Artificial Neural Network Syllabus — Government College of Engineerin…
Full syllabus, topics and curated resources for Artificial Neural Network (Government College of Engineering and Technology, Jammu).
Neural network characteristics and learning rules, different neural network architectures, applications of neural networks, and fuzzy logic
- Subject code: ECT-1704
- University: Government College of Engineering and Technology, Jammu
- Course: BE (2022 onwards)
- Branch: ECE
- Semester: 7
Artificial Neural Network syllabus
Unit 1: Neural Network Characteristics
- History and Principles of Neural Networks
- Artificial Neural Net Terminology
- Model of a Neuron
- Network Topology
- Supervised and Unsupervised Learning
Unit 2: Learning Rules
- Perceptron and Linear Separability
- Basic Learning Laws
- Hebb's Rule
- Delta Rule and Widrow-Hoff (LMS) Learning Rule
- Correlation Learning Rule
- Instar and Outstar Learning Rules
- Competitive Learning and K-Means Clustering
- Kohonen's Feature Maps
Unit 3: Different Neural Networks
- Radial Basis Function Networks
- Back Propagation Algorithm
- Feed Forward Networks
- ART (Adaptive Resonance Theory) Networks
Unit 4: Application of Neural Nets
- Pattern Recognition Using Back Propagation Networks
- Associative Memories
- Linear Regression Using Neural Networks