Your English writing platform
Discover LudwigSuggestions(1)
Exact(6)
This layer is trained by presented extension of neural gas algorithm into complex numbers.
The Liquid State Machine is a recurrent neural network of spiking neurons where only the output layer is trained.
These networks can be briefly explained as a multi-layer neural network in which each layer is trained independently.
Besides the intermediate layers having a different number of outputs, in both MLPs the output layer is trained as a function of the 61 TIMIT original phones.
Each layer is trained until convergence criteria expressed as an error term in function of the actual output and a desired output (scheme of firing) is reached. .
Each layer is trained until convergence criteria expressed as an error term in function of the actual output and a desired output (scheme of firing) is reached.
Similar(54)
Several networks with a number of neurons in their hidden layer were trained with Levenberg-Marquardt (LM) algorithm.
An MLP network, with a single hidden layer, was trained for phone classification at a frame level.
In a subsequent supervised learning phase, the weights between the SOM hidden layer and the output layer are trained to recognize class labels.
This is done in a hierarchical way layer by layer, where first the forward connections from the lower to the higher layer are trained with the help of examples.
Two neural networks each of which having a single hidden layer was trained to relate the measured rotations and vertical displacements of the frame to the strain values measured at different locations of the frame.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com