b) a neural network that contains feedback
Explanation:
An auto-associative network is equivalent to a neural network that contains feedback. The number of feedback paths(loops) does not have to be one.
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
Which of the following is true? (i) On average, neural networks have higher computational rates than conventional computers. (ii) Neural networks learn by example. (iii) Neural networks mimic the way the human brain works. a) All of the mentioned are true b) (ii) and (iii) are true c) (i), (ii) and (iii) are true d) None of the mentioned
A perceptron is a) a single layer feed-forward neural network with pre-processing b) an auto-associative neural network c) a double layer auto-associative neural network d) a neural network that contains feedback
Having 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
A 3-input neuron is trained to output a zero when the input is 110 and a one when the input is 111. After generalization, the output will be zero when and only when the input is a) 000 or 110 or 011 or 101 b) 010 or 100 or 110 or 101 c) 000 or 010 or 110 or 100 d) 100 or 111 or 101 or 001
The name for the function in question 16 is a) Step function b) Heaviside function c) Logistic function d) Perceptron function
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
Neuro software is a) A software used to analyze neurons b) It is powerful and easy neural network c) Designed to aid experts in real world d) It is software used by Neuro surgeon
Which of the following is true? Single layer associative neural networks do not have the ability to (i) perform pattern recognition (ii) find the parity of a picture (iii)determine whether two or more shapes in a picture are connected or not a) (ii) and (iii) are true b) (ii) is true c) All of the mentioned d) None of the mentioned
Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions
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