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Welcome to the Basics of Artificial Neural Networks MCQs Page

Dive deep into the fascinating world of Basics of Artificial Neural Networks with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Basics of Artificial Neural Networks, a crucial aspect of neural networks. In this section, you will encounter a diverse range of MCQs that cover various aspects of Basics of Artificial Neural Networks, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within neural networks.

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Check out the MCQs below to embark on an enriching journey through Basics of Artificial Neural Networks. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of neural networks.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Basics of Artificial Neural Networks. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Basics of Artificial Neural Networks MCQs | Page 6 of 7

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Q51.
Who proposed the first perceptron model in 1958?
Discuss
Answer: (d).Rosenblatt
Q52.
John hopfield was credited for what important aspec of neuron?
Discuss
Answer: (c).energy analysis
Q53.
What is the contribution of Ackley, Hinton in neural?
Discuss
Answer: (b).boltzman machine
Discuss
Answer: (c).adaptive resonance theory
Discuss
Answer: (a).weighted sum of inputs
Discuss
Answer: (a).excitatory input
Discuss
Answer: (b).inhibitory input
Q58.
The amount of output of one unit received by another unit depends on what?
Discuss
Answer: (d).weight
Q59.
The process of adjusting the weight is known as?
Discuss
Answer: (c).learning
Q60.
The procedure to incrementally update each of weights in neural is referred to as?
Discuss
Answer: (d).both learning algorithm and law
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