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  2. Perceptron - Wikipedia

    en.wikipedia.org/wiki/Perceptron

    The perceptron algorithm is also termed the single-layer perceptron, to distinguish it from a multilayer perceptron, which is a misnomer for a more complicated neural network. As a linear classifier, the single-layer perceptron is the simplest feedforward neural network .

  3. Mark I Perceptron - Wikipedia

    en.wikipedia.org/wiki/Mark_I_Perceptron

    The Mark I Perceptron was organized into three layers: [2] A set of sensory units which receive optical input; A set of association units, each of which fire based on input from multiple sensory units; A set of response units, which fire based on input from multiple association units; The connection between sensory units and association units ...

  4. 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.

  5. Feedforward neural network - Wikipedia

    en.wikipedia.org/wiki/Feedforward_neural_network

    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 in at least three layers, notable for being able to distinguish data that is not ...

  6. ADALINE - Wikipedia

    en.wikipedia.org/wiki/ADALINE

    Learning inside a single-layer ADALINE Photo of an ADALINE machine, with hand-adjustable weights implemented by rheostats Schematic of a single ADALINE unit [1]. ADALINE (Adaptive Linear Neuron or later Adaptive Linear Element) is an early single-layer artificial neural network and the name of the physical device that implemented it.

  7. Spiking neural network - Wikipedia

    en.wikipedia.org/wiki/Spiking_neural_network

    The idea is that neurons in the SNN do not transmit information at each propagation cycle (as it happens with typical multi-layer perceptron networks), but rather transmit information only when a membrane potential—an intrinsic quality of the neuron related to its membrane electrical charge—reaches a specific value, called the threshold ...

  8. Delta rule - Wikipedia

    en.wikipedia.org/wiki/Delta_rule

    Download as PDF; Printable version; In other projects ... This article has multiple issues. ... It can be derived as the backpropagation algorithm for a single-layer ...

  9. File:Perceptron example.svg - Wikipedia

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

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