JNTUK R16 3-2 Artificial Neural Networks Material PDF Download
Students those who are studying JNTUK R16 ECE Branch, Can Download Unit wise R16 3-2 Artificial Neural Networks (ANN) Material/Notes PDFs below.
JNTUK R16 3-2 Artificial Neural Networks Material PDF Download
OBJECTIVES:
- To Introduce the concept of Artificial Neural Networks , Characteristics, Models of Neuron, Learning Rules, Learning Methods, Stability and Convergence
- To study the basics of Pattern Recognition and Feed forward Neural Networks
- To study the basics of Feedback neural networks and Boltzmann machine
- To introduce the Analysis of Feedback layer for different output functions, Pattern Clustering and Mapping networks
- To study the Stability, Plasticity, Neocognitron and Different applications of Neural Networks
UNIT-1
Basics of Artificial Neural Networks Introduction: Biological Neural Networks, Characteristics of Neural Networks, Models of Neuron, Topology, Basic Learning Rules Activation and Synaptic Dynamics: Activation Dynamic Models, Synaptic Dynamic Models, Learning Methods, Stability & Convergence, Recall in Neural Networks
UNIT-2:
Functional Units of ANN for Pattern Recognition Tasks: Pattern Recognition problem Basic Fundamental Units, Pattern Recognition Tasks by the Functional Units Feed forward Neural Networks: Analysis of Pattern Association Networks, Analysis of Pattern Classification Networks, Analysis of Pattern Mapping Networks
UNIT-3:
Feedback Neural Networks: Analysis of linear auto adaptive feed forward networks, Analysis of pattern storage Networks, Stochastic Networks & Stimulated Annealing, Boltzmann machine
UNIT-4:
Competitive Learning Neural Networks: Components of a Competitive Learning Network, Analysis of Feedback layer for Different Output Functions, Analysis of Pattern Clustering Networks and Analysis of Feature Mapping Network
UNIT-5:
Architectures for Complex Pattern Recognition Tasks: Associative memory, Pattern mapping Stability – Plasticity dilemma: ART, temporal patterns, Pattern visibility: Neocognitron
UNIT-6:
Applications of Neural Networks: Pattern classification, Associative memories, Optimization, Applications in Image Processing, Applications in decision making
TEXT BOOKS:
- B.Yagnanarayana“Artificial Neural Networks”, PHI
REFERENCE BOOKS:
- Laurene Fausett ,“Fundamentals of Neural Networks”, Pearson Education
- Simon Haykin , “Neural Networks”, Second Edition
OUTCOMES:
- This Course introduces Artificial Neural Networks and Learning Rules and Learning methods
- Feed forward and Feedback Neural Networks are introduced
- Applications of Neural Networks in different areas are introduced
