Abstract This paper is mainly concerned with the application of different parametric spectral estimation techniques on deoxyribonucleic acid (DNA) sequences. The objective of this study is to allow the analysis of these sequences for useful information extraction such as exon information. It is known that the exon, if existing, is represented with a spectral peak at the normalized frequency of 0.667. A comparison study is presented between Burg, Covariance, Modified Covariance, Yule-Walker, MUltiple SIgnal Classification (MUSIC) and Auto-Regressive Moving Average (ARMA) techniques for efficient representation of DNA sequences in the frequency domain for further exon prediction. Moreover, to filter the out-of-band noise that appears in the frequency domain in the prediction process, an inverse Chebyshev bandpass filter tuned at 0.667 is utilized. The obtained results reveal the importance of bandpass filtering and ensure that Burg, Covariance and Modified Covariance techniques are the best for exon prediction with a detection range of about 60 dB.

中文翻译：

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用于 DNA 外显子预测的参数谱估计技术的有效实现

摘要 本文主要关注不同参数谱估计技术在脱氧核糖核酸（DNA）序列上的应用。本研究的目的是允许分析这些序列以提取有用的信息，例如外显子信息。已知外显子（如果存在）在归一化频率为 0.667 处用光谱峰表示。介绍了 Burg、协方差、修正协方差、Yule-Walker、多重信号分类 (MUSIC) 和自回归移动平均 (ARMA) 技术之间的比较研究，用于在频域中有效表示 DNA 序列以进行进一步的外显子预测。此外，为了过滤在预测过程中出现在频域中的带外噪声，使用了一个调谐在 0.667 的逆切比雪夫带通滤波器。