tailieunhanh - Báo cáo hóa học: " Multi-dimensional model order selection"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Multi-dimensional model order selection | da Costa et al. EURASIP Journal on Advances in Signal Processing 2011 2011 26 http content 2011 1 26 o EURASIP Journal on Advances in Signal Processing a SpringerOpen Journal RESEARCH Open Access Multi-dimensional model order selection João Paulo Carvalho Lustosa da Costa1 Florian Roemer2 Martin Haardt2 and Rafael Timóteo de Sousa Jr1 Abstract Multi-dimensional model order selection MOS techniques achieve an improved accuracy reliability and robustness since they consider all dimensions jointly during the estimation of parameters. Additionally from fundamental identifiability results of multi-dimensional decompositions it is known that the number of main components can be larger when compared to matrix-based decompositions. In this article we show how to use tensor calculus to extend matrix-based MOS schemes and we also present our proposed multi-dimensional model order selection scheme based on the closed-form PARAFAC algorithm which is only applicable to multidimensional data. In general as shown by means of simulations the Probability of correct Detection PoD of our proposed multi-dimensional MOS schemes is much better than the PoD of matrix-based schemes. Introduction In the literature matrix array signal processing techniques are extensively used in a variety of applications including radar mobile communications sonar and seismology. To estimate geometrical physical parameters such as direction of arrival direction of departure time of direction of arrival and Doppler frequency the first step is to estimate the model order . the number of signal components. By taking into account only one dimension the problem is seen from just one perspective . one projection. Consequently parameters cannot be estimated properly for certain scenarios. To handle that multidimensional array signal processing which considers several dimensions is studied. These dimensions can correspond to time frequency or polarization but also spatial dimensions .

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