Pages that link to "Item:Q1708845"

The following pages link to Multilayer feedforward networks are universal approximators (Q1708845):

Displaying 50 items.

• Novel synchronization of discrete-time chaotic systems using neural network observer (Q5246296) (← links)
• Approximation by perturbed neural network operators (Q5253674) (← links)
• Possibility of Dynamical Process Linearization Using Piecewise-Linear Neural Network (Q5259777) (← links)
• Reinforcement learning for adaptive optimal control of unknown continuous-time nonlinear systems with input constraints (Q5265704) (← links)
• Approximations by multivariate perturbed neural network operators (Q5267949) (← links)
• An Evolutionary Programming Based Knowledge Ensemble Model for Business Risk Identification (Q5302335) (← links)
• An EMD-Based Neural Network Ensemble Learning Model for World Crude Oil Spot Price Forecasting (Q5302347) (← links)
• Two Frameworks for Improving Gradient-Based Learning Algorithms (Q5302484) (← links)
• A Family of Model Predictive Control Algorithms With Artificial Neural Networks (Q5308323) (← links)
• Direct neural network-based self-tuning control for a class of nonlinear systems (Q5309016) (← links)
• Neural net control of nonlinear plants through state feedback (Q5317781) (← links)
• Consistency of Ridge Function Fields for Varying Nonparametric Regression (Q5321904) (← links)
• Multilayer Perceptron Classification of Unknown Volatile Chemicals from the Firing Rates of Insect Olfactory Sensory Neurons and Its Application to Biosensor Design (Q5327170) (← links)
• Toward Nonlinear Local Reinforcement Learning Rules Through Neuroevolution (Q5378282) (← links)
• Sub-grid scale model classification and blending through deep learning (Q5379089) (← links)
• A Single Hidden Layer Feedforward Network with Only One Neuron in the Hidden Layer Can Approximate Any Univariate Function (Q5380543) (← links)
• (Q5381112) (← links)
• Universal Approximation Depth and Errors of Narrow Belief Networks with Discrete Units (Q5383782) (← links)
• Hybrid learning-based neuro-fuzzy inference system: a new approach for system modeling (Q5402746) (← links)
• Intelligent financial time series forecasting: A complex neuro-fuzzy approach with multi-swarm intelligence (Q5403384) (← links)
• Computational Properties of Networks of Synchronous Groups of Spiking Neurons (Q5440976) (← links)
• NEURAL NETWORK-BASED DIGITAL REDESIGN APPROACH FOR CONTROL OF UNKNOWN CONTINUOUS-TIME CHAOTIC SYSTEMS (Q5474302) (← links)
• Enhancements to non-linear multiple model adaptive control schemes (Q5485923) (← links)
• Applying Machine Learning to the Problem of Choosing a Heuristic to Select the Variable Ordering for Cylindrical Algebraic Decomposition (Q5495916) (← links)
• Sliding-mode and proportional-derivative-type motion control with radial basis function neural network based estimators for wheeled vehicles (Q5499856) (← links)
• Extended Gaussianization Method for Blind Separation of Post-Nonlinear Mixtures (Q5696496) (← links)
• COARSE-GRAINED PARALLELIZATION OF THE ADVANCED NEUROSIMULATOR FAUN 1.0 WITH PVM AND THE ENHANCED CORNERED RAT GAME REVISITED (Q5711108) (← links)
• Neuro-adaptive cooperative tracking control with prescribed performance of unknown higher-order nonlinear multi-agent systems (Q5742527) (← links)
• Sigmoidal FFANN’s and the best approximation property (Q5756383) (← links)
• BOUNDS ON MULTI-ASSET DERIVATIVES VIA NEURAL NETWORKS (Q5854317) (← links)
• Development of Artificial Neural Networks Trained by Heuristic Algorithms for Prediction of Exhaust Emissions and Performance of a Diesel Engine Fuelled with Biodiesel Blends (Q5855621) (← links)
• Wide neural networks of any depth evolve as linear models under gradient descent ^* (Q5857449) (← links)
• Emergence of a finite-size-scaling function in the supervised learning of the Ising phase transition (Q5857509) (← links)
• Expressing harmonic sums as fractions (Q5860075) (← links)
• Strong Solutions for PDE-Based Tomography by Unsupervised Learning (Q5860278) (← links)
• Learning Maximally Monotone Operators for Image Recovery (Q5860360) (← links)
• Learnable Descent Algorithm for Nonsmooth Nonconvex Image Reconstruction (Q5860374) (← links)
• A (Semi)Parametric Functional Coefficient Logarithmic Autoregressive Conditional Duration Model (Q5863653) (← links)
• Deep Learning for Image/Video Restoration and Super-resolution (Q5863770) (← links)
• Forecasting Macroeconomic Variables Using Neural Network Models and Three Automated Model Selection Techniques (Q5864520) (← links)
• Nonlinear Level Set Learning for Function Approximation on Sparse Data with Applications to Parametric Differential Equations (Q5864754) (← links)
• A Local Deep Learning Method for Solving High Order Partial Differential Equations (Q5864768) (← links)
• IMPROVING AUTOMOBILE INSURANCE CLAIMS FREQUENCY PREDICTION WITH TELEMATICS CAR DRIVING DATA (Q5866172) (← links)
• Approximating functions with multi-features by deep convolutional neural networks (Q5873927) (← links)
• Spline representation and redundancies of one-dimensional ReLU neural network models (Q5873929) (← links)
• Expressivity of Deep Neural Networks (Q5879776) (← links)
• Deep advantage learning for optimal dynamic treatment regime (Q5879958) (← links)
• The balance property in neural network modelling (Q5880099) (← links)
• Numerical approximations of coupled forward–backward SPDEs (Q5880399) (← links)
• A Model-Constrained Tangent Slope Learning Approach for Dynamical Systems (Q5880418) (← links)