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- W339657584 abstract "Abstract : This thesis deals with the analysis of random data. Two approaches are discussed. The first approach is a Goodness of Fit test to determine whether or not random data samples are statistically consistent with a prespecified probability distribution. The well known Kolmogorov Smirnov test, Chi Square test, Q-Q Plots and P-P plots are reviewed and illustrated by means of several examples. A new algorithm, the Ozturk Algorithm, is introduced. The second approach deals with approximation of the underlying probability density function of random data samples. The previously mentioned well known tests are not suitable for this task. However, the Ozturk Algorithm provides a powerful solution for this problem with a nice graphical interpretation. Finally, computer simulated results obtained with the Ozturk Algorithm are presented and discussed." @default.
- W339657584 created "2016-06-24" @default.
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- W339657584 date "1995-09-01" @default.
- W339657584 modified "2023-09-24" @default.
- W339657584 title "High-Level Adaptive Signal Processing Architecture with Applications to Radar Non-Gaussian Clutter. Volume 2. A New Technique for Distribution Approximation of Random Data." @default.
- W339657584 doi "https://doi.org/10.21236/ada300902" @default.
- W339657584 hasPublicationYear "1995" @default.
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