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Can anyone help me in understanding Hebb networking and how different function like AND, OR used to solve by this network.

I couldn’t understand properly through the google.

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  • $\begingroup$ Can you please tell us where you heard of the expression "Hebb network"? Aren't you actually interested in Hebbian learning, as opposed to a particular neural network that learns in an Hebbian fashion? $\endgroup$
    – nbro
    Commented Apr 26, 2019 at 0:54
  • $\begingroup$ @nbro I am confused on the same thing if Hebbian learning and Hebb Network are same thing. $\endgroup$
    – Lexi
    Commented Apr 26, 2019 at 2:53
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    $\begingroup$ There is no such thing as a Hebb Network. Perhaps you mean a Hopfield Network? Or its probabilistic version the Boltzmann Machine? There are the models which are trained by Hebbian Learning. $\endgroup$
    – samlaf
    Commented Apr 27, 2019 at 6:24

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In machine learning, the idea behind Hebbian learning is to strengthen (or weaken) the connection (the weight) between the neurons that have similar (or, respectively, dissimilar) outputs, where "similar" can be defined in different ways (e.g. it could be based on the sign of the output of the neurons).

Hebbian learning is a more biologically plausible way of learning than back-propagation, because it is a "local learning strategy" (you locally update the connections and not all the connections of the model at the same time), as opposed to back-propagation, which is a "global learning strategy" (where all connections are usually updated at once, given a "global error" of the network).

There are several neural networks (or models) that can learn in a Hebbian fashion: for example, the Hopfield network or Numenta's temporal memory.

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