enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Multilayer perceptron - Wikipedia

    en.wikipedia.org/wiki/Multilayer_perceptron

    If a multilayer perceptron has a linear activation function in all neurons, that is, a linear function that maps the weighted inputs to the output of each neuron, then linear algebra shows that any number of layers can be reduced to a two-layer input-output model.

  3. Mark I Perceptron - Wikipedia

    en.wikipedia.org/wiki/Mark_I_Perceptron

    The Mark I Perceptron achieved 99.8% accuracy on a test dataset with 500 neurons in a single layer. The size of the training dataset was 10,000 example images. It took 3 seconds for the training pipeline to go through a single image.

  4. File:MultiLayerPerceptron.svg - Wikipedia

    en.wikipedia.org/wiki/File:MultiLayerPerceptron.svg

    Main page; Contents; Current events; Random article; About Wikipedia; Contact us; Pages for logged out editors learn more

  5. File:Perceptron example.svg - Wikipedia

    en.wikipedia.org/wiki/File:Perceptron_example.svg

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses ...

  6. Feedforward neural network - Wikipedia

    en.wikipedia.org/wiki/Feedforward_neural_network

    The bottom layer of inputs is not always considered a real neural network layer. A multilayer perceptron (MLP) is a misnomer for a modern feedforward artificial neural network, consisting of fully connected neurons (hence the synonym sometimes used of fully connected network (FCN)), often with a nonlinear kind of activation function, organized ...

  7. Perceptrons (book) - Wikipedia

    en.wikipedia.org/wiki/Perceptrons_(book)

    The Gamba perceptron machine was similar to the perceptron machine of Rosenblatt. Its input were images. The image is passed through binary masks (randomly generated) in parallel. Behind each mask is a photoreceiver that fires if the input, after masking, is bright enough. The second layer is made of standard perceptron units.

  8. Sigmoid function - Wikipedia

    en.wikipedia.org/wiki/Sigmoid_function

    In particular see "Chapter 4: Artificial Neural Networks" (in particular pp. 96–97) where Mitchell uses the word "logistic function" and the "sigmoid function" synonymously – this function he also calls the "squashing function" – and the sigmoid (aka logistic) function is used to compress the outputs of the "neurons" in multi-layer neural ...

  9. Multi-layer perceptron - Wikipedia

    en.wikipedia.org/?title=Multi-layer_perceptron&...

    Pages for logged out editors learn more. Contributions; Talk; Multi-layer perceptron