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Which is true for neural networks?
a) It has set of nodes and connections
b) Each node computes it’s weighted input
c) Node could be in excited state or non-excited state
d) All of the mentioned
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The network that involves backward links from output to the input and hidden layers is called as ____. a) Self organizing maps b) Perceptrons c) Recurrent neural network d) Multi layered perceptron
What are the disadvantages of artificial neural networks?
Which of the following is true for neural networks? (i) The training time depends on the size of the network. (ii) Neural networks can be simulated on a conventional computer. (iii) Artificial neurons are identical in operation to biological ones. a) All of the mentioned b) (ii) is true c) (i) and (ii) are true d) None of the mentioned
Which of the following is an application of NN (Neural Network)? a) Sales forecasting b) Data validation c) Risk management d) All of the mentioned
A 4-input neuron has weights 1, 2, 3 and 4. The transfer function is linear with the constant of proportionality being equal to 2. The inputs are 4, 10, 5 and 20 respectively. The output will be: a) 238 b) 76 c) 119 d) 123
How many kinds of kohonen networks exist?
What is back propagation? a) It is another name given to the curvy function in the perceptron b) It is the transmission of error back through the network to adjust the inputs c) It is the transmission of error back through the network to allow weights to be adjusted so that the network can learn. d) None of the mentioned
How are nns related to statistical methods?
Describe the structure of artificial neural networks?
. Why are linearly separable problems of interest of neural network researchers? a) Because they are the only class of problem that network can solve successfully b) Because they are the only class of problem that Perceptron can solve successfully c) Because they are the only mathematical functions that are continue d) Because they are the only mathematical functions you can draw
Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions
What is backprop?
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