In this paper, the mathematical derivation of the underlying probability distribution function
for the normalized least-squares wavelet spectrogram is presented. The impact of empirical …

The identification and removal of outliers in time series are important problems in numerous
fields. In this paper, a novel method (BCP-HI) is proposed to enhance the accuracy of outlier …

When ordinary principal component analysis (PCA) is employed to analyze the position time
series of a regional global navigation satellite system (GNSS) station network, the GNSS …

High-precision indoor positioning problems have attracted considerable attention recently.
The indoor ranging and positioning method based on wireless fidelity (WIFI) round-trip-time …

The improved SSA (ISSA) method is widely recognized for directly extracting signals from
gappy time-series without requiring prior interpolation. However, it is rather time consuming …

The measurement of data over time and/or space is of utmost importance in a wide range of
domains from engineering to physics. Devices that perform these measurements, such as …

We propose a nonparametric minimum entropy method for estimating an optimal velocity
from position time series, which may contain unknown noise, data gaps, loading effects …

Global navigation satellite systems (GNSS) provides a novel means for deformation
monitoring, which is an important guarantee for structures. Accurately separating its linear …

The stochastic calibration of low-cost and consumer grade inertial sensors has recently
become very important due to their wide-spread utilization in a multitude of mass-market …

The increasing use of low-cost inertial sensors in various mass-market applications
necessitates their accurate stochastic modeling. Such task faces challenges due to outliers …