simultaneously and quantitatively, making few assumptions about the nature of the code or relevant features. Th…
  crossref A.G. Dimitrov, J.P. Miller, T. Gedeon, Z. Aldworth 等 2003-01-22T23:14:48Z 置信度 0.70
• Front Matter
  crossref 2014-07-01T08:02:55Z 置信度 0.70
• Multilingual document embedding with sequential neural network models
  One of the current state-of-the-art multilingual document embedding model LASER is based on the bidirectional LSTM (BiLSTM) neural machine translation (NMT) model. This paper presents a Transformer-based Multilingual sentence/Document Embedding model, T-MDE, w…
  crossref Wei Li 2022-10-05T04:27:30Z 置信度 0.70
• Figure 7: Confusion matrix analysis of applied neural network approaches.
  crossref 2024-05-17T03:36:29Z 置信度 0.70
• Table 6: Performance metrics for neural network based summarization methods.
  crossref 2026-02-27T08:00:24Z 置信度 0.70
• Study of a learning algorithm for neural networks with discrete synaptic couplings
  The authors present a new learning algorithm for neural networks with discrete synaptic couplings. The main difference with respect to other previous algorithms is that it is defined in the continuous space. Its performance and features are analysed in detail.
  crossref C J Pérez Vicente, J Carrabina, E Valderrama 2015-08-18T16:04:12Z 置信度 0.70
• Multiplicative neural noise can favor an independent components representation of sensory input
  Arguments have been advanced to support the role of principal components (e.g., Karhunen-Loéve, eigenvector) and independent components transformations in early sensory processing, particularly for color and spatial vision. Although the concept of redundancy r…
  crossref Allan Gottschalk, Matthew G Sexton, Guilherme Roschke 2015-08-18T20:04:00Z 置信度 0.70
• Network Architecture
  crossref Dean A. Pomerleau 2011-06-15T05:55:34Z 置信度 0.70
• A Fully CMOS Low-Cost Chaotic Neural Network
  A chaotic IC is proposed and fabricated using a 0.35μm CMOS technology. The circuit iterates an N-shaped transfer function that can be modified using two external voltages, and is implemented using a three neurons network. The main advantages of the proposed c…
  crossref J.L. Rossello, S. Bota, V. Canals, I. de Paul 等 2008-07-18T11:27:21Z 置信度 0.70