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An Investigation on Hardware Implementation and Optimization of Spiking Neural Network

Mohammadi, Mahdi | 2015

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  1. Type of Document: M.Sc. Thesis
  2. Language: English
  3. Document No: 46912 (55)
  4. University: Sharif University of Technology, International Campus, Kish Island
  5. Department: Science and Engineering
  6. Advisor(s): Bagheri Shouraki, Saeed
  7. Abstract:
  8. Design of a spiking neural network suitable for electronic hardware implementation has been a hot research topic for a long time, in recent years implementation of spiking neural network in real time and biological scale has become important for scientists. This is due to the proximity of these networks to human brain, and the efforts led to the creation of numerous biological models and hardware which has been proposed in this context. This research includes two main parts, the first part is effort to implement a greater number of neurons per device and the second part proposes a communication system among devices to achieve biological scale. This work investigates novel neural elements and structure leading to revolutionary system architectures which emulate biological learning, and is multidisciplinary, which includes both experimental and theoretical research in the areas of novel devices, neural learning in terms of hardware implementation feasibility and costs, targeting large scale application. The envisaged neuromorphic systems will be capable of massively parallel computing, seamless implementation of complex tasks such as classification and pattern recognition
  9. Keywords:
  10. Spiking Neural Network ; Hardware Implementation ; Optimization ; Simulation ; Packed Based Communication

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