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frequency domain algorithm with generalized residuals is developed.
In the first stage, a frequency domain algorithm is estimated and forecasted.
Well-developed algorithms in the first category include the Peterson-Gorenstein-Zierler algorithm [2], Berlekamp-Massey algorithm [2, 3], Euclidean algorithm [2, 3], frequency domain algorithm [2, 3], and step-by-step algorithm [4 7].
Nevertheless, in both data sets, the combined model works well because the frequency domain algorithm captures cyclical behavior, while the neural net is better able to capture short-term dependence and trending.
The potential errors arise from the fact that the above frequency domain algorithm allows calculating only the average decay times of the oxygen probe which is only a rough approximation.
In this study, P receiver functions have been calculated in the RTZ reference system with a frequency domain algorithm using multitaper correlation estimates (Park and Levin, 2000) with a frequency cut off of 0.2 Hz in order to image the deep lithospheric structure.
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In [12], both time domain and frequency domain algorithms with data training have been investigated.
The results show that, even though the frequency domain algorithms are sensitive to carrier frequency offsets, satisfactory frame detection and synchronization can be achieved in the frequency domain.
The spatial domain algorithms are simple and the watermark can be damaged easily, but the frequency domain algorithms can resist versus intensity attack and watermark information cannot be damaged easily [13].
Frequency domain algorithms provide an alternative for this issue and hence the watermarking schemes based on DCT [8], DWT, RDWT [9, 10] and SVD [11] have gained momentum in watermarking concepts.
The methods tested include nonlinear regressions, neural networks, frequency domain algorithms, GARCH models (which utilize the residual variance), state transition models, and models that combine elements of several techniques.
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