NEURAL NETWORK           Submitted by :           Abhishek Sasan(500901515)           Laleet Grover()           Munish Kum...
Content Definition Examples Types of Neural Networks Selection of NN Areas where NN is useful Applications Advantag...
DefinitionA neural network is a computationalmethod inspired by studies of the brain andnervous systems in biological org...
Example :Single Neuron
Example :Three Layers Neural Net
Neural NetworkThey can be distinguished by:   their type (feed forward or feed back)   their structure   the learning a...
Types of Neural Network
Single Layer Feed forward Network
Multi -Layer Feed forward Network
Feed Back Network
Selection of Neural Nets
Perceptron
Multi-Layer-Perceptron
Back propagation Net
Hopfield Net
Kohonen Feature Map
How Do Neural Networks Work ?The output of a neuron is a function of theweighted sum of the inputs plus a bias       i1  ...
Areas where Neural Net May be Useful Pattern association Pattern classification Regularity detection Image processing...
Three Main ApplicationsConcurrent simulation, where results of an ANNmodel are compared with results of a less realistic ...
Why Use Neural NetworksAbility to learn : NN’s figure out how to perform their function on theirownDetermine their func...
Advantages : Neural NetworkHandle partial lack of system understandingCreate adaptive models (models that canlearn)
Limitations The operational problem encounteredwhen attempting to simulate the parallelismof neural networks Instability...
Neural Network Software Neural network software is used to stimulate, research,develop and apply artificial neural networ...
Neural Network
Neural Network
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Neural Network

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Neural Network

  1. 1. NEURAL NETWORK Submitted by : Abhishek Sasan(500901515) Laleet Grover() Munish Kumar(500901505)
  2. 2. Content Definition Examples Types of Neural Networks Selection of NN Areas where NN is useful Applications Advantages Limitations SNNS
  3. 3. DefinitionA neural network is a computationalmethod inspired by studies of the brain andnervous systems in biological organisms.A Computing system made of a number ofsimple, highly interconnected processingelements, which process information by theirdynamic state response to external input.
  4. 4. Example :Single Neuron
  5. 5. Example :Three Layers Neural Net
  6. 6. Neural NetworkThey can be distinguished by: their type (feed forward or feed back) their structure the learning algorithm they use
  7. 7. Types of Neural Network
  8. 8. Single Layer Feed forward Network
  9. 9. Multi -Layer Feed forward Network
  10. 10. Feed Back Network
  11. 11. Selection of Neural Nets
  12. 12. Perceptron
  13. 13. Multi-Layer-Perceptron
  14. 14. Back propagation Net
  15. 15. Hopfield Net
  16. 16. Kohonen Feature Map
  17. 17. How Do Neural Networks Work ?The output of a neuron is a function of theweighted sum of the inputs plus a bias i1 w1 i2 w2 Output = f(i1w1 + Neuron i2w2 + i3w3 + bias) i3 w3 Bias
  18. 18. Areas where Neural Net May be Useful Pattern association Pattern classification Regularity detection Image processing Speech analysis Optimization problems
  19. 19. Three Main ApplicationsConcurrent simulation, where results of an ANNmodel are compared with results of a less realistic butvalidated common model to avoid a non expectedbehavior of the Neural-Net.ANN as sub-components of a global model, to modelsubsystems that would be hard to model commonlybecause of a lack of understanding.Adaptive models, "models that can learn", accordingto an error feedback such model would be able to adaptruntime to situations that hasnt been taken into account.
  20. 20. Why Use Neural NetworksAbility to learn : NN’s figure out how to perform their function on theirownDetermine their function based only upon sample inputsAbility to generalizei.e. produce reasonable outputs for inputs it has not beentaught how to deal with
  21. 21. Advantages : Neural NetworkHandle partial lack of system understandingCreate adaptive models (models that canlearn)
  22. 22. Limitations The operational problem encounteredwhen attempting to simulate the parallelismof neural networks Instability to explain any results that theyobtain
  23. 23. Neural Network Software Neural network software is used to stimulate, research,develop and apply artificial neural networks, biologicalneural networks Simulators usually have some form of built-in visualization to monitor the training process

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