Publications

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2003
Soliman, E. A., M. A. El‐Gamal, and A. K. Abdelmageed, "Neural network model for the efficient calculation of Green's functions in layered media", International Journal of RF and Microwave Computer‐Aided Engineering, vol. 13, issue 2: Wiley Online Library, pp. 128-135, 2003. Abstract
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2002
El-Gamal, M. A., "Genetically evolved neural networks for fault classification in analog circuits", Neural Computing & Applications, vol. 11, no. 2: Springer, pp. 112–121, 2002. Abstract
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El-Gamal, M. A., "Genetically evolved neural networks for fault classification in analog circuits", Neural Computing & Applications, vol. 11, no. 2: Springer, pp. 112–121, 2002. Abstract
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El-Gamal, M. A., "Genetically evolved neural networks for fault classification in analog circuits", Neural Computing & Applications, vol. 11, issue 2: Springer, pp. 112-121, 2002. Abstract
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Soliman, E. A., A. K. Abdelmageed, and M. A. El-Gamal, "Neural computation of the MoM matrix elements for planar configurations", AEU-International Journal of Electronics and Communications, vol. 56, issue 3: Elsevier, pp. 155-162, 2002. Abstract
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1999
El-Gamal, M. A., and M. F. A. El-Yazeed, "A combined clustering and neural network approach for analog multiple hard fault classification", Journal of Electronic Testing, vol. 14, no. 3: Springer, pp. 207–217, 1999. Abstract
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El-Gamal, M. A., and M. F. A. El-Yazeed, "A combined clustering and neural network approach for analog multiple hard fault classification", Journal of Electronic Testing, vol. 14, no. 3: Springer, pp. 207–217, 1999. Abstract
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El-Gamal, M. A., and M. F. A. El-Yazeed, "A combined clustering and neural network approach for analog multiple hard fault classification", Journal of Electronic Testing, vol. 14, issue 3: Springer, pp. 207-217, 1999. Abstract
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1997
El-Gamal, M. A., "A knowledge-based approach for fault detection and isolation in analog circuits", Neural Networks, 1997., International Conference on, vol. 3: IEEE, pp. 1580–1584, 1997. Abstract
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El-Gamal, M. A., "A knowledge-based approach for fault detection and isolation in analog circuits", Neural Networks, 1997., International Conference on, vol. 3: IEEE, pp. 1580–1584, 1997. Abstract
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El-Gamal, M. A., "A knowledge-based approach for fault detection and isolation in analog circuits", Neural Networks, 1997., International Conference on, vol. 3: IEEE, pp. 1580-1584, 1997. Abstract
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1996
Abdulghafour, M., and M. A. El-Gamal, "A fuzzy logic system for analog fault diagnosis", Circuits and Systems, 1996. ISCAS'96., Connecting the World., 1996 IEEE International Symposium on, vol. 1: IEEE, pp. 97-100, 1996. Abstract
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1995
El-Gamal, M. A., A. S. O. Hassan, and H. L. Abdel-Malek, "A new approach for the selection of test points for fault diagnosis", Circuits and Systems, 1995. ISCAS'95., 1995 IEEE International Symposium on, vol. 3: IEEE, pp. 2019-2022, 1995. Abstract
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1990
Starzyk, J. A., and M. A. El-Gamal, "Artificial neural network for testing analog circuits", Circuits and Systems, 1990., IEEE International Symposium on: IEEE, pp. 1851–1854, 1990. Abstract
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Starzyk, J. A., and M. A. El-Gamal, "Artificial neural network for testing analog circuits", Circuits and Systems, 1990., IEEE International Symposium on: IEEE, pp. 1851–1854, 1990. Abstract
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Starzyk, J. A., and M. A. El-Gamal, "Artificial neural network for testing analog circuits", Circuits and Systems, 1990., IEEE International Symposium on: IEEE, pp. 1851-1854, 1990. Abstract
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El-Gamal, M. A., Fault location and parameter identification in analog circuits, : Ohio University, 1990. Abstract
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1988
Starzyk, J. A., and M. A. El-Gamal, "Diagnosabi 1 ity of Analog Circuits A Graph Theoretical Approach", Circuits and Systems, 1988., IEEE International Symposium on: IEEE, pp. 945-948, 1988. Abstract
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1984
Starzyk, J., and M. El-Gamal, "An optimization approach to fault location in analog circuits", Proc. IEEE Int. Symp. CAS, Montreal, pp. 456-459, 1984. Abstract
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1900
MA, E. G., and E. A. MMH, "On the Determination of Optimal Model Order for GMM-Based Text-Independent Speaker Identification", EURASIP Journal on Advances in Signal Processing, vol. 2004, issue 8: Hindawi Publishing Corporation, pp. 1078-1087, 1900. Abstract

Gaussian mixture models (GMMs) are recently employed to provide a robust technique for speaker identification. The determination of the appropriate number of Gaussian components in amodel for adequate speaker representation is a crucial but difficult problem. This number is in fact speaker dependent. Therefore, assuming a fixed number of Gaussian components for all speakers is not justified. In this paper, we develop a procedure for roughly estimating the maximum possible model order above which the estimation of model parameters becomes unreliable. In addition, a theoretical measure, namely, a goodness of fit (GOF) measure is derived and utilized in estimating the number of Gaussian components needed to characterize different speakers. The estimation is carried out by exploiting the distribution of the training data for each speaker. Experimental results indicate that the proposed technique provides results comparable to other well-known model selection criteria like the minimum description length (MDL) and the Akaike information criterion (AIC).