Artificial Neural Network detailed syllabus scheme for Electrical Engineering (EE), 2018-19 onwards has been taken from the DBATU official website and presented for the Bachelor of Technology students. For Subject Code, Course Title, Lecutres, Tutorials, Practice, Credits, and other information, do visit full semester subjects post given below.
For 6th Sem Scheme of Electrical Engineering (EE), 2018-19 Onwards, do visit EE 6th Sem Scheme, 2018-19 Onwards. For the Elective-VI scheme of 6th Sem 2018-19 onwards, refer to EE 6th Sem Elective-VI Scheme 2018-19 Onwards. The detail syllabus for artificial neural network is as follows.
Artificial Neural Network Syllabus for Electrical Engineering (EE) 3rd Year 6th Sem 2018-19 DBATU
Pre-requisite:
For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdf platform to make students’s lives easier.
.
Course Outcomes:
- To review basic principles of neuron structure.
- To understand building blocks artificial neural network.
- To understand different networks of ANN
- To develop different algorithm for learning.
- To study and understand Fuzzy neural networks.
Unit 1
Introduction and ANN Structure : Biological neurons and artificial neurons. Model of an ANN. Activation functions used in ANNs. Typical classes of network architectures. Mathematical Foundations and Learning mechanisms : Re-visiting vector and matrix algebra. State-space concepts. Concepts of optimization. Error-correction learning. Memory-based learning. Hebbian learning. Competitive learning.
Unit 2
For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdf platform to make students’s lives easier..
Unit 3
Feedforward ANN : Structures of Multi-layer feedforward networks. Back propagation algorithm. Back propagation – training and convergence. Functional approximation with back propagation. Practical and design issues of back propagation learning.
Unit 4
Radial Basis Function Networks : Pattern separability and interpolation. Regularization Theory.Regularization and RBF networks.RBF network design and training. Approximation properties of RBF
Unit 5
For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdf platform to make students’s lives easier..
Unit 6
Fuzzy Neural Networks : Neuro-fuzzy systems. Background of fuzzy sets and logic. Design of fuzzy stems. Design of fuzzy ANNs
Reference Book:
NPTEL course
For detail syllabus of all subjects of Electrical Engineering (EE) 6th Sem 2018-19 onwards, visit EE 6th Sem Subjects of 2018-19 Onwards.