Comparison from Accuracy Time between Artificial Neural Networks (ANN) of Matlab & Iterative Resolution with Gauss Seidal to Detect the Lesion
Keywords:
ANN, SOR, Relaxation, IterativeAbstract
In this paper we propose an iterative method (Gauss seidal technique (GS)) to detect the lesion than compared with Matlab program for neuronal network (ANN technique), where we can see clearly the high level of detection for the both methods, but for accuracy time our propose with G S present an excellent time in front of ANN technique, The program used is Matlab.
References
[1] Black, Noel and Moore, Shirley, "Gauss-Seidel Method", MathWorld.
[2] L. M. ADAMS AND H. JORDAN, Is SOR color-blind?, SIAM Journal on Scientificand Statistical Computing, 1985
[3] John Ashburner and all, " SPM12 Manual", Functional Imaging
[4] Abraham Berman, Robert J. Plemmons, Nonnegative Matrices in the Mathematical Sciences, 1994, SIAM. ISBN 0-89871-321-8.
[5] Golub, Gene H.; Van Loan, Charles F. (1996), Matrix Computations (3rd ed.), Baltimore: Johns Hopkins, ISBN 978-0-8018-5414-9.
[6] Black, Noel and Moore, Shirley, "Successive Overrelaxation Method", MathWorld.
[7] Yousef Saad, Iterative Methods for Sparse Linear Systems, 1st edition, PWS, 1996.
[8] Netlib's copy of "Templates for the Solution of Linear Systems", by Barrett et al.
[9] Richard S. Varga 2002 Matrix Iterative Analysis, Second ed. (of 1962 Prentice Hall edition), Springer-Verlag.
[10] David M. Young, Jr. Iterative Solution of Large Linear Systems, Academic Press, 1971. (reprinted by Dover, 2003)
[11] This article incorporates text from the article Successive_over-relaxation_method_-_SOR on CFD-Wiki that is under the GFDL license.
[12] Anand, R., Mehrotra, K., Mohan, C., and Ranka, S. Efficient classification for multiclass problems using modular neural networks.1995
[13] Bengio, Y. Neural networks for speech and sequence 1996
[14] International Thompson Computer Press, Boston, MA.
[15] Bengio, Y., Le Cun, Y., and Henderson, D. Globally trained handwritten word recognizer using spatial representation, space displacement neural networks and hidden Markov models. In Cowan, J., Tesauro, G., and Alspector,1994
[16] J., editors, Advances in Neural Information Processing Systems 6.
[17] Morgan Kaufmann, Cambridge, MA. Bishop, C. Neural networks for pattern recognition. Oxford University Press, Oxford.1995
[18] Burrascano, P. A norm selection criterion for the generalized delta rule. 1991
[19] DARFA Neural Network Study, AFCEA Int’l Press, Fairfax,Va.,1988
[20] J. Hertz, A. Krogh, and R.G. Palmer, Introduction to the “Theory of Neural Computation, Addison-Wesley, Reading, Mass.,1991.
[2] L. M. ADAMS AND H. JORDAN, Is SOR color-blind?, SIAM Journal on Scientificand Statistical Computing, 1985
[3] John Ashburner and all, " SPM12 Manual", Functional Imaging
[4] Abraham Berman, Robert J. Plemmons, Nonnegative Matrices in the Mathematical Sciences, 1994, SIAM. ISBN 0-89871-321-8.
[5] Golub, Gene H.; Van Loan, Charles F. (1996), Matrix Computations (3rd ed.), Baltimore: Johns Hopkins, ISBN 978-0-8018-5414-9.
[6] Black, Noel and Moore, Shirley, "Successive Overrelaxation Method", MathWorld.
[7] Yousef Saad, Iterative Methods for Sparse Linear Systems, 1st edition, PWS, 1996.
[8] Netlib's copy of "Templates for the Solution of Linear Systems", by Barrett et al.
[9] Richard S. Varga 2002 Matrix Iterative Analysis, Second ed. (of 1962 Prentice Hall edition), Springer-Verlag.
[10] David M. Young, Jr. Iterative Solution of Large Linear Systems, Academic Press, 1971. (reprinted by Dover, 2003)
[11] This article incorporates text from the article Successive_over-relaxation_method_-_SOR on CFD-Wiki that is under the GFDL license.
[12] Anand, R., Mehrotra, K., Mohan, C., and Ranka, S. Efficient classification for multiclass problems using modular neural networks.1995
[13] Bengio, Y. Neural networks for speech and sequence 1996
[14] International Thompson Computer Press, Boston, MA.
[15] Bengio, Y., Le Cun, Y., and Henderson, D. Globally trained handwritten word recognizer using spatial representation, space displacement neural networks and hidden Markov models. In Cowan, J., Tesauro, G., and Alspector,1994
[16] J., editors, Advances in Neural Information Processing Systems 6.
[17] Morgan Kaufmann, Cambridge, MA. Bishop, C. Neural networks for pattern recognition. Oxford University Press, Oxford.1995
[18] Burrascano, P. A norm selection criterion for the generalized delta rule. 1991
[19] DARFA Neural Network Study, AFCEA Int’l Press, Fairfax,Va.,1988
[20] J. Hertz, A. Krogh, and R.G. Palmer, Introduction to the “Theory of Neural Computation, Addison-Wesley, Reading, Mass.,1991.
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Published
2015-10-08
How to Cite
El Kourd, K., Naoul, A., & MAlki, A. (2015). Comparison from Accuracy Time between Artificial Neural Networks (ANN) of Matlab & Iterative Resolution with Gauss Seidal to Detect the Lesion. American Scientific Research Journal for Engineering, Technology, and Sciences, 14(2), 53–64. Retrieved from https://asrjetsjournal.org/index.php/American_Scientific_Journal/article/view/975
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