Artificial Neural Networks Seminar Report with PPT


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What is a Neural Network?

An Artificial Neural Network (ANN) is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurones) working in unison to solve specific problems. ANNs, like people, learn by example. An ANN is configured for a specific application, such as pattern recognition or data classification, through a learning process. Learning in biological systems involves adjustments to the synaptic connections that exist between the neurones. This is true of ANNs as well.

Artificial Neural Networks Seminar Report

Page Length : 31

Content :

    • Introduction to Neural Networks
      • What is a neural network?
      • Historical background
      • Why use neural networks?
      • Neural networks versus conventional computers – a comparison
    • Human and Artificial Neurones – investigating the similarities
      • How the Human Brain Learns?
      • From Human Neurones to Artificial Neurones
    • An Engineering approach
      • A simple neuron – description of a simple neuron
      • Firing rules – How neurones make decisions
      • Pattern recognition – an example
      • A more complicated neuron
    • Architecture of neural networks
      • Feed-forward (associative) networks
      • Feedback (autoassociative) networks
      • Network layers
      • Perceptrons
    • The Learning Process
      • Transfer Function
      • An Example to illustrate the above teaching procedure
      • The Back-Propagation Algorithm
    • Applications of neural networks
      • Neural networks in practice
      • Neural networks in medicine
        • Modelling and Diagnosing the Cardiovascular System
        • Electronic noses – detection and reconstruction of odours by ANNs
        • Instant Physician – a commercial neural net diagnostic program
      • Neural networks in business
        • Marketing
        • Credit evaluation
      • Conclusion
      • References

Artificial Neural Networks Presentation Report (PPT)

Page Length : 26

Content :

  • Introduction
  • History
  • Biological Neuron Model
  • Artificial Neuron Model
  • Artificial Neural Network
  • Neural Network Architecture
  • Learning
  • Back propagation Algorithm
  • Applications
  • Advantages
  • Conclusion

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Product Name

Artificial Neural Networks Seminar Report with PPT

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1.12 MB


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College, Semester, University

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Created By

Siddharth Vairagi (NIT Agartala)

Uploaded By

Roop Chandra




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