On a more basic level, [Gigante] did just that, teaching a neural network to play a basic driving game with a genetic algorithm ... With enough training, the cars are able to complete the course ...

Abstract: Signal processing has made extensive use of neural networks. This study examines neural network training using the PSO and BP algorithms. To train the neural network, the PSO algorithm alone ...

The approaches are similar but can produce very different results. The general consensus among neural network researchers is that when using the back-propagation training algorithm, using the online ...

Abstract: This study compares training algorithms for artificial neural networks such as genetic, adaptive and hybrid. The “Fisher's Irises” were used as a data for the classification problem and ...

He built a program that will get Mario through an entire level of Super Mario World – Donut Plains 1 – using neural networks ... as the training data it is given. [SethBling]’s algorithm ...

However, training deep learning models ... In most discussions, deep learning means using deep neural networks. There are, however, a few algorithms that implement deep learning using other ...

Hardware neural network (HNN) based on analog synapse array excels in ... Meanwhile, SNN has suffered from poor learning performance due to the lack of adequate training algorithms. Many efforts have ...

The best way to understand neural networks is to build one for yourself ... If we add a bit of logging to the training algorithm, running it will give output similar to Listing 10.

"This neural network algorithm made it way easier and more reliable to detect ... a large dataset of aliased spectra to train the neural network. The extensive training improved the model's ability to ...