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[Keyword] difference equations(3hit)

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  • Analysis of Block Delivery Delay in Network Coding-Based Delay Tolerant Networks

    Juhua PU  Xingwu LIU  Nima TORABKHANI  Faramarz FEKRI  Zhang XIONG  

     
    PAPER-Network

      Vol:
    E96-B No:1
      Page(s):
    135-142

    An important factor determining the performance of delay tolerant networks (DTNs) is packet delivery delay. In this paper, we study the block delivery delay of DTN with the epidemic routing scheme based on random linear network coding (RLNC). First, simulations show that the influence of relay buffer size on the delivery delay is not as strong in RLNC-based routing as it is in replica-based routing. With this observation,we can simplify the performance analysis by constraining the buffer of the relay node to just one size. Then we derive the cumulative distribution function (CDF) of block delivery delay with difference equations. Finally, we validate the correctness of our analytical results by simulations.

  • Analysis of the Sign-Sign Algorithm Based on Gaussian Distributed Tap Weights

    Shin'ichi KOIKE  

     
    PAPER-Adaptive Signal Processing

      Vol:
    E83-A No:8
      Page(s):
    1551-1558

    In this paper, a new set of difference equations is derived for transient analysis of the convergence of adaptive FIR filters using the Sign-Sign Algorithm with Gaussian reference input and additive Gaussian noise. The analysis is based on the assumption that the tap weights are jointly Gaussian distributed. Residual mean squared error after convergence and simpler approximate difference equations are further developed. Results of experiment exhibit good agreement between theoretically calculated convergence and that of simulation for a wide range of parameter values of adaptive filters.

  • Derivation and Applications of Difference Equations for Adaptive Filters Based on a General Tap Error Distribution

    Shin'ichi KOIKE  

     
    PAPER-Digital Signal Processing

      Vol:
    E79-A No:12
      Page(s):
    2166-2175

    In this paper stochastic aradient adaptive filters using the Sign or Sign-Sign Algorithm are analyzed based upon general assumptions on the reference signal, additive noise and particularly jointly distributed tap errors. A set of difference equations for calculating the convergence process of the mean and covariance of the tap errors is derived with integrals involving characteristic function and its derivative of the tap error distribution. Examples of echo canceller convergence with jointly Gaussian distributed tap errors show an excellent agreement between the empirical results and the theory.