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Trends in Applied Sciences Research
  Year: 2008 | Volume: 3 | Issue: 3 | Page No.: 242-252
DOI: 10.3923/tasr.2008.242.252
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A Comparison of RK-Fourth Orders of Variety of Means on Multilayer Raster CNN Simulation

R. Ponalagusamy and S. Senthilkumar

In this study, an adaptable algorithm for simulating CNN arrays is implemented using various means such as Arithmetic Mean (AM), Centroidal Mean (CM), Harmonic Mean (HM), Contra Harmonic Mean (CoM), Heronian Mean (HeM), Geometric Mean (GM) and Root Mean Square (RMS). The role of the simulator is that it is capable of performing raster simulation for any kind as well as any size of input image. It is a powerful tool for researchers to investigate the potential applications of CNN. This study proposes an efficient pseudo code exploiting the latency properties of Cellular Neural Networks along with well known Runge-Kutta (RK) fourth order numerical integration algorithms. Simulation results and comparison have also been presented to show the efficiency of the various means in numerical integration algorithms. It is observed that the RK-Arithmetic Mean (AM) outperforms well in comparison with other means.
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  •    Local Truncation Error for the Parallel Runge-Kutta-Fifth Order Methods
How to cite this article:

R. Ponalagusamy and S. Senthilkumar, 2008. A Comparison of RK-Fourth Orders of Variety of Means on Multilayer Raster CNN Simulation. Trends in Applied Sciences Research, 3: 242-252.

DOI: 10.3923/tasr.2008.242.252






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