Results 221 to 230 of about 21,160 (284)

Predicting the interfacial tension of CO₂ and NaCl aqueous solution with machine learning. [PDF]

Sci Rep
Liaqat K, Preston DJ, Schaefer L.
europepmc   +1 more source

Research on Acoustic Scene Classification Based on Time-Frequency-Wavelet Fusion Network. [PDF]

Sensors (Basel)
Bi F, Yang L.
europepmc   +1 more source

Reply to Eltawil et al. Comment on "Iacobescu et al. Evaluating Binary Classifiers for Cardiovascular Disease Prediction: Enhancing Early Diagnostic Capabilities. J. Cardiovasc. Dev. Dis. 2024, 11, 396". [PDF]

J Cardiovasc Dev Dis
Iacobescu P, Marina V, Anghel C, Anghele AD.   +3 more
europepmc   +1 more source

Heavy-tailed update distributions arise from information-driven self-organization in nonequilibrium learning. [PDF]

Proc Natl Acad Sci U S A
Zhang XY, Tang C.
europepmc   +1 more source

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Evolving Multilayer Perceptrons

Neural Processing Letters, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Pedro Ángel Castillo Valdivieso, J. Carpio, Juan Julián Merelo Guervós, Alberto Prieto, Víctor Manuel Rivas Santos, Gustavo Romero   +5 more
openaire   +2 more sources

A hyperbolic multilayer perceptron

Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium, 2000
We present a novel MLP-type neural network based on hyperbolic numbers $the hyperbolic multilayer perceptron (HMLP). The neurons of the HMLP compute 2D-hyperbolic orthogonal transformations as weight propagation functions. The HMLP can therefore be seen as the hyperbolic counterpart of the known complex MLP.
Sven Buchholz 0001, Gerald Sommer
openaire   +1 more source

Adaptive multilayer perceptrons

IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339), 2003
Multilayer perceptrons (MLP) with long- and short-term memories (LASTM) are proposed for adaptive processing. The activation functions of the output neurons of such a network are linear and thus the weights in the last layer affect the outputs of the network linearly and are called linear weights.
James T. Lo, Devasis Bassu
openaire   +1 more source

Multilayer perceptrons and fractals

Information Sciences, 1998
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
C. A. Murthy, Jennifer Pittman
openaire   +2 more sources