Neural Networks detailed Syllabus for Electronics & Communication Engineering (ECE), 2018 scheme has been taken from the VTUs official website and presented for the VTU students. For Course Code, Subject Names, Teaching Department, Paper Setting Board, Theory Lectures, Tutorial, Practical/Drawing, Duration in Hours, CIE Marks, Total Marks, Credits and other information, visit full semester subjects post given below. The Syllabus PDF files can also be downloaded from the official website of the university.
For all the other VTU ECE 7th Sem Syllabus for BE 2018 Scheme, visit Electronics & Communication Engineering 7th Sem 2018 Scheme.
For all the (Open Elective-B) subjects refer to Open Elective-B Scheme. The detail syllabus for neural networks is as follows.
Course Learning Objectives:
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Module-1
Introduction: Biological Neuron – Artificial Neural Model – Types of activation functions – Architecture: Feedforward and Feedback, Convex Sets, Convex Hull and Linear Separability, Non-Linear Separable Problem. XOR Problem, Multilayer Networks. Learning: Learning Algorithms, Error correction and Gradient Descent Rules, Learning objective of TLNs, Perceptron Learning Algorithm, Perceptron Convergence Theorem. L1, L2
Module-2
Supervised Learning: Perceptron learning and Non Separable sets, a-Least Mean Square Learning, MSE Error surface, Steepest Descent Search, |j-LMS approximate to gradient descent, Application of LMS to Noise Cancelling, Multi-layered Network Architecture, Back propagation Learning Algorithm, Practical consideration of BP algorithm. L1,L2, L3
Module-3
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Module-4
Attractor Neural Networks: Associative Learning Attractor Associative Memory, Linear Associative memory, Hopfield Network, application of Hopfield Network, Brain State in a Box neural Network, Simulated Annealing, Boltzmann Machine, Bidirectional Associative Memory. L1,L2, L3
Module-5
Self-organization Feature Map: Maximal Eigenvector Filtering, Extracting Principal Components, Generalized Learning Laws, Vector Quantization, Self-organization Feature Maps, Application of SOM, Growing Neural Gas. L1,L2, L3
Course Outcomes:
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Question Paper Pattern:
- Examination will be conducted for 100 marks with question paper containing 10 full questions, each of 20 marks.
- Each full question can have a maximum of 4 sub questions.
- There will be 2 full questions from each module covering all the topics of the module.
- Students will have to answer 5 full questions, selecting one full question from each module.
- The total marks will be proportionally reduced to 60 marks as SEE marks is 60
Text Books:
Neural Networks A Classroom Approach- Satish Kumar, McGraw Hill Education (India) Pvt. Ltd, Second Edition.
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 the detail Syllabus of all other subjects of BE (ECE) 7th Sem, visit Electronics & Communication Engineering 7th Sem Subjects.
For all (CBSE & Non-CBSC) BE/B.Tech results, visit VTU BE/B.Tech all semester results.