Department of Voice and Sound Technology, Institute for Language and Speech Processing / "Athena" R.C., Maroussi, Paradissos Amaroussiou, Greece.
Comput Math Methods Med. 2012;2012:917695. doi: 10.1155/2012/917695. Epub 2012 Feb 22.
This paper presents a new state-space method for spectral estimation that performs decimation by any factor, it makes use of the full set of data and brings further apart the poles under consideration, while imposing almost no constraints to the size of the Hankel matrix (model order), as decimation increases. It is compared against two previously proposed techniques for spectral estimation (along with derived decimative versions), that lie among the most promising methods in the field of spectroscopy, where accuracy of parameter estimation is of utmost importance. Moreover, it is compared against a state-of-the-art purely decimative method proposed in literature. Experiments performed on simulated NMR signals prove the new method to be more robust, especially for low signal-to-noise ratio.
本文提出了一种新的谱估计状态空间方法，可按任意因子抽取，它利用了完整的数据集合，并在抽取增加时进一步分离所考虑的极点，同时对汉克尔矩阵（模型阶数）的大小几乎没有限制。该方法与两种以前提出的谱估计技术（以及派生的抽取版本）进行了比较，这些技术是光谱学领域最有前途的方法之一，其中参数估计的准确性至关重要。此外，还与文献中提出的一种最先进的纯抽取方法进行了比较。在模拟 NMR 信号上进行的实验证明，新方法更加稳健，尤其是在低信噪比情况下。
