About Lab
The Neural Networks and Fuzzy Logic (NNFL) Lab is a specialized facility that provides hands-on experience in artificial intelligence (AI), machine learning (ML), and soft computing techniques. This lab focuses on artificial neural networks (ANN), fuzzy logic (FL), and their hybrid models for solving complex real-world problems.
Objectives of the Lab
- To understand the fundamentals of neural networks and fuzzy logic.
- To implement and analyse different Artificial Neural Networks (ANNs).
- To design and simulate Fuzzy Logic Controllers (FLCs).
- To develop hybrid neuro-fuzzy models for decision-making and control applications.
- To apply MATLAB, Python, and other computational tools for simulating NNFL models.
- To explore real-world applications of NNFL in robotics, automation, image processing, and data analysis.
Key Components of the Lab
- Software Tools Used
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- MATLAB with Neural Network & Fuzzy Logic Toolboxes
- Hardware Components (for real-time applications)
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- Microcontrollers (Arduino, Raspberry Pi, ESP32) for fuzzy and neural-based control
People
- Faculty Coordinator: Ms. Ritambhra Katoch
- Lab Technician: Mr. Ashish Kumar