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$\underline{\textbf{Answer:}\Rightarrow}$

$\underline{\textbf{Explanation:}\Rightarrow}$


Neural networks are defined at various levels of abstraction, and thus it models different aspects of neural networks.

$\therefore$ The network capacity is nothing but the levels of abstraction or the number of fundamental memories or the number of patterns that can be stored and recalled in a network.


https://en.wikipedia.org/wiki/Neural_network

https://scialert.net/fulltextmobile/?doi=itj.2008.684.688

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The number of patterns that can be stored and recalled in a network.

The capacity of a neural network refers to its ability to store and recall patterns. It is influenced by factors such as the architecture of the network, the weights associated with connections, and the activation functions used.

So, the correct option is:

The number of patterns that can be stored and recalled in a network.

Answer:

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