Signal Processing in Power State Variables for Noise Cancellation of Electromagnetic Environment. Issue 1 (October 2014)

• Record Type: Journal Article
• Authors: Ikuta, Akira; Ogawa, Hitoshi; Orimoto, Hisako
• Is Part Of: Electrical engineering in Japan. Volume 189:Issue 1(2014)
• Page Start: 36
• Page End: 46
• Publication Date: 2014-10
• Subjects: Electrical engineering -- Periodicals; 621.30952
• DOI: 10.1002/eej.22578
• Languages: English
• ISSNs: 0424-7760

Abstract

<abstract abstract-type="main"> <title>SUMMARY</title> <p>The specific signal in an actual electromagnetic wave frequently shows some very complex fluctuation forms of non‐Gaussian type owing to natural, social, and human factors. Furthermore, the observed data are inevitably contaminated by the background noise of arbitrary distribution type. In these situations, it is often desirable to estimate several evaluation quantities such as the peak value, the amplitude probability distribution, the average crossing rate, the pulse spacing, duration distributions, and so on of the specific signal. Without losing their mutual relationships, it is indispensable to estimate the probability distribution or the original wave fluctuation form of itself of the specific signal based on the observed noise data. In this study, static and dynamic signal processing methods for estimating a specific signal with the existence of background noise of non‐Gaussian distribution forms are proposed. More specifically, by paying attention to the power state variable for a specific signal in the electromagnetic environment, which exhibits complex probability distribution forms, a new type of signal processing method for noise cancellation is proposed. In the case of considering the power state variable, a physical mechanism of contamination by a background noise can be reflected in the noise cancellation method by using an additive property between the specific signal and background noise. The proposed method positively utilizes the additive property of power state variable in the derivation process of the noise cancellation method. Furthermore, the effectiveness of the proposed theoretical method is experimentally confirmed by applying it to an estimation problem in actual electromagnetic environment.</p> </abstract>