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11th IEEE Symposium on Computers and Communications (ISCC'06)
Wavelet Based RDNN for Software Reliability Estimation
Cagliari, Sardinia, Italy
June 26-June 29
ISBN: 0-7695-2588-1
Adam Smiarowski, Jr., Oakland University, USA
Hoda S. Abdel-Aty-Zohdy, Oakland University, USA
Mostafa Hashem Sherif, AT&T Bell Labs, USA
Hemal Shah, Oakland University, USA
Using the wavelet basis in Recurrent Dynamic Neural Network (RDNN) can improve the failure event estimation of software defect tracking in telecommunications. Non-linearity of the system is represented by proper selection of the wavelet function. This RDNN handles noisy data and enhances the speed of convergence as compared with alternate approaches. A new adaptive RDNN is presented where software deployment testing observations are used to synthesize intrinsic model parameters.
Citation:
Adam Smiarowski, Jr., Hoda S. Abdel-Aty-Zohdy, Mostafa Hashem Sherif, Hemal Shah, "Wavelet Based RDNN for Software Reliability Estimation," iscc, pp.312-317, 11th IEEE Symposium on Computers and Communications (ISCC'06), 2006
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