• Login
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Statistics

    View Usage StatisticsView Google Analytics Statistics

    Study of communication schemes for multiple neural processing nodes

    Thumbnail
    View/Open
    201311032.pdf (1.331Mb)
    Date
    2015
    Author
    Mehta, Nilay V.
    Metadata
    Show full item record
    Abstract
    Over the past few years variety of hardware for implementing Artificial Neural Networks (ANN) has been designed. The most basic approach to speed up any ANN algorithm, is to parallelize processing. However, the existing wired strategies are not easily scalable and are also expensive. This thesis aims to provide low cost, easily scalable architecture for implementation of ANN, targeted for microcontrollers and FPGA architectures. With wired strategies, it is difficult to have scalable architecture with multiple Processing Nodes (PNs). Scalability of the same architecture can be improved by enabling wireless communication between the PNs. In this thesis, different strategies for implementation ofANNhave been analyzed, which considers two different types of PNs (Arduino R and Spartan3E R ) and various communication strategies (I2C with different speeds, Zigbee beacon enabled, Zigbee Non-beacon enabled, Zigbee GTS mode and TDMA scheme). Comparison of all these communication protocols have been carried out in terms of performance (speed) and energy. In this thesis, Nearest-Neighbour-Mesh (NNM) structure for the implementation is considered, where an application consists of 1024 neurons and 1024 synapses per neuron. The analysis has been carried out by varying number of PNs available for implementing this application. For simulation of all the wireless strategies, NS2 (Network Simulator) is used. For estimating computation time for Arduino and Spartan3E, Arduino software (Arduino 1.6.2) and Xilinx ISE Design Suite 14.7 R is used, respectively.
    URI
    http://drsr.daiict.ac.in/handle/123456789/563
    Collections
    • M Tech Dissertations [923]

    Resource Centre copyright © 2006-2017 
    Contact Us | Send Feedback
    Theme by 
    Atmire NV
     

     


    Resource Centre copyright © 2006-2017 
    Contact Us | Send Feedback
    Theme by 
    Atmire NV