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On non-Gaussian characterization of shipping traffic underwater noise

机译:船舶交通水下噪声的非高斯表征

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This paper is originated from the desire to obtain classification and characterization of a vast category of signals which have been ignored in conventional classical applications, like the ones concerning shipping traffic underwater noise. Current interest in the field of communications, the falling price of personal computers (based on 80486 or pentium), and the availability of extremely high level languages, have lead the authors to develop this work. The paper is documented in several stages: initially the non parametric and parametric approach, for the nongaussian and nonlinear signal processing are described, and proposed by system which divides interferences sources into classes A, B and C is introduced. In order to achieve to the main goal of the present paper various mathematical techniques have been adopted such as example the bispectrum approach (H.O.S. Theory), and Gabor expansion. After the nonlinearity identification due to transient signals, the processing system is applied to class B interferences. Although the heavy computational complexity in various stages, i.e. the calculation of the coefficients used for the Gabor processing and the routine for the bispectrum estimation, the results confirm the wide extendibility of the D. Middleton approach. This work has been developed in the contest of the MAST-I-SNECOW Project ( Shipping Noise Evaluation in Coastal Waters) of the European Community Marine Science and Technology Program.
机译:本文源于对各种信号进行分类和表征的愿望,这些信号在传统的经典应用中已被忽略,例如与水下交通噪音相关的信号。当前对通信领域的兴趣,个人计算机的价格下降(基于80486或pentium)以及极高级语言的可用性,促使作者开发了这项工作。本文分几个阶段进行了记录:首先介绍了用于非高斯和非线性信号处理的非参数方法和参数方法,并介绍了将干扰源分为A,B和C类的系统提出的方法。为了达到本发明的主要目的,已经采用了各种数学技术,例如双谱法(H.O.S. Theory)和Gabor展开法。在由于瞬态信号引起的非线性识别之后,将处理系统应用于B类干扰。尽管各个阶段的计算复杂度很高,即用于Gabor处理的系数的计算和用于双谱估计的例程,但结果证实了D. Middleton方法的广泛可扩展性。这项工作是在欧洲共同体海洋科学与技术计划的MAST-I-SNECOW项目(沿海水域船舶噪声评估)竞赛中开发的。

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