Vittoria Bruni , Rosanna Campagna , Domenico Vitulano
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引用次数: 0
Abstract
Multicomponent signals play a key role in many application fields, such as biology, audio processing, seismology, air traffic control and security. They are well represented in the time-frequency plane where they are mainly characterized by special curves, called ridges, which carry information about the instantaneous frequency (IF) of each signal component. However, ridges identification usually is a difficult task for signals having interfering components and requires the automatic localization of time-frequency interference regions (IRs). This paper presents a study on the use of the frequency parameter of a hyperbolic-polynomial penalized spline (HP-spline) to predict the presence of interference regions. Since HP-splines are suitably designed for signal regression, it is proved that their frequency parameter can capture the change caused by the interaction between signal components in the time-frequency representation. In addition, the same parameter allows us to define a data-driven approach for IR localization, namely HP-spline Signal Interference Detection (HP-SID) method. Numerical experiments show that the proposed HP-SID can identify specific interference regions for different types of multicomponent signals by means of an efficient algorithm that does not require explicit data regression.
多分量信号在生物、音频处理、地震学、空中交通管制和安全等许多应用领域都发挥着重要作用。多分量信号在时频平面上有很好的表现,其主要特征是特殊曲线(称为脊),其中包含每个信号分量的瞬时频率(IF)信息。然而,对于具有干扰成分的信号来说,脊线识别通常是一项艰巨的任务,需要自动定位时频干扰区域(IR)。本文研究了如何利用双曲-多项式惩罚样条曲线(HP-样条曲线)的频率参数来预测干扰区域的存在。由于 HP 样条适合于信号回归,因此证明了其频率参数可以捕捉时频表示中信号成分之间相互作用所引起的变化。此外,同一参数还允许我们定义一种数据驱动的红外定位方法,即 HP 样条信号干扰检测(HP-SID)方法。数值实验表明,所提出的 HP-SID 可以通过无需明确数据回归的高效算法,识别不同类型多分量信号的特定干扰区域。
期刊介绍:
The purpose of the journal is to provide a forum for the publication of high quality research and tutorial papers in computational mathematics. In addition to the traditional issues and problems in numerical analysis, the journal also publishes papers describing relevant applications in such fields as physics, fluid dynamics, engineering and other branches of applied science with a computational mathematics component. The journal strives to be flexible in the type of papers it publishes and their format. Equally desirable are:
(i) Full papers, which should be complete and relatively self-contained original contributions with an introduction that can be understood by the broad computational mathematics community. Both rigorous and heuristic styles are acceptable. Of particular interest are papers about new areas of research, in which other than strictly mathematical arguments may be important in establishing a basis for further developments.
(ii) Tutorial review papers, covering some of the important issues in Numerical Mathematics, Scientific Computing and their Applications. The journal will occasionally publish contributions which are larger than the usual format for regular papers.
(iii) Short notes, which present specific new results and techniques in a brief communication.