Artificial Neural Networks detailed syllabus for Electronics & Instrumentation Engineering (EIE), R18 regulation has been taken from the JNTUHs official website and presented for the students of B.Tech Electronics & Instrumentation Engineering branch affiliated to JNTUH course structure. For Course Code, Course Titles, Theory Lectures, Tutorial, Practical/Drawing, Credits, and other information do visit full semester subjects post given below. The syllabus PDF files can also be downloaded from the universities official website.
For all the other EIE 4th Year 1st Sem Syllabus for B.Tech R18 Regulation JNTUH scheme, visit Electronics & Instrumentation Engineering 4th Year 1st Sem R18 Scheme.
For all the (Professional Elective-4) subjects refer to Professional Elective-4 Scheme. The detail syllabus for artificial neural networks is as follows.
Prerequisite:
Nil
Course Objective:
For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
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Course Outcome:
Upon completing this course, the student will be able to
- Understand the similarity of Biological networks and Neural networks
- Perform the training of neural networks using various learning rules.
- Understanding the concepts of forward and backward propagations.
- Understand and Construct the Hopfield models.
Unit – I
Introduction: A Neural Network, Human Brain, Models of a Neuron, Neural Networks viewed as Directed Graphs, Network Architectures, Knowledge Representation, Artificial Intelligence and Neural Networks Learning Process: Error Correction Learning, Memory Based Learning, Hebbian Learning, Competitive, Boltzmann Learning, Credit Assignment Problem, Memory, Adaption, Statistical Nature of the Learning Process
Unit – II
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Unit – III
Back Propagation: Back Propagation and Differentiation, Hessian Matrix, Generalization, Cross Validation, Network Pruning Techniques, Virtues and Limitations of Back Propagation Learning, Accelerated Convergence, Supervised Learning
Unit – IV
Self-Organization Maps (SOM): Two Basic Feature Mapping Models, Self-Organization Map, SOM Algorithm, Properties of Feature Map, Computer Simulations, Learning Vector Quantization, Adaptive Patter Classification
Unit – V
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 pdfs platform to make students’s lives easier..
Text Books:
- Neural Networks a Comprehensive Foundations, Simon S Haykin, PHI Ed.,.
- Introduction to Artificial Neural Systems Jacek M. Zurada, JAICO Publishing House Ed. 2006.
Reference Books:
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 pdfs platform to make students’s lives easier..
For detail syllabus of all other subjects of B.Tech Electronics & Instrumentation Engineering 4th Year 1st Sem , visit EIE 4th Year 1st Sem syllabus subjects.
For B.Tech Electronics & Instrumentation Engineering (EIE) 4th Year results, visit JNTUH B.Tech Electronics & Instrumentation Engineering semester results direct link.