Q. What can be done by using non – linear output function for each processing unit in a feedback network?

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Q. Does linear autoassociative network have any practical use?

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Q. In a linear autoassociative network, if input is noisy than output will be noisy?

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Q. Which is a simplest pattern recognition task in a feedback network?

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Q. How can learning process be stopped in backpropagation rule?

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Q. Does backpropagaion learning is based on gradient descent along error surface?

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Q. What are the general tasks that are performed with backpropagation algorithm?

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Q. What are general limitations of back propagation rule?

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Q. What is meant by generalized in statement “backpropagation is a generalized delta rule” ?

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Q. There is feedback in final stage of backpropagation algorithm?

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Q. What is true regarding backpropagation rule?

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Q. The backpropagation law is also known as generalized delta rule, is it true?

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Q. What is the objective of backpropagation algorithm?

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Q. Feedforward networks are also used for autoassociation and pattern storage?

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Q. Feedback networks are used for autoassociation and pattern storage?

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Q. What are 3 basic types of neural nets that form basic functional units?

i)feedforward
ii) loop
iii) recurrent
iv) feedback
v) combination of feed forward and back

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Q. Can system be both interpolative and accretive at same time?

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Q. If a(l) gives output b(l) and a’=a(l)+m,where m is small quantity and if a’ gives ouput b(l)+n then?

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Q. If a(l) gives output b(l) and a’=a(l)+m,where m is small quantity and if a’ gives ouput b(l) then?

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Q. The recalled output in pattern association problem depends on?

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