Homework Help is Here – Start Your Trial Now!
Engineering
Computer Engineering
۸۳ TELEGRAM اسئلة المد الاول.pdf تم University of Baghdad Al-Khawarzmi College of Eng. Mechatronics Engineering Dept. 2022-2023 Mid Term 1 Q1: Consider the classification problem defined below. Class: 4 Year Subject: Artificial Intelligence Time: 90 minutes Date: 04/12/2022 Lecturer: Ayad Jasim 1. Use Decision boundary to design a single-neuron perceptron to solve this problem graphically by choosing weight vectors and bias. II. Test your solution with all six input vectors. III. Classify the following input vectors with your solution. P₁ = Px= Po= Pio Q2: Use Perceptron learning rule to solve the classification problem below with P₁ = With W (0) [00] b(0)-0, (Test 15 iterations only) Q3: Consider the prototype patterns shown to the right. Are these patterns orthogonal? II. Use the Hebb rule to design an autoassociator for these patterns. III. Use the Pseudoinverse rule to design an autoassociator for these patterns. ٢:٤٩ 5 P₁ P: Q4: 1/Design a Hamming network to distinguish between P II. Test your design with a (p,) and (P.), where and P₂ Pr , and P₁ = PA Ő L

۸۳ TELEGRAM اسئلة المد الاول.pdf تم University of Baghdad Al-Khawarzmi College of Eng. Mechatronics Engineering Dept. 2022-2023 Mid Term 1 Q1: Consider the classification problem defined below. Class: 4 Year Subject: Artificial Intelligence Time: 90 minutes Date: 04/12/2022 Lecturer: Ayad Jasim 1. Use Decision boundary to design a single-neuron perceptron to solve this problem graphically by choosing weight vectors and bias. II. Test your solution with all six input vectors. III. Classify the following input vectors with your solution. P₁ = Px= Po= Pio Q2: Use Perceptron learning rule to solve the classification problem below with P₁ = With W (0) [00] b(0)-0, (Test 15 iterations only) Q3: Consider the prototype patterns shown to the right. Are these patterns orthogonal? II. Use the Hebb rule to design an autoassociator for these patterns. III. Use the Pseudoinverse rule to design an autoassociator for these patterns. ٢:٤٩ 5 P₁ P: Q4: 1/Design a Hamming network to distinguish between P II. Test your design with a (p,) and (P.), where and P₂ Pr , and P₁ = PA Ő L

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
See similar textbooks
icon
Related questions
Question
۸۳ TELEGRAM اسئلة المد الاول.pdf تم University of Baghdad Al-Khawarzmi College of Eng. Mechatronics Engineering Dept. 2022-2023 Mid Term 1 Q1: Consider the classification problem defined below. Class: 4 Year Subject: Artificial Intelligence Time: 90 minutes Date: 04/12/2022 Lecturer: Ayad Jasim 1. Use Decision boundary to design a single-neuron perceptron to solve this problem graphically by choosing weight vectors and bias. II. Test your solution with all six input vectors. III. Classify the following input vectors with your solution. P₁ = Px= Po= Pio Q2: Use Perceptron learning rule to solve the classification problem below with P₁ = With W (0) [00] b(0)-0, (Test 15 iterations only) Q3: Consider the prototype patterns shown to the right. Are these patterns orthogonal? II. Use the Hebb rule to design an autoassociator for these patterns. III. Use the Pseudoinverse rule to design an autoassociator for these patterns. ٢:٤٩ 5 P₁ P: Q4: 1/Design a Hamming network to distinguish between P II. Test your design with a (p,) and (P.), where and P₂ Pr , and P₁ = PA Ő L
Transcribed Image Text:۸۳ TELEGRAM اسئلة المد الاول.pdf تم University of Baghdad Al-Khawarzmi College of Eng. Mechatronics Engineering Dept. 2022-2023 Mid Term 1 Q1: Consider the classification problem defined below. Class: 4 Year Subject: Artificial Intelligence Time: 90 minutes Date: 04/12/2022 Lecturer: Ayad Jasim 1. Use Decision boundary to design a single-neuron perceptron to solve this problem graphically by choosing weight vectors and bias. II. Test your solution with all six input vectors. III. Classify the following input vectors with your solution. P₁ = Px= Po= Pio Q2: Use Perceptron learning rule to solve the classification problem below with P₁ = With W (0) [00] b(0)-0, (Test 15 iterations only) Q3: Consider the prototype patterns shown to the right. Are these patterns orthogonal? II. Use the Hebb rule to design an autoassociator for these patterns. III. Use the Pseudoinverse rule to design an autoassociator for these patterns. ٢:٤٩ 5 P₁ P: Q4: 1/Design a Hamming network to distinguish between P II. Test your design with a (p,) and (P.), where and P₂ Pr , and P₁ = PA Ő L
Expert Solution
steps

Step by step

Solved in 2 steps

SEE SOLUTIONCheck out a sample Q&A here
Blurred answer
Recommended textbooks for you
Computer Networking: A Top-Down Approach (7th Edi…
Computer Networking: A Top-Down Approach (7th Edi…
Computer Engineering
ISBN:
9780133594140
Author:
James Kurose, Keith Ross
Publisher:
PEARSON
Computer Organization and Design MIPS Edition, Fi…
Computer Organization and Design MIPS Edition, Fi…
Computer Engineering
ISBN:
9780124077263
Author:
David A. Patterson, John L. Hennessy
Publisher:
Elsevier Science
Network+ Guide to Networks (MindTap Course List)
Network+ Guide to Networks (MindTap Course List)
Computer Engineering
ISBN:
9781337569330
Author:
Jill West, Tamara Dean, Jean Andrews
Publisher:
Cengage Learning
Concepts of Database Management
Concepts of Database Management
Computer Engineering
ISBN:
9781337093422
Author:
Joy L. Starks, Philip J. Pratt, Mary Z. Last
Publisher:
Cengage Learning
Prelude to Programming
Prelude to Programming
Computer Engineering
ISBN:
9780133750423
Author:
VENIT, Stewart
Publisher:
Pearson Education
Sc Business Data Communications and Networking, T…
Sc Business Data Communications and Networking, T…
Computer Engineering
ISBN:
9781119368830
Author:
FITZGERALD
Publisher:
WILEY
SEE MORE TEXTBOOKS