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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. 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.

  4. Neural network (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Neural_network_(machine...

    Neurons of one layer connect only to neurons of the immediately preceding and immediately following layers. The layer that receives external data is the input layer. The layer that produces the ultimate result is the output layer. In between them are zero or more hidden layers. Single layer and unlayered networks are also used.

  5. Perceptrons (book) - Wikipedia

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

    The perceptron convergence theorem was proved for single-layer neural nets. [12] During this period, neural net research was a major approach to the brain-machine issue that had been taken by a significant number of individuals. [12]

  6. Types of artificial neural networks - Wikipedia

    en.wikipedia.org/wiki/Types_of_artificial_neural...

    Each block consists of a simplified multi-layer perceptron (MLP) with a single hidden layer. The hidden layer h has logistic sigmoidal units, and the output layer has linear units. Connections between these layers are represented by weight matrix U; input-to-hidden-layer connections have weight matrix W.

  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. 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.

  9. 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 ...