Pages that link to "Item:Q1708845"

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

Displaying 50 items.

• Learning and Convergence of the Normalized Radial Basis Functions Networks (Q5881515) (← links)
• Stochastically weighted average conditional moment tests of functional form (Q5881678) (← links)
• On Approximation by Neural Networks with Optimized Activation Functions and Fixed Weights (Q5882452) (← links)
• Neural network approximation (Q5887830) (← links)
• A Proof that Artificial Neural Networks Overcome the Curse of Dimensionality in the Numerical Approximation of Black–Scholes Partial Differential Equations (Q5889064) (← links)
• Approximation by superpositions of a sigmoidal function (Q5917524) (← links)
• A simulation study of artificial neural networks for nonlinear time-series forecasting (Q5926605) (← links)
• Hyperplane arrangements separating arbitrary vertex classes in \(n\)-cubes (Q5927944) (← links)
• A combined PID/adaptive controller for a class of nonlinear systems (Q5932278) (← links)
• Approximate models for nonlinear dynamical systems and their generalization properties (Q5936775) (← links)
• A hybrid genetic fuzzy neural network algorithm designed for classification problems involving several groups (Q5938749) (← links)
• Neural network based modelling of environmental variables: A systematic approach (Q5939084) (← links)
• An application of artificial neural networks for rainfall forecasting (Q5939085) (← links)
• Predictive modelling of brewing fermentation: From knowledge-based to black-box models (Q5939988) (← links)
• Symbolic knowledge extraction from trained neural networks: A sound approach (Q5940782) (← links)
• Approximating and simulating the stochastic growth model: Parameterized expectations, neural networks, and the genetic algorithm (Q5941340) (← links)
• Special issue: Neural network feedback control (Q5943834) (← links)
• Adaptive output feedback control of nonlinear systems using neural networks (Q5943839) (← links)
• Using investment portfolio return to combine forecasts: A multiobjective approach (Q5945201) (← links)
• An investigation of neural networks for linear time-series forecasting (Q5945323) (← links)
• Control of chaotic dynamical systems using radial basis function network approximators (Q5946274) (← links)
• Comparative evaluation of genetic algorithm and backpropagation for training neural networks (Q5946280) (← links)
• On control of a base-excited inverted pendulum using neural networks (Q5950722) (← links)
• Extraction of nonlinear dynamics from short and noisy time series (Q5951010) (← links)
• An artificial neural network as a model for chaotic behavior of a three-phase fluidized bed. (Q5951020) (← links)
• An approximation result for nets in functional estimation (Q5951990) (← links)
• Neural-network-based realibility analysis: A comparative study (Q5955343) (← links)
• On the generalization problem (Q5956967) (← links)
• Neural networks in stochastic mechanics. (Q5957108) (← links)
• Programming backgammon using self-teaching neural nets (Q5958206) (← links)
• Error bounds for approximation with neural networks (Q5959036) (← links)
• Estimation of all-terminal network reliability using an artificial neural network (Q5959376) (← links)
• MAQA: a quantum framework for supervised learning (Q6043552) (← links)
• Koopman analysis of nonlinear systems with a neural network representation (Q6043737) (← links)
• Training Neural Networks as Learning Data-adaptive Kernels: Provable Representation and Approximation Benefits (Q6044638) (← links)
• Representations of hypergraph states with neural networks* (Q6046360) (← links)
• Solving second-order nonlinear evolution partial differential equations using deep learning (Q6048188) (← links)
• Electrical impedance tomography with deep Calderón method (Q6048408) (← links)
• Gauss-Newton method for solving linear inverse problems with neural network coders (Q6049832) (← links)
• Seq-SVF: an unsupervised data-driven method for automatically identifying hidden governing equations (Q6051370) (← links)
• Construction and approximation for a class of feedforward neural networks with sigmoidal function (Q6052306) (← links)
• An axiomatic approach to differentiation of polynomial circuits (Q6052943) (← links)
• Adaptive neural network control for nonholonomic systems with partial/full or without state constraints (Q6053928) (← links)
• Deep Neural Networks for Solving Large Linear Systems Arising from High-Dimensional Problems (Q6054285) (← links)
• A machine learning approach to portfolio pricing and risk management for high‐dimensional problems (Q6054432) (← links)
• A deep network construction that adapts to intrinsic dimensionality beyond the domain (Q6054952) (← links)
• On the approximation of functions by tanh neural networks (Q6055124) (← links)
• Reliable impulsive synchronization for fuzzy neural networks with mixed controllers (Q6055128) (← links)
• Approximation capabilities of neural networks on unbounded domains (Q6055159) (← links)
• Transformers for modeling physical systems (Q6055222) (← links)