[amp_mcq option1=”a neural network that contains no loops” option2=”a neural network that contains feedback” option3=”a neural network that has only one loop” option4=”a single layer feed-forward neural network with pre-processing” correct=”option2″]
The correct answer is: B. a neural network that contains feedback.
An auto-associative network is a type of neural network that can learn to reconstruct its input. It does this by creating a set of weights that associate each input pattern with its corresponding output pattern. The network can then be used to reconstruct an input pattern even if it is incomplete or noisy.
Auto-associative networks are often used for tasks such as data compression, pattern recognition, and denoising. They can also be used to create artificial memories.
Option A is incorrect because an auto-associative network does contain loops. These loops allow the network to learn to associate each input pattern with its corresponding output pattern.
Option C is incorrect because an auto-associative network can have more than one loop. In fact, the number of loops in an auto-associative network is not fixed.
Option D is incorrect because an auto-associative network is not a single layer feed-forward neural network. It is a type of recurrent neural network.