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IGNOU MMTE 7 SOLVED ASSIGNMENT HINDI

IGNOU MMTE 7 SOLVED ASSIGNMENT HINDI


IGNOU MMTE 7 Solved Assignment 2026
Rs. 200
Rs. 123

IGNOU MMTE 7 SOLVED ASSIGNMENT HINDI

Rs. 200
Rs. 123

Last Date of Submission of IGNOU MMTE-07 (MSCMACS) 2026 Assignment is for January 2026 Session: 30th September, 2026 (for December 2026 Term End Exam).
Semester Wise
January 2026 Session:
30th March, 2026 (for June 2026 Term End Exam).
July 2026 Session: 30th September, 2026 (for December 2026 Term End Exam).

Title NameIGNOU MMTE 7 SOLVED ASSIGNMENT HINDI
TypeSoft Copy (E-Assignment) .pdf
UniversityIGNOU
DegreeMASTER DEGREE PROGRAMMES
Course CodeMSCMACS
Course NameM.Sc. Mathematics with Applications in Computer Science
Subject CodeMMTE 7
Subject NameSoft Computing & Applications
Year2026
Session
LanguageEnglish Medium
Assignment CodeMMTE-07/Assignmentt-1//2026
Product DescriptionAssignment of MSCMACS (M.Sc. Mathematics with Applications in Computer Science) 2026. Latest MMTE 07 2026 Solved Assignment Solutions
Last Date of IGNOU Assignment Submission
Last Date of Submission of IGNOU MMTE-07 (MSCMACS) 2026 Assignment is for January 2026 Session: 30th September, 2026 (for December 2026 Term End Exam).
Semester Wise
January 2026 Session:
30th March, 2026 (for June 2026 Term End Exam).
July 2026 Session: 30th September, 2026 (for December 2026 Term End Exam).

Rs. 200
Rs. 123
Questions Included in this Help Book

Ques 1.

बताइए निम्नलिखित कथन सत्य हैं या असत्य। अपने उत्तरों के कारण बताइए।

 

(i) equation

 

(ii) तीन चरों वाला एक वास्तविक-मान फलन, जो सर्वत्र सतत है, अवकलनीय होता है।
(iii) equation से परिभाषित फलन equation किसी भी बिन्दु equation पर स्थानिकतः व्युत्क्रमणीय होता है।
(iv) 
से परिभाषित फलन equation समाकलनीय होता है।
(v) equation से परिभाषित फलन equation का (0, 0) पर एक चरम मान होता है।

Ques 2.

(क) निम्नलिखित सीमा ज्ञात कीजिए :
(i) equation
(ii) equation

 

(ख) बिन्दु (1,2) पर फलन equation का तृतीय टेलर बहुपद ज्ञात कीजिए।
(ग) केवल परिभाषाओं को लागू करके fxy(0,0) और fyx(0,0) ज्ञात कीजिए, जबकि फलन

 

 

के लिए इनका अस्तित्व होता हो।

Ques 3.

  (क) मान लीजिए

 

equation$
दिखाइए कि (0,0) पर सभी दिशाओं में f दिक् अवकलज होते हैं।

 

(ख) मान लीजिए equation और f, x और y का एक संततः अवकलनीय फलन है जिसके आंशिक अवकलज भी संततः अवकलनीय हैं। दिखाइए कि
equation$

 

(ग) मान लीजिए equation के तीन बिन्दु हैं।
|2b - a + 3c| ज्ञात कीजिए।

Ques 4.

(क) वक्रों equation और equation से परिबद्ध और equation के घनत्व वाले एक पतली शीट का गुरुत्व केन्द्र ज्ञात कीजिए।
(ख) equation और equation से परिबद्ध ठोस घनाकृति का द्रव्यमान ज्ञात कीजिए, जबकि घनत्व फलन, equation हो।

Ques 5.

 (क) ग्रीन प्रमेय का कथन दीजिए और इसकी सहायता से
equation का मान निकालिए,
जहाँ C, दीर्घवृत्त equation है।
(ख) पृष्ठ equation पर फलन equation के चरम मान ज्ञात कीजिए।

Ques 6.

 (क) equation के एक विवृत उपसमुच्चय D पर दो अवकलनीय फलनों f और g की फलनात्मक आश्रितता का आवश्यक प्रतिबंध बताने वाले प्रमेय का कथन दीजिए। निम्नलिखित फलनों f तथा g द्वारा परिभाषित इस प्रमेय को सत्यापित कीजिए।
equation equation$

(ख) अस्पष्ट फलन प्रमेय की सहायता से यह दिखाइए कि 1 के प्रतिवेश में एक ऐसा अवकलनीय फलन g होता है, जिससे कि (2,1) के प्रतिवेश में equation और equation जहाँ
equation से फलन F परिभाषित है। g'(y) भी ज्ञात कीजिए। 
(ग) equation द्वारा परिभाषित फलन f की (1, -1) पर स्थानीय व्युत्क्रमणीयता की जाँच कीजिए। फलन f के लिए एक प्रांत ज्ञात कीजिए जिसमें f व्युत्क्रमणीय है। 

Ques 7.

(क) (0,0) पर निम्नलिखित फलन f के सांतत्य और अवकलनीयता की जाँच कीजिए, जहाँ

 

(ख) फलन equation से परिभाषित फलन f का प्रांत और परिसर ज्ञात कीजिए। इस फलन के दो स्तर वक्र भी ज्ञात कीजिए। 

Ques 8.

(क) equation के मान निकालिए, जहाँ C equation से प्राप्त वक्र है। 
(ख) द्विश: समाकलन का प्रयोग करके दीर्घवृत्तज

 

Ques 9.

क) यदि equation तो a और b के मान ज्ञात कीजिए। 
(ख) मान लीजिए कि S और C equation के उपसमुच्चय हैं। S मूल-बिन्दु पर केन्द्र वाला एकक विवृत गोलक है तथा C विवृत घन equation। 
निम्नलिखित में से कौनसा कथन सत्य है? अपने उत्तर की पुष्टि कीजिए।
(i) equation
(ii) equation

(ग) निम्नलिखित फलनों के स्तर वक्र ज्ञात कीजिए :
(i) equation
(ii) equation
(iii) x-y
(iv) y / x

Ques 10.

 

 (क) क्या निम्नलिखित फलन equation श्वार्ज़-प्रमेय की आवश्यकताओं को (1,1) पर संतुष्ट करता है? अपने उत्तर की पुष्टि कीजिए। (4)
(ख) निम्नलिखित के स्तब्ध बिन्दु निर्धारित करके उनका वर्गीकरण कीजिए : (6)
(i) equation
(ii) equation

Ques 11.

State whether the following statements are True or False. Give short proof or a counter example in support of your answer.
a) In the Hopfield network, the neurons belonging to the same layer receive input from the neurons of the previous layer and send their value only to the neurons of the next layer.
b) The length of chromosomes to determine the maximum value of the set:


equation is 12.
c) The fuzzy relation (R) given below, is an equivalence relation.



equation
d) The Self Organizing Map (SOM) is a supervised learning technique.
e) In a single layer neural network, if equation, then the output is -1.

Ques 12.

 Determine the fuzzy relation T as a composition between the fuzzy relations R and S given below by using max-min and max-product:
equation
equation

Ques 13.

 State whether the following statements are True or False. Give short proof or a counter example in support of your answer.
a) In the Hopfield network, the neurons belonging to the same layer receive input from the neurons of the previous layer and send their value only to the neurons of the next layer.
b) The length of chromosomes to determine the maximum value of the set:

 



equation is 12.
c) The fuzzy relation (R) given below, is an equivalence relation.

 



equation
d) The Self Organizing Map (SOM) is a supervised learning technique.
e) In a single layer neural network, if equation, then the output is -1.

Ques 14.

 Determine the fuzzy relation T as a composition between the fuzzy relations R and S given below by using max-min and max-product:
equation
equation

Ques 15.

 

Solve the network to approximate the function:
equation
for equation, choosing the initial weights and bias as the random numbers.

Ques 16.

Verify whether the Genetic Algorithm (GA) improves the solution from one generation to the next generation, for the function given below:
Maximize:


equation
Subject to:


equation
Assume that chromosomes of length 6 are created at random and modified by Roulette-Wheel selection.

Ques 17.

 

 A single layer neural network is to have six inputs and three outputs. The outputs are continuous over the range 0 to 1. Now answer the following:
i) How many neurons are required?
ii) What are the dimensions of the weight matrix?
iii) What kind of transfer function could be used?
iv) Is a bias required? Give reasons.

Ques 18.

 Consider the single layer perception given below:

 

 

The activation function is:


equation
Obtain the output for each of the following input pattern:

Patterns  


p1
 

 


p2
 

 


p3
 

 


p4
 

 


x1
 

1 0 1 1
 


x2
 

0 1 0 1
 


x3
 

0 1 1 1

Ques 19.

 

 Consider the ADALINE filter with three neurons in the input layer having weights 3,1 and − 2and the input sequence ......., ,0,0,0 − 0,0,0,5,4 ,.....}. Find the filter output.

Ques 20.

Find the length and order of the following schema:

i) equation

ii) equation

iii) equation

iv) equation

Ques 21.

 Consider the fuzzy sets A and B defined on the interval [0, 5]. Their membership functions are:



equation$

 

and equation

Determine the membership function and graph them for each of the following:

i) AC, BC

ii) equation

iii) equation

iv) equation

v) equation

Ques 22.

 Let A and B be two Fuzzy sets as given below:
equation
equation
Determine the following:
i) Universe of discourse for Set A and Set B.
ii) Complements of Set A and Set B
iii) equation
iv) equation

Ques 23.

Implement AND function using McCulloch-Pitts neuron.

Ques 24.

 Out of three genetic operators viz. selection, cross-over and mutation, list and justify which operator or combination there of will be required for the following:

i) To fill the population with copies of the best individual from the population.
ii) For the convergence of an algorithm to good but sub-optimal solution.

Ques 25.

 

Approximate the function equation for equation, by solving 1-2-1 network, using Back propagation algorithm. The weighted structure and initial input are as follows:
Weighted structures are:
equation and bias equation
equation and bias equation
The initial input is 1.
Draw the architecture of the model. Perform one iteration.

Ques 26.

 Consider a dataset of five observations given in the following table, each of which has two features f1 and f2:

  x₁ x₂ x₃ x₄ x₅
f₁ 2 3 4 3 5
f₂ 6 7 5 4 6

Assume the number of cluster equation and the real number equation. Also, assume the initial cluster centers as equation and equation. Apply fuzzy c-mean algorithm to find the modified cluster center after one iteration.

Ques 27.

 Generate the population in the next iteration by using Roulette-Wheel criterion:

 


k
 

 


Fk
 

1 3.5
2 4.6
3 5
4 2.8
5 1.8

Ques 28.

Determine the equation-cut of the fuzzy set (A) are given below, at 0.7 and 0.2.
equation
Also, compare the equation-cut of the two outcomes, and give comments for status of equation-value variation.

Ques 29.

 Consider the following table for the connections between input neurons and the hidden layer neurons:

Input Neurons Hidden Layer Neurons Connection Weight
1 1 - 1
1 2 - 0.1
1 3 1
2 1 - 1
2 2 1
2 3 1
3 1 - 0.2
3 2 - 0.3
3 3 - 0.6

The connection weights from the hidden layer neurons to the output neurons are -0.6, -0.3 and -0.6, for the first, second and third neurons, respectively.

Corresponding threshold value for the output layer is 0.5 and for the hidden layer is 1.8, 0.005 and 0.2 for the first, second and third neurons, respectively.
i) Draw the diagram of the network.

 

ii) Write the output at each node.

Ques 30.

 

 Using diagram, show the difference between feed-forward neural network and recurrent neural network.

Ques 31.

 Computer the output for the neurons in the kohonen networks, the related data is given below:
i) Input to Kohnen neural network:
Input Neuron-1 equation
Input Neuron-2 equation
ii) Connected weights between the neurons are as given below:
equation
equation
equation
equation

Ques 32.

 Consider the two parents which are participating in partially mapped cross over as shown below:

Parent 1: C D | E A B |I H G F

Parent 2: A B | C D E |F G H I

Using partially mapped crossover assuming 2nd and 6th as the cross over sites, find the children solution.

 

Ques 33.

बताइए निम्नलिखित कथन सत्य हैं या असत्य। अपने उत्तरों के कारण बताइए।

 

(i) equation

 

(ii) तीन चरों वाला एक वास्तविक-मान फलन, जो सर्वत्र सतत है, अवकलनीय होता है।
(iii) equation से परिभाषित फलन equation किसी भी बिन्दु equation पर स्थानिकतः व्युत्क्रमणीय होता है।
(iv) 
से परिभाषित फलन equation समाकलनीय होता है।
(v) equation से परिभाषित फलन equation का (0, 0) पर एक चरम मान होता है।

Ques 34.

(क) निम्नलिखित सीमा ज्ञात कीजिए :
(i) equation
(ii) equation

 

(ख) बिन्दु (1,2) पर फलन equation का तृतीय टेलर बहुपद ज्ञात कीजिए।
(ग) केवल परिभाषाओं को लागू करके fxy(0,0) और fyx(0,0) ज्ञात कीजिए, जबकि फलन

 

 

के लिए इनका अस्तित्व होता हो।

Ques 35.

  (क) मान लीजिए

 

equation$
दिखाइए कि (0,0) पर सभी दिशाओं में f दिक् अवकलज होते हैं।

 

(ख) मान लीजिए equation और f, x और y का एक संततः अवकलनीय फलन है जिसके आंशिक अवकलज भी संततः अवकलनीय हैं। दिखाइए कि
equation$

 

(ग) मान लीजिए equation के तीन बिन्दु हैं।
|2b - a + 3c| ज्ञात कीजिए।

Ques 36.

(क) वक्रों equation और equation से परिबद्ध और equation के घनत्व वाले एक पतली शीट का गुरुत्व केन्द्र ज्ञात कीजिए।
(ख) equation और equation से परिबद्ध ठोस घनाकृति का द्रव्यमान ज्ञात कीजिए, जबकि घनत्व फलन, equation हो।

Ques 37.

 (क) ग्रीन प्रमेय का कथन दीजिए और इसकी सहायता से
equation का मान निकालिए,
जहाँ C, दीर्घवृत्त equation है।
(ख) पृष्ठ equation पर फलन equation के चरम मान ज्ञात कीजिए।

Ques 38.

 (क) equation के एक विवृत उपसमुच्चय D पर दो अवकलनीय फलनों f और g की फलनात्मक आश्रितता का आवश्यक प्रतिबंध बताने वाले प्रमेय का कथन दीजिए। निम्नलिखित फलनों f तथा g द्वारा परिभाषित इस प्रमेय को सत्यापित कीजिए।
equation equation$

(ख) अस्पष्ट फलन प्रमेय की सहायता से यह दिखाइए कि 1 के प्रतिवेश में एक ऐसा अवकलनीय फलन g होता है, जिससे कि (2,1) के प्रतिवेश में equation और equation जहाँ
equation से फलन F परिभाषित है। g'(y) भी ज्ञात कीजिए। 
(ग) equation द्वारा परिभाषित फलन f की (1, -1) पर स्थानीय व्युत्क्रमणीयता की जाँच कीजिए। फलन f के लिए एक प्रांत ज्ञात कीजिए जिसमें f व्युत्क्रमणीय है। 

Ques 39.

(क) (0,0) पर निम्नलिखित फलन f के सांतत्य और अवकलनीयता की जाँच कीजिए, जहाँ

 

(ख) फलन equation से परिभाषित फलन f का प्रांत और परिसर ज्ञात कीजिए। इस फलन के दो स्तर वक्र भी ज्ञात कीजिए। 

Ques 40.

(क) equation के मान निकालिए, जहाँ C equation से प्राप्त वक्र है। 
(ख) द्विश: समाकलन का प्रयोग करके दीर्घवृत्तज

 

Ques 41.

क) यदि equation तो a और b के मान ज्ञात कीजिए। 
(ख) मान लीजिए कि S और C equation के उपसमुच्चय हैं। S मूल-बिन्दु पर केन्द्र वाला एकक विवृत गोलक है तथा C विवृत घन equation। 
निम्नलिखित में से कौनसा कथन सत्य है? अपने उत्तर की पुष्टि कीजिए।
(i) equation
(ii) equation

(ग) निम्नलिखित फलनों के स्तर वक्र ज्ञात कीजिए :
(i) equation
(ii) equation
(iii) x-y
(iv) y / x

Ques 42.

 

 (क) क्या निम्नलिखित फलन equation श्वार्ज़-प्रमेय की आवश्यकताओं को (1,1) पर संतुष्ट करता है? अपने उत्तर की पुष्टि कीजिए। (4)
(ख) निम्नलिखित के स्तब्ध बिन्दु निर्धारित करके उनका वर्गीकरण कीजिए : (6)
(i) equation
(ii) equation

Ques 43.

State whether the following statements are True or False. Give short proof or a counter example in support of your answer.
a) In the Hopfield network, the neurons belonging to the same layer receive input from the neurons of the previous layer and send their value only to the neurons of the next layer.
b) The length of chromosomes to determine the maximum value of the set:


equation is 12.
c) The fuzzy relation (R) given below, is an equivalence relation.



equation
d) The Self Organizing Map (SOM) is a supervised learning technique.
e) In a single layer neural network, if equation, then the output is -1.

Ques 44.

 Determine the fuzzy relation T as a composition between the fuzzy relations R and S given below by using max-min and max-product:
equation
equation

Ques 45.

 State whether the following statements are True or False. Give short proof or a counter example in support of your answer.
a) In the Hopfield network, the neurons belonging to the same layer receive input from the neurons of the previous layer and send their value only to the neurons of the next layer.
b) The length of chromosomes to determine the maximum value of the set:

 



equation is 12.
c) The fuzzy relation (R) given below, is an equivalence relation.

 



equation
d) The Self Organizing Map (SOM) is a supervised learning technique.
e) In a single layer neural network, if equation, then the output is -1.

Ques 46.

 Determine the fuzzy relation T as a composition between the fuzzy relations R and S given below by using max-min and max-product:
equation
equation

Ques 47.

 

Solve the network to approximate the function:
equation
for equation, choosing the initial weights and bias as the random numbers.

Ques 48.

Verify whether the Genetic Algorithm (GA) improves the solution from one generation to the next generation, for the function given below:
Maximize:


equation
Subject to:


equation
Assume that chromosomes of length 6 are created at random and modified by Roulette-Wheel selection.

Ques 49.

 

 A single layer neural network is to have six inputs and three outputs. The outputs are continuous over the range 0 to 1. Now answer the following:
i) How many neurons are required?
ii) What are the dimensions of the weight matrix?
iii) What kind of transfer function could be used?
iv) Is a bias required? Give reasons.

Ques 50.

 Consider the single layer perception given below:

 

 

The activation function is:


equation
Obtain the output for each of the following input pattern:

Patterns  


p1
 

 


p2
 

 


p3
 

 


p4
 

 


x1
 

1 0 1 1
 


x2
 

0 1 0 1
 


x3
 

0 1 1 1

Ques 51.

 

 Consider the ADALINE filter with three neurons in the input layer having weights 3,1 and − 2and the input sequence ......., ,0,0,0 − 0,0,0,5,4 ,.....}. Find the filter output.

Ques 52.

Find the length and order of the following schema:

i) equation

ii) equation

iii) equation

iv) equation

Ques 53.

 Consider the fuzzy sets A and B defined on the interval [0, 5]. Their membership functions are:



equation$

 

and equation

Determine the membership function and graph them for each of the following:

i) AC, BC

ii) equation

iii) equation

iv) equation

v) equation

Ques 54.

 Let A and B be two Fuzzy sets as given below:
equation
equation
Determine the following:
i) Universe of discourse for Set A and Set B.
ii) Complements of Set A and Set B
iii) equation
iv) equation

Ques 55.

Implement AND function using McCulloch-Pitts neuron.

Ques 56.

 Out of three genetic operators viz. selection, cross-over and mutation, list and justify which operator or combination there of will be required for the following:

i) To fill the population with copies of the best individual from the population.
ii) For the convergence of an algorithm to good but sub-optimal solution.

Ques 57.

 

Approximate the function equation for equation, by solving 1-2-1 network, using Back propagation algorithm. The weighted structure and initial input are as follows:
Weighted structures are:
equation and bias equation
equation and bias equation
The initial input is 1.
Draw the architecture of the model. Perform one iteration.

Ques 58.

 Consider a dataset of five observations given in the following table, each of which has two features f1 and f2:

  x₁ x₂ x₃ x₄ x₅
f₁ 2 3 4 3 5
f₂ 6 7 5 4 6

Assume the number of cluster equation and the real number equation. Also, assume the initial cluster centers as equation and equation. Apply fuzzy c-mean algorithm to find the modified cluster center after one iteration.

Ques 59.

 Generate the population in the next iteration by using Roulette-Wheel criterion:

 


k
 

 


Fk
 

1 3.5
2 4.6
3 5
4 2.8
5 1.8

Ques 60.

Determine the equation-cut of the fuzzy set (A) are given below, at 0.7 and 0.2.
equation
Also, compare the equation-cut of the two outcomes, and give comments for status of equation-value variation.

Ques 61.

 Consider the following table for the connections between input neurons and the hidden layer neurons:

Input Neurons Hidden Layer Neurons Connection Weight
1 1 - 1
1 2 - 0.1
1 3 1
2 1 - 1
2 2 1
2 3 1
3 1 - 0.2
3 2 - 0.3
3 3 - 0.6

The connection weights from the hidden layer neurons to the output neurons are -0.6, -0.3 and -0.6, for the first, second and third neurons, respectively.

Corresponding threshold value for the output layer is 0.5 and for the hidden layer is 1.8, 0.005 and 0.2 for the first, second and third neurons, respectively.
i) Draw the diagram of the network.

 

ii) Write the output at each node.

Ques 62.

 

 Using diagram, show the difference between feed-forward neural network and recurrent neural network.

Ques 63.

 Computer the output for the neurons in the kohonen networks, the related data is given below:
i) Input to Kohnen neural network:
Input Neuron-1 equation
Input Neuron-2 equation
ii) Connected weights between the neurons are as given below:
equation
equation
equation
equation

Ques 64.

 Consider the two parents which are participating in partially mapped cross over as shown below:

Parent 1: C D | E A B |I H G F

Parent 2: A B | C D E |F G H I

Using partially mapped crossover assuming 2nd and 6th as the cross over sites, find the children solution.

 

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