News

Scientific Research Publishing17d
Hornik, K., Stinchcombe, M. and White, H. (1989) Multilayer Feedforward Networks Are Universal Approximators. Neural Networks, 2, 359-366.
ABSTRACT: We explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...
Scientific Research Publishing17d
Leshno, M., Lin, V.Y., Pinkus, A. and Schocken, S. (1993) Multilayer Feedforward Networks with a Nonpolynomial Activation Function Can Approximate Any Function. Neural Networks ...
ABSTRACT: We explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...
IEEE16d
Fast learning process of multilayer neural networks using recursive least squares method
Abstract: A new approach for the learning process of multilayer perceptron neural networks using the recursive least squares (RLS) type algorithm is proposed. This method minimizes the global sum of ...
IEEE14d
Parameter Definition for Multilayer Perceptron Intended for Speaker Identification
the developed neural network model allows achieving identification accuracy of about 0.95, which is comparable with the most modern means of a similar purpose. The necessity of further research on ...
Deep Learning with Yacine on MSN13d
Create a Perceptron From Scratch in Python
Build your first neural network step by step! Learn how a perceptron works by coding it from the ground up—no libraries, just Python.
GitHub29d
Releases: SebSanchez97/Multilayer-Perceptron-Network
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