In this paper, we investigate the impact of chaos on the learning process of the XOR-boolean function by backpropagation neural networks.
Printed in the Netherlands. Chaos and Neural Network Learning. Some. Observations ... Key words: backpropagation algorithm, bifurcation, chaos, neural network ...
Apr 21, 2024 · Chaos is a real mathematical term with a very pedestrian definition, which is sensitive dependence on initial conditions.
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Jul 16, 2021 · So, Li and Ravela asked if and how a simple neural network could reproduce, extrapolate, and emulate the behaviors of well-known, chaotic ...
Nov 30, 2021 · There is a paper that proposes using chaotic systems as benchmark for evaluating deep learning models.
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In this paper, we introduce a novel scheme for the modeling task of multi-dimensional discrete-time chaotic maps rely- ing on the capabilities of perceptron ...
1998. In this paper, we investigate the impact of chaos on the learning process of the XOR-boolean function by backpropagation neural networks.
In this issue of Neuron, Sussillo and Abbott describe a new learning rule that helps harness the computational power of recurrent neural networks.
We show that neural networks can accurately learn the dynamical laws of chaotic time series from a limited number of iterates.
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May 12, 2022 · A general data driven numerical framework has been developed for learning and modeling of unknown dynamical systems using fully- or partially-observed data.