Question

Difference between autoassociative and heteroassociative net

Answer 1

*the inputs and output vectors s and t are the same.
*.The Hebb rule is used as a learning algorithm or calculate the weight matrix by summing the outer products of each input-output pair
*.The autoassociative application algorithmis used to test the algorithm

Hetero associative.
*The inputs and output vectors s and t are different.
*.The Hebb rule is used as a learning algorithm or calculate the weight matrix by summing the outer products of each input-output pair.
*.The heteroassociative application algorithm is used to test the algorithm.

Answer 2

The difference between autoassociative and heteroassociative networks is:

Autoassociative Networks:

• Autoassosiative networks are special kind of networks used to simulate associative processes.
• These are acheived through interaction of set of simple processing elements which are connected through weighted connections.
• They are capable to retrieve piece of data with the partial information and also capable for remembering from small portion of data.

Heteroassociative Networks:

• Heteroassociative networks stores input-output pattern pairs to recall stored output pattern by receiving noisy or incomplete version.
• In each of the pairs, an input pattern should differ from an output pattern.
• In this basic logical operations are used to determine associations among common and special features of reference patterns.