Neural Network
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Neural Network






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Neural Network Neural Network Presentation Transcript

  • NEURAL NETWORK Submitted by : Abhishek Sasan(500901515) Laleet Grover() Munish Kumar(500901505)
  • Content Definition Examples Types of Neural Networks Selection of NN Areas where NN is useful Applications Advantages Limitations SNNS
  • 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.
  • 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 algorithm they use
  • 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 w1 i2 w2 Output = f(i1w1 + Neuron i2w2 + i3w3 + bias) i3 w3 Bias
  • Areas where Neural Net May be Useful Pattern association Pattern classification Regularity detection Image processing Speech analysis Optimization problems
  • 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.
  • 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
  • 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 to explain any results that theyobtain
  • 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