Q. Generalization feature of a multilayer feedforward network depends on factors?

View solution

Q. What is accretive behaviour?

View solution

Q. What is Interpolative behaviour?

View solution

Q. Does pattern association involves non linear units in feedforward neural network?

View solution

Q. What is the feature that doesn’t belongs to pattern classification in feeddorward neural networks?

View solution

Q. What is the feature that doesn’t belongs to pattern mapping in feeddorward neural networks?

View solution

Q. In determination of weights by learning, for orthogonal input vectors what kind of learning should be employed?

View solution

Q. In determination of weights by learning, for linear input vectors what kind of learning should be employed?

View solution

Q. In determination of weights by learning, for noisy input vectors what kind of learning should be employed?

View solution

Q. What are the features that can be accomplished using affine transformations?

View solution

Q. What is the features that cannot be accomplished earlier without affine transformations?

View solution

Q. What are affine transformations?

View solution

Q. Can a artificial neural network capture association if input patterns is greater then dimensionality of input vectors?

View solution

Q. By using only linear processing units in output layer, can a artificial neural network capture association if input patterns is greater then dimensionality of input vectors?

View solution

Q. Number of output cases depends on what factor?

View solution

Q. For noisy input vectors, Hebb methodology of learning can be employed?

View solution

Q. What is the objective of perceptron learning?

View solution

Q. On what factor the number of outputs depends?

View solution

Q. In perceptron learning, what happens when input vector is correctly classified?

View solution

Q. When two classes can be separated by a separate line, they are known as?

View solution