Synthetic aperture radar (SAR) has proven to be a powerful remote sensing instrument for underground and obscured object detection. However, SAR echoes are often contaminated by radio frequency interferences (RFI) from multiple broadcasting stations. Essentially, RFI suppression problem is one-dimensional stationary time series denoising problem. This article proposed a novel RFI suppression al...

Ionospheric modeling across the Indian low latitudes continues to be a challenging task because of day-to-day variability pertaining underlying complex equatorial and latitude electrodynamics. In this paper, we aimed at developing an ionospheric Total Electron Content (TEC) model based on Singular Spectrum Analysis (SSA) using Global Positioning System (GPS)-TEC observations (from 2009 2019) Be...

In this chapter we present a nonlinear enhancement of a linear method, the singular system analysis (SSA), which can identify potentially predictable or relatively regular processes, such as cycles and oscillations, in a background of colored noise. The first step in the distinction of a signal from noise is a linear transformation of the data provided by the SSA. In the second step, the dynami...

An extension of the Monte Carlo Singular System Analysis (MC SSA) is described, based on evaluating and testing regularity of dynamics of the SSA modes against the colored noise null hypothesis, in addition to the test based on variance (eigenvalues). The application of the regularity index, computed from a coarse-grained estimation of mutual information, enhances the test sensitivity and relia...

As an essential tool for secure communications, adaptive steganography aims to communicate secret information with the least security cost. Inspired by Ranking Priority Profile (RPP), we propose a novel two-step cost function in this paper. The RPP mainly includes three rules, i.e. Complexity-First rule, Clustering rule and Spreading design function. We use two-dimensional Singular Spectrum Ana...

Centrifugal compressor machinery is subject to a potentially damaging phenomenon called surge at low mass flow rates. This effect may be preceded by phenomena known as inlet recirculation — reversal upstream of the impeller. A methodology isolate characteristic feature for monitoring centrifugal instability presented in this study. The based on nonparametric time series analysis technique singu...

Microseismic (MS) monitoring technology has been widely used to monitor ground pressure disasters. However, the underground mining environment is complex and contains many types of noise sources. Furthermore, traditional recognition method entails a process with low accuracy for MS signals, so it difficult serve safe production mines. Therefore, this study established hybrid model combining sin...

Abstract Gravity recovery and climate experiment (GRACE) GRACE Follow-On (GRACE-FO) are Earth’s gravity satellite missions with hydrological monitoring applications. However, caused by measuring instrumental problems, there several temporal missing values in the dataset of two where a long gap between mission also exists. Recent studies utilized different gap-filling methodologies to fill those...

Alcoholism is a widely affected disorder that leads to critical brain deficiencies such as emotional and behavioural impairments. One of the prominent sources detect alcoholism by analysing Electroencephalogram (EEG) signals. Previously, most works have focused on detecting using various machine deep learning algorithms. This paper has used novel algorithm named Sliding Singular Spectrum Analys...

Abstract In this research, a new method based on singular spectrum analysis (SSA) and fuzzy entropy is developed for damage detection thin wall-like structures, the normalized employed as an indicator to identify severity of damage. The lead zirconate titanate (PZT) transducers are used in research generate detect Lamb waves. During detection, collected signals from PZT sensors firstly decompos...