Artificial Neural Network
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Follow on Instagram for UpdatesArtificial Neural Network Syllabus — Unit-wise Content
The official GTU curriculum for Artificial Neural Network (subject code ME01000701) as prescribed for IT · Semester 1 divides the course into 8 units, covering 15 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (ME01000701)Unit 1 Introduction to artificial neural nets, motivation and applications
- Basic neuron model
- Hebbian learning rule
- neural network structures 3 10 w. e. f
- Academic Year: A.Y. 2024-25 Semester: 1st Semester Category of the Course: PEC Program Name: Master of Engineering Level: PG Branch: Information Technology Course / Subject Code : ME01000701 Course / Subject Name : Artificial Neural Network
Unit 2 Single layer perceptron, nonlinear activation function, Delta rule
- The least mean square (LMS) algorithm
- perceptron convergence theorem
Unit 3 Supervised learning
- multilayer networks
- Backpropagation Learning General practices for network training and testing
- applications of multilayer perceptron
Unit 4 Recurrent Backprop0gation networks; Backpropagation through time
- learning algorithm
- Radial basis function (RBF) networks and regularization theory
Unit 7 Unsupervised learning, principal components analysis, competitive
- networks Hopfield networks and Boltzmann machines
Unit 8 Kohonen’s self organizing feature maps
- Algorithms and applications 4 5
Unit 9 Information theoric approach to model selection, independent
- components analysis 3 5
Unit 11 Artificial Neural Systems
- Overview of Actual Models
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