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Which of the following is not the promise of artificial neural network? a) It can explain result b) It can survive the failure of some nodes c) It has inherent parallelism d) It can handle noise
1 8486Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions
1 13411A perceptron adds up all the weighted inputs it receives, and if it exceeds a certain value, it outputs a 1, otherwise it just outputs a 0. a) True b) False c) Sometimes – it can also output intermediate values as well d) Can’t say
1 7349The name for the function in question 16 is a) Step function b) Heaviside function c) Logistic function d) Perceptron function
1 4959Having multiple perceptrons can actually solve the XOR problem satisfactorily: this is because each perceptron can partition off a linear part of the space itself, and they can then combine their results. a) True – this works always, and these multiple perceptrons learn to classify even complex problems. b) False – perceptrons are mathematically incapable of solving linearly inseparable functions, no matter what you do c) True – perceptrons can do this but are unable to learn to do it – they have to be explicitly hand-coded d) False – just having a single perceptron is enough
1 4738The 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
1 12721Which of the following is an application of NN (Neural Network)? a) Sales forecasting b) Data validation c) Risk management d) All of the mentioned
1 7941Post New AI Neural Networks Questions
How to avoid overflow in the logistic function?
Which is the similar operation performed by the drop-out in neural network?
Are neural networks helpful in medicine?
What are the applications of a Recurrent Neural Network (RNN)?
Describe the structure of artificial neural networks?
What are cases and variables?
How does an LSTM network work?
What is simple artificial neuron?
What are the population, sample, training set, design set, validation set, and test set?
What are the disadvantages of artificial neural networks?
What learning rate should be used for backprop?
Explain neural networks?
What is the difference between a Feedforward Neural Network and Recurrent Neural Network?
What are batch, incremental, on-line, off-line, deterministic, stochastic, adaptive, instantaneous, pattern, constructive, and sequential learning?
How are weights initialized in a network?
