Research scientists all over the world are taking steps towards building computers with circuits patterned after the complex interconnections existing among the human brain’s nerve cells. What name is given to such type of computers? a) Intelligent computers b) Supercomputers c) Neural network computers d) Smart computers

Research scientists all over the world are taking steps towards building computers with circuits
patterned after the complex interconnections existing among the human brain’s nerve cells. What name
is given to such type of computers?
a) Intelligent computers
b) Supercomputers
c) Neural network computers
d) Smart computers
by

1 Answer

Answer :

c) Neural network computers
by

Related questions

Why is the XOR problem exceptionally interesting to neural network researchers? a) Because it can be expressed in a way that allows you to use a neural network b) Because it is complex binary operation that cannot be solved using neural networks c) Because it can be solved by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.

Description : Why is the XOR problem exceptionally interesting to neural network researchers? a) Because it can be expressed in a way that allows you to use a neural network b) Because it is complex ... solved by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.

Last Answer : d) Because it is the simplest linearly inseparable problem that exists.

This set of Artificial Intelligence MCQs focuses on “Neural Networks – 2”. 1. Why is the XOR problem exceptionally interesting to neural network researchers? a) Because it can be expressed in a way that allows you to use a neural network b) Because it is complex binary operation that cannot be solved using neural networks c) Because it can be solved by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.

Description : This set of Artificial Intelligence MCQs focuses on Neural Networks - 2 . 1. Why is the XOR problem exceptionally interesting to neural network researchers? a) Because it can be expressed in ... by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.

Last Answer : d) Because it is the simplest linearly inseparable problem that exists.

Claude Shannon described the operation of electronic switching circuits with a system of mathematical logic called _____________ a) LISP b) XLISP c) Neural networking d) Boolean algebra

Description : Claude Shannon described the operation of electronic switching circuits with a system of mathematical logic called _____________ a) LISP b) XLISP c) Neural networking d) Boolean algebra

Last Answer : c) Neural networking

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

Description : 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. ... ) are true c) (i), (ii) and (iii) are true d) None of the mentioned

Last Answer : a) All of the mentioned are true

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

Description : 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 ... ) are true c) (i), (ii) and (iii) are true d) None of the mentioned

Last Answer : a) All of the mentioned are true

What are the advantages of neural networks over conventional computers? (i) They have the ability to learn by example (ii) They are more fault tolerant (iii)They are more suited for real time operation due to their high ‘computational’ rates a) (i) and (ii) are true b) (i) and (iii) are true c) Only (i) d) All of the mentioned

Description : What are the advantages of neural networks over conventional computers? (i) They have the ability to learn by example (ii) They are more fault tolerant (iii)They are more suited for real time operation due to their high ... true b) (i) and (iii) are true c) Only (i) d) All of the mentioned

Last Answer : d) All of the mentioned

What are the advantages of neural networks over conventional computers? (i) They have the ability to learn by example (ii) They are more fault tolerant (iii)They are more suited for real time operation due to their high ‘computational’ rates a) (i) and (ii) are true b) (i) and (iii) are true c) Only (i) d) All of the mentioned

Description : What are the advantages of neural networks over conventional computers? (i) They have the ability to learn by example (ii) They are more fault tolerant (iii)They are more suited for real time operation due to their high ... true b) (i) and (iii) are true c) Only (i) d) All of the mentioned

Last Answer : d) All of the mentioned

Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

Description : Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

Last Answer : a) Linear Functions

Neural Networks are complex ______________with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

Description : Neural Networks are complex ______________with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

Last Answer : b) Nonlinear Functions

Neural Networks are complex ———————–with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions e) Power Functions

Description : Neural Networks are complex ———————–with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions e) Power Functions

Last Answer : b) Nonlinear Functions

Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

Description : Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

Last Answer : a) Linear Functions

What among the following is/are the example of the intelligent agent/agents? a) Human b) Robot c) Autonomous Spacecraft d) All of the mentioned

Description : What among the following is/are the example of the intelligent agent/agents? a) Human b) Robot c) Autonomous Spacecraft d) All of the mentioned

Last Answer : 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

Description : 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

Last Answer : b) It is powerful and easy neural network

Which coaxial connector is a more complex and expensive but do a better job in maintaining the electrical characteristics of the cable through the interconnections? A. N-type connector B. F-type connector C.BNC D. PL-259

Description : Which coaxial connector is a more complex and expensive but do a better job in maintaining the electrical characteristics of the cable through the interconnections? A. N-type connector B. F-type connector C.BNC D. PL-259

Last Answer : A. N-type connector

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

Description : 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

Last Answer : d) All of the mentioned

The network that involves backward links from output to the input and hidden layers is called _________ a) Self organizing maps b) Perceptrons c) Recurrent neural network d) Multi layered perceptron

Description : The network that involves backward links from output to the input and hidden layers is called _________ a) Self organizing maps b) Perceptrons c) Recurrent neural network d) Multi layered perceptron

Last Answer : c) Recurrent neural network

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

Description : 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

Last Answer : a) It can explain result

What is Neuro software? a) A software used to analyze neurons b) It is powerful and easy neural network

Description : What is Neuro software? a) A software used to analyze neurons b) It is powerful and easy neural network

Last Answer : b) It is powerful and easy neural network

What is an auto-associative network? a) a neural network that contains no loops b) a neural network that contains feedback c) a neural network that has only one loop d) a single layer feed-forward neural network with pre-processing

Description : What is an auto-associative network? a) a neural network that contains no loops b) a neural network that contains feedback c) a neural network that has only one loop d) a single layer feed-forward neural network with pre-processing

Last Answer : b) a neural network that contains feedback

What is perceptron? 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

Description : What is perceptron? 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

Last Answer : a) a single layer feed-forward neural network with pre-processing

A perceptron is a ______________ a) Feed-forward neural network b) Backpropagation algorithm c) Backtracking algorithm d) Feed Forward-backward algorithm

Description : A perceptron is a ______________ a) Feed-forward neural network b) Backpropagation algorithm c) Backtracking algorithm d) Feed Forward-backward algorithm

Last Answer : a) Feed-forward neural network

An Artificial Neural Network Is based on? a) Strong Artificial Intelligence approach b) Weak Artificial Intelligence approach c) Cognitive Artificial Intelligence approach d) Applied Artificial Intelligence approach

Description : An Artificial Neural Network Is based on? a) Strong Artificial Intelligence approach b) Weak Artificial Intelligence approach c) Cognitive Artificial Intelligence approach d) Applied Artificial Intelligence approach

Last Answer : c) Cognitive Artificial Intelligence approach

Three main basic features involved in characterizing membership function are A. Intution, Inference, Rank Ordering B. Fuzzy Algorithm, Neural network, Genetic Algorithm C. Core, Support , Boundary D. Weighted Average, center of Sums, Median

Description : Three main basic features involved in characterizing membership function are A. Intution, Inference, Rank Ordering B. Fuzzy Algorithm, Neural network, Genetic Algorithm C. Core, Support , Boundary D. Weighted Average, center of Sums, Median

Last Answer : C. Core, Support , Boundary

In artificial Neural Network interconnected processing elements are called A. nodes or neurons B. weights C. axons D. Soma

Description : In artificial Neural Network interconnected processing elements are called A. nodes or neurons B. weights C. axons D. Soma

Last Answer : A. nodes or neurons

Artificial neural network used for A. Pattern Recognition B. Classification C. Clustering D. All of these

Description : Artificial neural network used for A. Pattern Recognition B. Classification C. Clustering D. All of these

Last Answer : D. All of these

A Neural Network can answer A. For Loop questions B. what-if questions C. IF-The-Else Analysis Questions D.

Description : A Neural Network can answer A. For Loop questions B. what-if questions C. IF-The-Else Analysis Questions D.

Last Answer : B. what-if questions

A perceptron is a ——————————–. a) Feed-forward neural network b) Back-propagation algorithm c) Back-tracking algorithm d) Feed Forward-backward algorithm e) Optimal algorithm with Dynamic programming

Description : A perceptron is a ——————————–. a) Feed-forward neural network b) Back-propagation algorithm c) Back-tracking algorithm d) Feed Forward-backward algorithm e) Optimal algorithm with Dynamic programming

Last Answer : a) Feed-forward neural network

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

Description : 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

Last Answer : d) All of the mentioned

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

Description : 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

Last Answer : c) Recurrent neural network

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

Description : 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

Last Answer : a) It can explain result

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

Description : 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 ... mathematical functions that are continue d) Because they are the only mathematical functions you can draw

Last Answer : b) Because they are the only class of problem that Perceptron can solve successfully

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

Description : 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 ... b) (ii) is true c) (i) and (ii) are true d) None of the mentioned

Last Answer : c) (i) and (ii) are true

An auto-associative network is: a) a neural network that contains no loops b) a neural network that contains feedback c) a neural network that has only one loop d) a single layer feed-forward neural network with pre-processing

Description : An auto-associative network is: a) a neural network that contains no loops b) a neural network that contains feedback c) a neural network that has only one loop d) a single layer feed-forward neural network with pre-processing

Last Answer : b) a neural network that contains feedback

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

Description : 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

Last Answer : a) a single layer feed-forward neural network with pre-processing

What is single layer feed forward neural network?

Description : What is single layer feed forward neural network? 

Last Answer : A network with all the inputs connected directly to the outputs is called a single layer neural network or a perceptron networks.

What are the categories of neural network structures?

Description : What are the categories of neural network structures? 

Last Answer : i. Acyclic (or) Feed – forward networks  ii. Cyclic (or) Recurrent Networks

Which among the following includes the areas of Artificial Intelligence specialization:a) Games (Programming computers to play games against human opponents)b) Natural Languages (Programming computers to understand natural human languages)c) Neutral Networks (Systems that simulate intelligence by attempting to reproduce the types ofphysical connections that occur in animal brains)d) All of the Abovee) None of These

Description : Which among the following includes the areas of Artificial Intelligence specialization: a) Games (Programming computers to play games against human opponents) b) Natural Languages (Programming computers to understand natural ... that occur in animal brains) d) All of the Above e) None of These

Last Answer : d) All of the Above

______________is a branch of science that deals with programing the systems in such a way that they automatically learn and improve with experience A. Machine Learning B. Deep Learning C. Neural Networks D. None of these

Description : ______________is a branch of science that deals with programing the systems in such a way that they automatically learn and improve with experience A. Machine Learning B. Deep Learning C. Neural Networks D. None of these

Last Answer : A. Machine Learning 

Neural Computing A. mimics human brain B. information processing paradigm C. Both (a) and (b) D. None of the above

Description : Neural Computing A. mimics human brain B. information processing paradigm C. Both (a) and (b) D. None of the above

Last Answer : C. Both (a) and (b)

_____ model were developed and incorporated in machines which mimicked the functionalities of human origin. A. Functional model B. Neural model C. Computational model D. None of above

Description : _____ model were developed and incorporated in machines which mimicked the functionalities of human origin. A. Functional model B. Neural model C. Computational model D. None of above

Last Answer : C. Computational model 

Computer programs that mimic the way the human brain processes information is called as A. Machine Learning B. Deep Learning C. Neural Networks D. None of these

Description : Computer programs that mimic the way the human brain processes information is called as A. Machine Learning B. Deep Learning C. Neural Networks D. None of these

Last Answer : The correct answer is: C. Neural Networks Neural Networks are computer programs or models that are designed to mimic the way the human brain processes information. They are a subset of ... advanced form of neural networks that uses multiple layers of artificial neurons to perform complex tasks.

The tubular and dorsal nervous system of chordates is related to the cephalization in these animals and to bilateral symmetry. The presence of neural integrating centers with concentration of neurons in the brains and the spinal cord (central nervous system, CNS) allowed the increase of the interaction complexity between these animals and the environment. Receptor (afferent conduction) and efferent (motor, regulatory and behavioral reactions) functions come out more sophisticated in chordates due to the presence of more well-developed neural networks. These features have been preserved by evolution as they provide adaptive advantage to their owners.

Description : The tubular and dorsal nervous system of chordates is related to the cephalization in these animals and to bilateral symmetry. The presence of neural integrating centers with concentration of ... These features have been preserved by evolution as they provide adaptive advantage to their owners.

Last Answer : How can the tubular-dorsal nervous system in chordates be compared to the nervous pattern present in invertebrates?

What is the main difference between a mainframe and a super computer? A) Super computer is much larger than mainframe computers B) Super computers are much smaller than mainframe computers C) Supercomputers are focused to execute few programs as fast as possible while mainframe uses its power to execute as many programs concurrently D) Supercomputers are focused to execute as many programs as possible while mainframe uses its power to execute few programs as fast as possible.

Description : What is the main difference between a mainframe and a super computer? A) Super computer is much larger than mainframe computers B) Super computers are much smaller than mainframe computers C) ... programs as possible while mainframe uses its power to execute few programs as fast as possible.

Last Answer : Answer : C

The operating system called UNIX is typically used for - 1) Desktop computers 2) Laptop computers 3) Supercomputers 4) All of these

Description : The operating system called UNIX is typically used for - 1) Desktop computers 2) Laptop computers 3) Supercomputers 4) All of these

Last Answer : 4) All of these

Data centers and centralized computing covers many and a) Microcomputers b) Minicomputers c) Mainframe computers d) Supercomputers

Description : Data centers and centralized computing covers many and a) Microcomputers b) Minicomputers c) Mainframe computers d) Supercomputers

Last Answer : Supercomputers

The operating system called UNIX is typically used for - 1 Desktop computers 2 Laptop computers 3 Supercomputers 4 All of these

Description : The operating system called UNIX is typically used for - 1 Desktop computers 2 Laptop computers 3 Supercomputers 4 All of these

Last Answer : 4 All of these

Super Computers termed considered as: a) Dumb Terminal b) Intelligent Terminal c) Smart Terminal d) Super Terminal e) None of These

Description : Super Computers termed considered as: a) Dumb Terminal b) Intelligent Terminal c) Smart Terminal d) Super Terminal e) None of These

Last Answer : b) Intelligent Terminal

Subject orientation A . The science of collecting, organizing, and applying numerical facts B. Measure of the probability that a certain hypothesis is incorrect given certain observations. C. One of the defining aspects of a data warehouse, which is specially built around all the existing applications of the operational data D . None of these

Description : Subject orientation A . The science of collecting, organizing, and applying numerical facts B. Measure of the probability that a certain hypothesis is incorrect given certain observations. C. ... specially built around all the existing applications of the operational data D . None of these

Last Answer : C. One of the defining aspects of a data warehouse, which is specially built around all the existing applications of the operational data

A _________ is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. a) Decision tree b) Graphs c) Trees d) Neural Networks

Description : A _________ is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. a) Decision tree b) Graphs c) Trees d) Neural Networks

Last Answer : a) Decision tree

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

Description : 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

Last Answer : d) All of the mentioned