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

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

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Q. What are general limitations of back propagation rule?

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

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

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

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

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

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Q. Does linear autoassociative network have any practical use?

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

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Q. When are stable states reached in energy landscapes, that can be used to store input patterns?

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Q. The number of patterns that can be stored in a given network depends on?

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Q. What happens when number of available energy minima be less than number of patterns to be stored?

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Q. What happens when number of available energy minima be more than number of patterns to be stored?

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Q. How hard problem can be solved?

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Q. Why there is error in recall, when number of energy minima is more the required number of patterns to be stored?

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