References
- Bader , M. 1987 . A comparative study of new truncation error estimates and intrinsic accuracies of some higher order Runge–Kutta algorithms . Comput. Chem. , 11 : 121 – 124 .
- Bader , M. 1988 . A new technique for the early detection of stiffness in coupled differential equations and application to standard Runge–Kutta algorithms . Theor. Chem. Acc. , 99 : 215 – 219 .
- Butcher , J. C. 1987 . The Numerical Analysis of Ordinary Differential Equations: Runge–Kutta and General Linear Methods , Chichester : John Wiley .
- Butcher , J. C. 1983 . Numerical Methods for Ordinary Differential Equations , Chichester : John Wiley .
- Chua , L. O. and Yang , L. 1988 . Cellular neural networks: theory . IEEE Trans. Circuits Syst. , 35 : 1257 – 1272 .
- Chua , L. O. and Yang , L. 1988 . Cellular neural networks: applications . IEEE Trans. Circuits Syst. , 35 : 1273 – 1290 .
- Devarajan , G. , Murugesh , V. and Murugesan , K. 2006 . Numerical solution of second-order Robot arm control problem using Runge-Kutta Butcher algorithm . Int. J. Comput. Math. , 83 : 345 – 356 .
- Lee , C.-C. and de Gyvez , P. 1994 . Single-layer CNN simulator . Int. Symp. Circuits Syst. , 6 : 217 – 220 .
- Murugesh , V. and Murugesan , K. 2004 . Comparison of numerical integration algorithms in Raster CNN simulation . Lect. Notes Comput. Sci. , 3285 : 115 – 122 .
- Murugesh , V. and Murugesan , K. 2005 . Simulation of cellular neural networks using the RK butcher algorithm . Int. J. Manage. Syst. , 21 : 65 – 78 .
- Murugesh , V. and Murugesan , K. 2006 . Simulation of time-multiplexing cellular neural networks with numerical integration algorithms . Lect. Notes Comput. Sci. , 3991 : 115 – 122 .
- Nossek etal , J. A. 1992 . Cellular neural networks: theory and circuit design . Int. J. Circuit Theory Appl. , 20 : 533 – 553 .
- Oliveira , S. C. 1999 . Evaluation of effectiveness factor of immobilized enzymes using Runge–Kutta–Gill method: how to solve mathematical undetermination at particle center point? . Bioprocess Eng. , 20 : 85 – 187 .