JNTUK R16 3-2 Artificial Neural Networks Material PDF Download


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


  • 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


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

Download UNIT-1 Material PDF


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

Download UNIT-2 Material PDF


Feedback Neural Networks: Analysis of linear auto adaptive feed forward networks, Analysis of pattern storage Networks, Stochastic Networks & Stimulated Annealing, Boltzmann machine

Download UNIT-3 Material PDF


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

Download UNIT-4 Material PDF


Architectures for Complex Pattern Recognition Tasks: Associative memory, Pattern mapping Stability – Plasticity dilemma: ART, temporal patterns, Pattern visibility: Neocognitron

Download UNIT-5 Material PDF


Applications of Neural Networks: Pattern classification, Associative memories, Optimization, Applications in Image Processing, Applications in decision making

Download UNIT-6 Material PDF


  1. B.Yagnanarayana“Artificial Neural Networks”, PHI


  1. Laurene Fausett ,“Fundamentals of Neural Networks”, Pearson Education
  2. Simon Haykin , “Neural Networks”, Second Edition


  • 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

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