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Recent questions tagged neural-network
2
votes
1
answer
1
UGC NET CSE | June 2019 | Part 2 | Question: 98
Which of the following is an example of unsupervised neural network? Back-propagation network Hebb network Associative memory network Self-organizing feature map
Which of the following is an example of unsupervised neural network?Back-propagation networkHebb networkAssociative memory networkSelf-organizing feature map
Arjun
3.2k
views
Arjun
asked
Jul 2, 2019
Artificial Intelligence
ugcnetcse-june2019-paper2
artificial-intelligence
neural-network
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–
3
votes
3
answers
2
ISRO2018-75
ln neural network, the network capacity is defined as: The traffic (tarry capacity of the network The total number of nodes in the network The number of patterns that can be stored and recalled in a network None of the above
ln neural network, the network capacity is defined as:The traffic (tarry capacity of the networkThe total number of nodes in the networkThe number of patterns that can be...
Arjun
2.7k
views
Arjun
asked
Apr 22, 2018
Artificial Intelligence
isro2018
non-gate
neural-network
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–
0
votes
1
answer
3
Uttrakhand Asst. Professor Exam-24
Which of the following can be an application of neural network ? Sales forecasting Data validation Risk management All of the above
Which of the following can be an application of neural network ?Sales forecastingData validationRisk managementAll of the above
gatecse
2.6k
views
gatecse
asked
Mar 2, 2018
Unknown Category
uttarakhand-asst-prof-2018
neural-network
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0
votes
0
answers
4
UGC NET CSE | December 2008 | Part 2 | Question: 49
An example of a data mining algorithm which uses squared error score function is : CART algorithm back propagation algorithm a priori algorithm vector space algorithm
An example of a data mining algorithm which uses squared error score function is :CART algorithm back propagation algorithm a priori algorithm ...
rishu_darkshadow
632
views
rishu_darkshadow
asked
Sep 26, 2017
Computer Networks
ugcnetcse-dec2008-paper2
neural-network
data-mining-algorithm
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1
votes
1
answer
5
UGC NET CSE | August 2016 | Part 3 | Question: 66
Let R and S be two fuzzy relations defined as and Then, the resulting relation, $T$, which relates elements of universe of $X$ to elements of universe of $Z$ using max-product composition is given by
Let R and S be two fuzzy relations defined asand Then, the resulting relation, $T$, which relates elements of universe of $X$ to elements of universe of $Z$ using max-pro...
makhdoom ghaya
1.7k
views
makhdoom ghaya
asked
Oct 4, 2016
Others
ugcnetcse-aug2016-paper3
neural-network
fuzzy-relations
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–
2
votes
1
answer
6
UGC NET CSE | August 2016 | Part 3 | Question: 64
What are the following sequence of steps taken in designing a fuzzy logic machine ? Fuzzification $\rightarrow$ Rule evaluation $\rightarrow$ Defuzzification Fuzzification $\rightarrow$ Defuzzification $\rightarrow$ ... $\rightarrow$ Fuzzification $\rightarrow$ Defuzzification Rule evaluation $\rightarrow$ Defuzzification $\rightarrow$ Fuzzification
What are the following sequence of steps taken in designing a fuzzy logic machine ?Fuzzification $\rightarrow$ Rule evaluation $\rightarrow$ DefuzzificationFuzzification ...
makhdoom ghaya
2.9k
views
makhdoom ghaya
asked
Oct 4, 2016
Others
ugcnetcse-aug2016-paper3
neural-network
fuzzy-logic
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–
3
votes
1
answer
7
UGC NET CSE | December 2014 | Part 3 | Question: 70
Consider the following statements about a perception : $I$. Feature detector can be any function of the input parameters. $II$. Learning procedure only adjusts the connection weights to the output layer. Identify the correct statement out of the following : $I$ is ... $II$ is false. $ I$ is false and $II$ is true. $I$ is true and $II$ is true.
Consider the following statements about a perception :$I$. Feature detector can be any function of the input parameters.$II$. Learning procedure only adjusts the connecti...
makhdoom ghaya
3.5k
views
makhdoom ghaya
asked
Aug 2, 2016
Data Mining and Warehousing
ugcnetcse-dec2014-paper3
neural-network
perceptron
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–
4
votes
3
answers
8
UGC NET CSE | Junet 2015 | Part 3 | Question: 72
Suppose the function y and a fuzzy integer number around - 4 for x are given as $y=(x-3)^2 + 2$. Around - 4 ={(2, 0.3), (3, 0.6), (4, 1), (5, 0.6), (6, 0.3)} respectively. Then f(Around-4) is given by {(2, 0.6), (3, 0.3), (6, 1), (11, 0.3)} {(2, 0.6), (3, ... (11, 0.3)} {(2, 0.6), (3, 1), (6, 0.6), (11, 0.3)} {(2, 0.6), (3, 0.3), (6, 0.6), (11, 0.3)}
Suppose the function y and a fuzzy integer number around - 4 for x are given as $y=(x-3)^2 + 2$. Around - 4 ={(2, 0.3), (3, 0.6), (4, 1), (5, 0.6), (6, 0.3)} respectively...
go_editor
7.1k
views
go_editor
asked
Aug 2, 2016
Others
ugcnetcse-june2015-paper3
fuzzy-set
neural-network
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–
4
votes
1
answer
9
UGC NET CSE | Junet 2015 | Part 3 | Question: 71
Let A and B be two fuzzy integers defined as: A={(1.0.3), (2, 0.6), (3, 1), (4, 0.7), (5, 0.2)} B={(10, 0.5), (11, 1), (12, 0.5)} Using fuzzy arithmetic operation given by $\mu_{A+B^{(Z)}} = \underset{x+y=z}{\oplus} (\mu_A (x) \otimes \mu_B(y))$ ... , 0.5), (17, 0.2)} {(11, 0.3), (12, 0.5), (13, 0.6), (14, 1), (15, 0.7), (16, 0.5), (17, 0.2)}
Let A and B be two fuzzy integers defined as:A={(1.0.3), (2, 0.6), (3, 1), (4, 0.7), (5, 0.2)}B={(10, 0.5), (11, 1), (12, 0.5)}Using fuzzy arithmetic operation given by$\...
go_editor
5.6k
views
go_editor
asked
Aug 2, 2016
Others
ugcnetcse-june2015-paper3
fuzzy-set
neural-network
+
–
3
votes
2
answers
10
UGC NET CSE | Junet 2015 | Part 3 | Question: 70
Consider the two class classification task that consists of the following points: Class $C_1$ : [1 1.5] [1 -1.5] Class $C_2$ : [-2 2.5] [-2 -2.5] The decision boundary between the two classes using single perceptron is given by: $x_1+x_2+1.5=0$ $x_1+x_2-1.5=0$ $x_1+1.5=0$ $x_1-1.5=0$
Consider the two class classification task that consists of the following points:Class $C_1$: [1 1.5][1 -1.5]Class $C_2$: [-2 2.5][-2 -2.5]The decision boundary b...
go_editor
4.1k
views
go_editor
asked
Aug 2, 2016
Others
ugcnetcse-june2015-paper3
fuzzy-set
neural-network
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0
votes
1
answer
11
UGC NET CSE | September 2013 | Part 3 | Question: 28
In a single perceptron, the updation rule of weight vector is given by $w(n+1) = w(n) + \eta [d(n)-y(n)]$ $w(n+1) = w(n) - \eta [d(n)-y(n)]$ $w(n+1) = w(n) + \eta [d(n)-y(n)]*x(n)$ $w(n+1) = w(n) - \eta [d(n)-y(n)]*x(n)$
In a single perceptron, the updation rule of weight vector is given by$w(n+1) = w(n) + \eta [d(n)-y(n)]$$w(n+1) = w(n) - \eta [d(n)-y(n)]$$w(n+1) = w(n) + \eta [d(n)-y(n)...
go_editor
3.2k
views
go_editor
asked
Jul 24, 2016
Artificial Intelligence
ugcnetcse-sep2013-paper3
neural-network
machine-learning
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–
1
votes
1
answer
12
UGC NET CSE | September 2013 | Part 3 | Question: 27
Support of a fuzzy set $A= \big\{ \frac{x_1}{0.2}, \frac{x_2}{0.15}, \frac{x_3}{0.9}, \frac{x_4}{0.95}, \frac{x_5}{0.15} \big \}$ ... $\{x_3, x_4 \}$ $\{x_1, x_2, x_3, x_4, x_5\}$
Support of a fuzzy set $A= \big\{ \frac{x_1}{0.2}, \frac{x_2}{0.15}, \frac{x_3}{0.9}, \frac{x_4}{0.95}, \frac{x_5}{0.15} \big \}$ within a universal set X is given as$\bi...
go_editor
3.6k
views
go_editor
asked
Jul 24, 2016
Others
ugcnetcse-sep2013-paper3
neural-network
fuzzy-set
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–
0
votes
1
answer
13
UGC NET CSE | September 2013 | Part 3 | Question: 26
Let A be a set of comfortable houses given as $A = \big\{ \frac{x_1}{0.8}, \frac{x_2}{0.9}, \frac{x_3}{0.1}, \frac{x_4}{0.7} \big \}$ ... $\big\{ \frac{x_1}{0.7}, \frac{x_2}{0.7}, \frac{x_3}{0.7}, \frac{x_4}{0.9} \big \}$
Let A be a set of comfortable houses given as $A = \big\{ \frac{x_1}{0.8}, \frac{x_2}{0.9}, \frac{x_3}{0.1}, \frac{x_4}{0.7} \big \}$ and be the set of affordable houses ...
go_editor
3.5k
views
go_editor
asked
Jul 24, 2016
Others
ugcnetcse-sep2013-paper3
neural-network
fuzzy-logic
+
–
1
votes
1
answer
14
UGC NET CSE | June 2013 | Part 3 | Question: 75
Consider a single perception with weights as given in the following figure: and $f(t)$ is defined as $f(t) \bigg\{ 1, t>0 \: 0, t \leq 0$ The above perception can solve OR problem AND problem XOR problem All of the above
Consider a single perception with weights as given in the following figure:and $f(t)$ is defined as$f(t) \bigg\{ 1, t>0 \: 0, t \leq 0$The above perception can solveOR p...
go_editor
3.4k
views
go_editor
asked
Jul 19, 2016
Others
ugcnetcse-june2013-paper3
neural-network
single-layer-perceptron
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–
1
votes
1
answer
15
UGC NET CSE | June 2013 | Part 3 | Question: 74
If A and B are two fuzzy sets with membership functions $\mu _A (x)=\{0.6,0.5,0.1,0.7,0.8\}$ $\mu_B(x)=\{0.9, 0.2, 0.6, 0.8, 0.5\}$ Then the value of $\mu_{\overline{A \cup B} }(x)$ will be $\{0.9, 0.5, 0.6, 0.8, 0.8\}$ $\{0.6, 0.2, 0.1, 0.7, 0.5 \}$ $\{0.1, 0.5, 0.4, 0.2, 0.2\}$ $\{0.1, 0.5, 0.4, 0.2, 0.3 \}$
If A and B are two fuzzy sets with membership functions$\mu _A (x)=\{0.6,0.5,0.1,0.7,0.8\}$$\mu_B(x)=\{0.9, 0.2, 0.6, 0.8, 0.5\}$Then the value of $\mu_{\overline{A \cup ...
go_editor
11.3k
views
go_editor
asked
Jul 19, 2016
Others
ugcnetcse-june2013-paper3
neural-network
fuzzy-set
+
–
2
votes
1
answer
16
UGC NET CSE | June 2013 | Part 3 | Question: 73
A fuzzy set A on R is ______ iff $A(\lambda x_1 + (1- \lambda)x_2) \geq min [A(x_1), A(x_2)]$ for all $x_1, x_2 \in R$ and all $\lambda \in [0,1]$ where minimum denotes the minimum operator. Support $\alpha$ - cut Convex Concave
A fuzzy set A on R is ______ iff $A(\lambda x_1 + (1- \lambda)x_2) \geq min [A(x_1), A(x_2)]$ for all $x_1, x_2 \in R$ and all $\lambda \in [0,1]$ where minimum denotes t...
go_editor
2.7k
views
go_editor
asked
Jul 19, 2016
Others
ugcnetcse-june2013-paper3
neural-network
fuzzy-set
+
–
1
votes
1
answer
17
UGC NET CSE | December 2012 | Part 3 | Question: 9
You are given an OR problem and XOR problem to solve. Then, which one of the following statements is true? Both OR and XOR problems can be solved using single layer perception OR can be solved using single layer ... single layer perception OR can be solved using single layer perception and XOR problem can be solved using radial basis function
You are given an OR problem and XOR problem to solve. Then, which one of the following statements is true?Both OR and XOR problems can be solved using single layer perce...
go_editor
2.6k
views
go_editor
asked
Jul 12, 2016
Artificial Intelligence
ugcnetcse-dec2012-paper3
artificial-intelligence
neural-network
+
–
3
votes
3
answers
18
ISRO2011-2
Which of the following is an unsupervised neural network? RBS Hopfield Back propagation Kohonen
Which of the following is an unsupervised neural network?RBSHopfieldBack propagationKohonen
Anuanu
4.4k
views
Anuanu
asked
Jun 15, 2016
Artificial Intelligence
isro2011
neural-network
non-gate
+
–
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