https://github.com/amey-thakur/computational-intelligence
ELEC 8330: Computational Intelligence [CI] | Semester IV | MEng Computer Engineering
https://github.com/amey-thakur/computational-intelligence
amey ameythakur associative-memory cnn computational-intelligence computer-engineering convolutional-neural-network convolutional-neural-networks engineering fuzzy-systems genetic-algorithm genetic-algorithms learning-vector-quantization master-of-engineering meng meng-ece radial-basis-function self-organizing-map university-of-windsor uwindsor
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ELEC 8330: Computational Intelligence [CI] | Semester IV | MEng Computer Engineering
- Host: GitHub
- URL: https://github.com/amey-thakur/computational-intelligence
- Owner: Amey-Thakur
- License: cc-by-4.0
- Created: 2024-02-06T11:42:25.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2026-02-21T01:49:48.000Z (4 months ago)
- Last Synced: 2026-02-25T12:38:30.230Z (4 months ago)
- Topics: amey, ameythakur, associative-memory, cnn, computational-intelligence, computer-engineering, convolutional-neural-network, convolutional-neural-networks, engineering, fuzzy-systems, genetic-algorithm, genetic-algorithms, learning-vector-quantization, master-of-engineering, meng, meng-ece, radial-basis-function, self-organizing-map, university-of-windsor, uwindsor
- Language: MATLAB
- Homepage: https://github.com/Amey-Thakur/MENG-COMPUTER-ENGINEERING
- Size: 19 MB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Citation: CITATION.cff
- Security: SECURITY.md
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README
# Computational Intelligence
### ELEC 8330 · Semester IV · MEng Computer Engineering
[](LICENSE)
[](https://www.uwindsor.ca)
[](https://www.uwindsor.ca/engineering/)
[](https://github.com/Amey-Thakur)
**A comprehensive academic archive for Computational Intelligence (ELEC 8330), documenting technical proficiency in neural architectures, fuzzy logic systems, evolutionary computing, and intelligent optimization standards within the Master of Engineering program.**
---
[Overview](#overview) · [Contents](#repository-contents) · [Reference Books](#reference-books) · [Personal Preparation](#personal-preparation) · [Assignments](#assignments) · [MATLAB Programs](#matlab-programs) · [Examinations](#examinations) · [Grades](#grades) · [Syllabus](#syllabus) · [Usage Guidelines](#usage-guidelines) · [License](#license) · [About](#about-this-repository) · [Acknowledgments](#acknowledgments)
---
## Overview
Computational Intelligence (ELEC 8330) is a specialized graduate-level course in the Master of Engineering (MEng) program at the University of Windsor. This course focuses on the exploration and implementation of advanced intelligent systems, encompassing neural networks, fuzzy logic, and genetic optimization for solving complex engineering paradigms.
### Course Objectives
The curriculum encompasses several key intelligent computing domains:
- **Neural Networks**: Mastering Hebbian learning, Associative Memories (AM), and Bidirectional Associative Memories (BAM).
- **Self-Organizing Maps**: Implementing competitive learning via SOM and Learning Vector Quantization (LVQ) architectures.
- **Fuzzy Systems**: Developing fuzzy set theory, reasoning models, and high-fidelity inference systems.
- **Genetic Optimization**: Leveraging evolutionary algorithms for global search and multi-objective optimization.
- **Intelligent Modeling**: Utilizing Radial Basis Function (RBF) networks and Convolutional Neural Networks (CNNs) for predictive analysis.
### Repository Purpose
This repository represents a curated collection of study materials, reference books, course assessments, and technical implementations compiled during my academic journey. The primary motivation for creating and maintaining this archive is simple yet profound: **to preserve knowledge for continuous learning and future reference**.
As I progress in my career, I recognize that the foundations of computational intelligence remain essential for solving complex engineering problems and explaining them with technical precision. This repository serves as my intellectual reference point: a resource I can return to for relearning concepts, reviewing methodologies, and strengthening understanding when needed.
**Why this repository exists:**
- **Knowledge Preservation**: To maintain organized access to comprehensive study materials beyond the classroom.
- **Continuous Learning**: To support lifelong learning by enabling easy revisitation of fundamental intelligent principles.
- **Academic Documentation**: To authentically document my learning journey through Computational Intelligence.
- **Community Contribution**: To share these resources with students and learners who may benefit from them.
> [!NOTE]
> All materials were created, compiled, and organized by me during the **Winter 2024** semester as part of my MEng degree requirements.
---
## Repository Contents
### Reference Books
This collection includes **comprehensive reference materials** covering all major topics:
| # | Resource | Focus Area |
|:-:|:---|:---|
| 1 | [Intelligent Computing - Hon K. Kwan](Reference%20Books/Hon%20K.%20Kwan%20-%20Intelligent%20Computing%20A%20Computing%20Approach%20to%20Artificial%20Intelligence.pdf) | Core textbook for advanced AI paradigms and neural computation. |
| 2 | [Worked Problems in Intelligent Computing](Reference%20Books/Hon%20K.%20Kwan%20-%20Matlab%20and%20Worked%20Problems%20in%20Intelligent%20Computing%20and%20System%20Design.pdf) | Practical exercise suite and MATLAB-integrated problem-solving. |
---
### Personal Preparation
Academic roadmap and administrative records for the **Winter 2024** session:
| # | Resource | Description |
|:-:|:---|:---|
| 1 | [Course Syllabus](ELEC8330%20Syllabus%20for%202024%20Winter%20Graduate%20Courses%20%28GA%2C20240323%29v3.pdf) | Official course outcomes and assessment specifications |
| 2 | [MEng Class Schedule](View%20My%20Classes%20-%20Winter%202024.pdf) | Enrollment record and pedagogical timeline |
| 3 | [Midterm Exam Revision](CI%20-%20Midterm%20Exam%20Revision.pdf) | Targeted theoretical synthesis for midterm evaluation |
---
### Assignments
A granular record of analytical assessments and tactical computational proofs conducted during the **Winter 2024** session.
| # | Assignment | Topics | Source Code | Report | Marks |
| :-: | :--- | :--- | :---: | :---: | :---: |
| 1 | **AM Quiz** | Associative Memories (AM) | — | [View](Assignments/AM%20Quiz%201.jpg) | 1 / 1 |
| 2 | **Assignment 1** | Associative Memories (AM/BAM) | [BAM](Assignments/Assignment%20-%20AM/Bidirectional_Associative_Memory.m) & [Hopfield](Assignments/Assignment%20-%20AM/Generalized_Hopfield_Step_Function.m) | [Q1A & Q1B](Assignments/Assignment%20-%20AM/Amey%20Mahendra%20Thakur%20-%20110107589%20-%202024-01-31.pdf) | 1 / 3 |
| 3 | **Assignment 2** | Self-Organizing Maps (SOM) | [SOM](Assignments/Assignment%20-%20SOM/Self_Organizing_Maps_Kohonen.m) | [Q1](Assignments/Assignment%20-%20SOM/Amey%20Mahendra%20Thakur%20-%20110107589%20-%202024-02-04.pdf) | 4 / 4 |
| 4 | **Assignment 3** | Learning Vector Quantization (LVQ) | [LVQ](Assignments/Assignment%20-%20LVQ/Learning_Vector_Quantization.m) | [Q1](Assignments/Assignment%20-%20LVQ/Amey%20Mahendra%20Thakur%20-%20110107589%20-%202024-02-17.pdf) | 3 / 3 |
| 5 | **Assignment 4** | Radial Basis Function (RBF) | [RBF](Assignments/Assignment%20-%20RBF/Radial_Basis_Function_Network.m) & [Optimization](Assignments/Assignment%20-%20RBF/Radial_Basis_Function_Optimization.m) | [Q1](Assignments/Assignment%20-%20RBF/Amey%20Mahendra%20Thakur%20-%20110107589%20-%202024-02-19.pdf) | 3 / 3 |
| 6 | **Assignment 5** | Fuzzy Sets (FSet) | [FSet](Assignments/Assignment%20-%20FSet/Fuzzy_Set_Theory_Operations.m) | [Q1](Assignments/Assignment%20-%20FSet/Attempt-2/Electronic%20Answer%20Book%20Submission%20-%20Thakur%2C%20Amey%20Mahendra%2C%20110107589%2C%2020240314.pdf) | 4 / 4 |
| 7 | **Assignment 6** | Fuzzy Logic and Reasoning (FLR) | — | [Q2a](Assignments/Assignment%20-%20FLR/Attempt-2/Electronic%20Answer%20Book%20Submission%20-%20Thakur%2C%20Amey%20Mahendra%2C%20110107589%2C%2020240320%20-%20Q2a.pdf) & [Q2b](Assignments/Assignment%20-%20FLR/Attempt-2/Electronic%20Answer%20Book%20Submission%20-%20Thakur%2C%20Amey%20Mahendra%2C%20110107589%2C%2020240320%20-%20Q2b.pdf) | 4 / 4 |
| 8 | **Assignment 7** | Fuzzy Systems (FSys) | — | [Q2a](Assignments/Assignment%20-%20FSys/Electronic%20Answer%20Book%20Submission%20-%20Thakur%2C%20Amey%20Mahendra%2C%20110107589%2C%2020240322%20-%20Q2a.pdf) & [Q2b](Assignments/Assignment%20-%20FSys/Electronic%20Answer%20Book%20Submission%20-%20Thakur%2C%20Amey%20Mahendra%2C%20110107589%2C%2020240322%20-%20Q2b.pdf) | 4 / 4 |
| 9 | **Assignment 8** | Genetic Algorithms (GA) | [GA](Assignments/Assignment%20-%20GA/Genetic_Algorithm_Implementation.m) | [Q1](Assignments/Assignment%20-%20GA/Electronic%20Answer%20Book%20Submission%20-%20Thakur%2C%20Amey%20Mahendra%2C%20110107589%2C%2020240326%20-%20Q1.pdf) & [Q2](Assignments/Assignment%20-%20GA/Electronic%20Answer%20Book%20Submission%20-%20Thakur%2C%20Amey%20Mahendra%2C%20110107589%2C%2020240326%20-%20Q2.pdf) | 0 / 4 |
| 10 | **Assignment 9** | Convolutional Neural Networks (CNNs) | — | [Q1](Assignments/Assignment%20-%20CNN/Electronic%20Answer%20Book%20Submission%20-%20Thakur%2C%20Amey%20Mahendra%2C%20110107589%2C%2020240331%20-%20Q1.pdf) | 2 / 2 |
---
## MATLAB Programs
Technical solutions and algorithmic models developed to implement neural networks, fuzzy logic, and genetic algorithms.
[](MATLAB/) [](https://www.mathworks.com/products/matlab.html) [](https://github.com/Amey-Thakur/COMPUTATIONAL-INTELLIGENCE) [](https://github.com/Amey-Thakur)
> [!TIP]
> Computational Intelligence is not merely the execution of algorithms; it is the **practical application of heuristics to simulate intelligent behavior**. These technical implementations focus on **functional problem-solving through computational modeling**, providing a reliable framework for the rigorous design and verification of intelligent systems.
| # | Topic | Source Code |
| :-: | :--- | :---: |
| 1 | **Binary to Decimal Conversion (Util)** | [View](MATLAB/Binary_to_Decimal_Conversion.m) |
| 2 | **Decimal to Binary Conversion (Util)** | [View](MATLAB/Decimal_to_Binary_Conversion.m) |
| 3 | **Fuzzy Set Theory Operations (FSet)** | [View](MATLAB/Fuzzy_Set_Theory_Operations.m) |
| 4 | **Fuzzy Set Theory (FSet)** | [View](MATLAB/Fuzzy_Set_Theory.m) |
| 5 | **Fuzzy Logic and Reasoning (FLR)** | [View](MATLAB/Fuzzy_Logic_and_Reasoning.m) |
| 6 | **Fuzzy Reasoning System (FSys)** | [View](MATLAB/Fuzzy_Reasoning_System.m) |
| 7 | **Generalized Hopfield Network (AM)** | [View](MATLAB/Generalized_Hopfield_Step_Function.m) |
| 8 | **Bidirectional Associative Memory (AM)** | [View](MATLAB/Bidirectional_Associative_Memory.m) |
| 9 | **Learning Vector Quantization (LVQ)** | [View](MATLAB/Learning_Vector_Quantization.m) |
| 10 | **Self-Organizing Maps (SOM)** | [View](MATLAB/Self_Organizing_Maps_Kohonen.m) |
| 11 | **Radial Basis Function Network (RBF)** | [View](MATLAB/Radial_Basis_Function_Network.m) |
| 12 | **Radial Basis Function Optimization (RBF)** | [View](MATLAB/Radial_Basis_Function_Optimization.m) |
| 13 | **Convolutional Neural Network (CNN)** | [View](MATLAB/Convolutional_Neural_Network.m) |
| 14 | **Genetic Algorithm Implementation (GA)** | [View](MATLAB/Genetic_Algorithm_Implementation.m) |
| 15 | **Genetic Algorithm Optimization (GA)** | [View](MATLAB/Genetic_Algorithm_Optimization.m) |
| 16 | **Genetic Algorithm Variant I (GA)** | [View](MATLAB/Genetic_Algorithm_Variant_I.m) |
| 17 | **Genetic Algorithm Variant II (GA)** | [View](MATLAB/Genetic_Algorithm_Variant_II.m) |
---
## Examinations
The following examinations represent key assessment milestones in Computational Intelligence, documenting technical proficiency through mid-term evaluations and the final summative assessment.
### Graduate Examination Records
| # | Examination Milestone | Date | Archival Deliverables | Marks |
| :---: | :--- | :---: | :--- | :---: |
| 1 | **Midterm Examination** | February 28, 2024 | • **[Midterm Revision Notes](CI%20-%20Midterm%20Exam%20Revision.pdf)** — by Amey Thakur
• [Q2A & Q2B Associative Memories Answer Sheet](Midterm%20Exam/AM-%20Amey%20Mahendra%20Thakur%20-%20110107589%20-%202024-02-28.pdf)
• [Q2A Radial Basis Function Answer Sheet](Midterm%20Exam/RBF%20-%20Amey%20Mahendra%20Thakur%20-%20110107589%20-%202024-02-28.pdf)
• [Q2B Radial Basis Function Answer Sheet](Midterm%20Exam/4RBF%20-%20Amey%20Mahendra%20Thakur%20-%20110107589%20-%202024-02-28.pdf)
• [Q2 Self-Organizing Maps Answer Sheet](Midterm%20Exam/SOM%20-%20Amey%20Mahendra%20Thakur%20-%20110107589%20-%202024-02-28.pdf) | 15 / 24 |
| 2 | **Final Examination** | April 15, 2024 | • **[Fuzzy Set Theory](Final%20Exam/MATLAB%20Programs/Fuzzy_Set_Theory.m)** — MATLAB Program
• [Q2A Fuzzy Sets Answer Sheet](Final%20Exam/Fuzzy%20Set%20Theory/Thakur,%20Amey%20Mahendra,%20110107589,%2020240415%20-%20FSet%20Q2a.pdf)
• [Q2B Fuzzy Sets Answer Sheet](Final%20Exam/Fuzzy%20Set%20Theory/Thakur,%20Amey%20Mahendra,%20110107589,%2020240415%20-%20FSet%20Q2b.pdf)
• **[Genetic Algorithm Optimization](Final%20Exam/MATLAB%20Programs/Genetic_Algorithm_Optimization.m)** — MATLAB Program
• [Q2A Genetic Algorithms Answer Sheet](Final%20Exam/Genetic%20Algorithms/Thakur,%20Amey%20Mahendra,%20110107589,%2020240415%20-%20GA%20Q2a.pdf)
• [Q2B Genetic Algorithms Answer Sheet](Final%20Exam/Genetic%20Algorithms/Thakur,%20Amey%20Mahendra,%20110107589,%2020240415%20-%20GA%20Q2b.pdf)
• **[Fuzzy Logic and Reasoning](Final%20Exam/MATLAB%20Programs/Fuzzy_Logic_and_Reasoning.m)** — MATLAB Program
• [Q2A Fuzzy Logic and Reasoning Answer Sheet](Final%20Exam/Fuzzy%20Logic%20and%20Reasoning/Thakur,%20Amey%20Mahendra,%20110107589,%2020240415%20-%20FLR%20Q2a.pdf)
• [Q2B Fuzzy Logic and Reasoning Answer Sheet](Final%20Exam/Fuzzy%20Logic%20and%20Reasoning/Thakur,%20Amey%20Mahendra,%20110107589,%2020240415%20-%20FLR%20Q2b.pdf)
• **[Fuzzy Reasoning System](Final%20Exam/MATLAB%20Programs/Fuzzy_Reasoning_System.m)** — MATLAB Program
• [Q2A Fuzzy Systems Answer Sheet](Final%20Exam/Fuzzy%20Reasoning%20System/Thakur,%20Amey%20Mahendra,%20110107589,%2020240415%20-%20FSys%20Q2a.pdf)
• [Q2B Fuzzy Systems Answer Sheet](Final%20Exam/Fuzzy%20Reasoning%20System/Thakur,%20Amey%20Mahendra,%20110107589,%2020240415%20-%20FSys%20Q2b.pdf)
• **[Convolutional Neural Network](Final%20Exam/MATLAB%20Programs/Convolutional_Neural_Network.m)** — MATLAB Program
• [Q3A Convolutional Neural Networks Answer Sheet](Final%20Exam/Convolutional%20Neural%20Network/Thakur,%20Amey%20Mahendra,%20110107589,%2020240415%20-%20CNN%20Q3a.pdf)
• [Q3B Convolutional Neural Networks Answer Sheet](Final%20Exam/Convolutional%20Neural%20Network/Thakur,%20Amey%20Mahendra,%20110107589,%2020240415%20-%20CNN%20Q3b.pdf) | 29 / 44 |
---
## Grades
The graded performance record documents academic achievement across various assessment categories including assignments, midterm evaluations, and the final examination.
| # | Assessment Category | Marks | Archival Record |
| :---: | :--- | :---: | :---: |
| 1 | Final Grades | 80 / 100 (80%) | [View Grades](CI%20Grades.pdf) |
---
## Syllabus
> **[Official ELEC 8330 Syllabus](ELEC8330%20Syllabus%20for%202024%20Winter%20Graduate%20Courses%20%28GA%2C20240323%29v3.pdf)**
> Complete graduate-level syllabus document for the **Winter 2024** session, including detailed course outcomes, theoretical modules, and assessment criteria for Computational Intelligence.
> [!IMPORTANT]
> Always verify the latest syllabus details with the official University of Windsor academic portal, as curriculum specifications for Computational Intelligence may undergo instructor-led adaptations across different sessions.
---
## Usage Guidelines
This repository is openly shared to support learning and knowledge exchange across the academic community.
**For Students**
Use these resources as templates for MATLAB scripting in intelligent systems, reference materials for fuzzy reasoning, and examples of evolutionary optimization. All content is organized to support self-paced learning.
**For Educators**
These materials may serve as curriculum references, technical benchmarks for neural architecture, or supplementary instructional content in computational intelligence. Attribution is appreciated when utilizing content.
**For Researchers**
The simulations and algorithmic implementations may provide insights into scholarly Computational Intelligence patterns and graduate-level intelligent systems documentation.
---
## License
This repository and all linked academic content are made available under the **Creative Commons Attribution 4.0 International License (CC BY 4.0)**. See the [LICENSE](LICENSE) file for complete terms.
> [!NOTE]
> **Summary**: You are free to share and adapt this content for any purpose, even commercially, as long as you provide appropriate attribution to the original author.
---
## About This Repository
**Created & Maintained by**: [Amey Thakur](https://github.com/Amey-Thakur)
**Academic Journey**: Master of Engineering in Computer Engineering (2023-2024)
**Institution**: [University of Windsor](https://www.uwindsor.ca), Windsor, Ontario
**Faculty**: [Faculty of Engineering](https://www.uwindsor.ca/engineering/)
This repository represents a comprehensive collection of study materials, reference books, technical assignments, and personal preparation notes curated during my academic journey. All content has been carefully organized and documented to serve as a valuable resource for students pursuing Computational Intelligence.
**Connect**: [GitHub](https://github.com/Amey-Thakur) · [LinkedIn](https://www.linkedin.com/in/amey-thakur) · [ORCID](https://orcid.org/0000-0001-5644-1575)
### Acknowledgments
Grateful acknowledgment to **Dr. Hon Kwan** for his exceptional instruction in Computational Intelligence, which played a pivotal role in shaping my analytical understanding of the subject. His clear and disciplined approach, along with his thorough explanation of neural networks, fuzzy logic, and genetic algorithms, made the subject both accessible and engaging. His distinguished expertise and commitment to academic excellence in **Computational Intelligence** are sincerely appreciated.
Grateful acknowledgment to **Archit Konde** for his outstanding understanding and distinguished peer mentorship. His exceptional ability to explain complex concepts with clarity and precision significantly enhanced my learning experience throughout the Computational Intelligence course. His dedication to academic excellence and scholarly support was fundamental to my mastery of advanced intelligent architectures and conceptual development.
Special thanks to the **mentors** and **peers** whose encouragement, discussions, and support contributed meaningfully to this learning experience.
---
[↑ Back to Top](#computational-intelligence)
[Overview](#overview) · [Contents](#repository-contents) · [Reference Books](#reference-books) · [Personal Preparation](#personal-preparation) · [Assignments](#assignments) · [MATLAB Programs](#matlab-programs) · [Examinations](#examinations) · [Grades](#grades) · [Syllabus](#syllabus) · [Usage Guidelines](#usage-guidelines) · [License](#license) · [About](#about-this-repository) · [Acknowledgments](#acknowledgments)
---
### 🎓 [MEng Computer Engineering Repository](https://github.com/Amey-Thakur/MENG-COMPUTER-ENGINEERING)
**Computer Engineering (M.Eng.) - University of Windsor**
*Semester-wise curriculum, laboratories, projects, and academic notes.*