Results 91 to 100 of about 4,010,683 (211)
Neural DAEs: Constrained Neural Networks
SIAM Journal on Scientific ComputingThis article investigates the effect of explicitly adding auxiliary algebraic trajectory information to neural networks for dynamical systems. We draw inspiration from the field of differential-algebraic equations and differential equations on manifolds and implement related methods in residual neural networks, despite some fundamental scenario ...
Tue Boesen, Eldad Haber, Uri M. Ascher
openaire +5 more sources
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1990 Several means for improving the performance and training of neural networks for classification are proposed. Crossvalidation is used as a tool for optimizing network parameters and architecture. It is shown that the remaining residual generalization error can be reduced by invoking ensembles of similar networks. >
Lars Kai Hansen, Peter Salamon
openaire +3 more sources
Exploring Traffic Systems by Elasticity Analysis of Neural Networks
, 2019 This chapter shows how elasticity testing of neural networks can greatly aid our understanding of transport systems. It examines several different pieces of work which have the common theme of using neural networks, coupled with a technique of elasticity
Dougherty, Mark,, Mark Dougherty
core +1 more source
A Model for Programmability and Virtuality in Dynamical Neural Networks [PDF]
, 2009 In this dissertation a fixed-weight architecture for Continuous Time Recurrent Neural Networks (CTRNNs) is proposed in order to give an account for biological phenomena, controlled by neuronal activity, in which changes of behavior occur so fast that ...
Donnarumma, Francesco
core +1 more source
Detailed analysis of drift diffusion model parameters estimated for the ultimatum game
Neuroscience ResearchBargaining is fundamental in human social interactions and often studied using the ultimatum game, where a proposer offers a division of resources, and the responder decides whether to accept or reject it.
Shotaro Numano, Masahiko Haruno
doaj +1 more source
Neural Networks: Is it hermeneutic? [PDF]
This paper proposes a synoptic methodology to evaluate the determinants of audit fees by utilising Neural Networks. First, a brief discussion is presented to highlight the significant application of Neural Network in the areas of financial management ...
Rama Prasad Kanungo
core
Asymptotic stability for neural networks with mixed time-delays: The discrete-time case [PDF]
, 2009 This is the post print version of the article. The official published version can be obtained from the link - Copyright 2009 Elsevier LtdThis paper is concerned with the stability analysis problem for a new class of discrete-time recurrent neural ...
Liu, Y +8 more
core +1 more source
Neural Networks, 2019 It has been known for discrete-time recurrent neural networks (NNs) that binary-state models using the Heaviside activation function (with Boolean outputs 0 or 1) are equivalent to finite automata (level 3 in the Chomsky hierarchy), while analog-state NNs with rational weights, employing the saturated-linear function (with real-number outputs in the ...
openaire +3 more sources
Neuronal Substrates Underlying Performance Variability in Well-Trained Skillful Motor Task in Humans
Neural Plasticity, 2016 Motor performance fluctuates trial by trial even in a well-trained motor skill. Here we show neural substrates underlying such behavioral fluctuation in humans.
Nobuaki Mizuguchi +4 more
doaj +1 more source
ARTIFICIAL NEURAL NETWORKS AND THEIR APPLICATIONS IN BUSINESS [PDF]
In modern software implementations of artificial neural networks the approach inspired by biology has more or less been abandoned for a more practical approach based on statistics and signal processing. In some of these systems, neural networks, or parts
Iordache Ana Maria Mihaela
core