# Nonlinear signal processing

These data is state estimation accuracy of the proposed algorithm.

These data includes the position estimation accuracy and velocity estimation accuracy of the algorithm.

The data are explained below:

rmse_ckf_1 and rmse_ckf_2 are the position accuracy and speed accuracy of CKF，respectively.

rmse_ukf_1 and rmse_ukf_2 are the position accuracy and speed accuracy of UKF，respectively.

rmse_ssmckf1_2 and rmse_ssmckf1_2 are the position accuracy and speed accuracy of SSM-RCKF when the similarity function is selected as exponentiac function, respectively.

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Ground Penetrating Radar (GPR) has a wide range of applications such as detection of buried mines, pipes and wires. GPR has been used as a near-surface remote sensing technique, and its working principle is based on electromagnetic (EM) wave theory. Here proposed data set is meant for data driven surrogate modelling based Buried Object Characterization. The considered problem of estimating geophysical parameters of a buried object is 2D. The training and testing scenarios include B-scan images (2D data), which contain 16 pairs of A-scan (concatenated forms of A-scans).

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The proliferation of efficient edge computing has enabled a paradigm shift of how we monitor and interpret urban air quality. Coupled with the dense spatiotemporal resolution realized from large-scale wireless sensor networks, we can achieve highly accurate realtime local inference of airborne pollutants. In this paper, we introduce a novel Deep Neural Network architecture targeted at latent time-series regression tasks from continuous, exogenous sensor measurements, based on the Transformer encoder scheme and designed for deployment on low-cost power-efficient edge processors.

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**A Cu-doped TiO2 -x nanoscale memristor is fabricated, whose faithful mathematical model is established based on the memristive behaviors and its switching mechanism. Using this model, a chaotic system is constructed and its complex dynamics are investigated by numerical simulations. Furthermore, hardware experiments are also designed to verify the model in chaotic circuit.**

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This dataset is proposed for human activity recognition tasks. The static activities including sitting, standing, and laying, as well as walking, running, cycling, and walking upstairs/downstairs. Each activity lasts for 2 minutes, 50 subjects were involved in the experiments.

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A qualitative and quantitative extension of the chaotic models used to generate self-similar traffic with long-range dependence (LRD) is presented by means of the formulation of a model that considers the use of piecewise affine onedimensional maps. Based on the disaggregation of the temporal series generated, a valid explanation of the behavior of the values of Hurst exponent is proposed and the feasibility of their control from the parameters of the proposed model is shown.

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This Matlab model and the included results are submitted as reference for the paper ''.

Presenting a comparative study of the Sequential Unscented Kalman Filter (SUKF), Least-squares (LS) Multilateration and standard Unscented Kalman Filter (UKF) for localisation that relies on sequentially received datasets.

The KEWLS and KKF approach presents a novel solution using Linear Kalman Filters (LKF) to extrapolate individual sensor measurements to a synchronous point in time for use in LS Multilateration.

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This article explores the required amount of time series points from a high-speed computer network to accurately estimate the Hurst exponent. The methodology consists in designing an experiment using estimators that are applied to time series addresses resulting from the capture of high-speed network traffic, followed by addressing the minimum amount of point required to obtain in accurate estimates of the Hurst exponent.

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This **open access webpage** has all miscellaneous data and design related to ß-machines- Non-Medical, ß-Biomedical machines, processed ECG, sensors, heart and breathing patterns, sounds, finite element analysis, mathematics and BioEngineering.

As all only want free download and I used to get emails to share data freely ; with IEEE DataPort I had began journey of Data, so I will do update data as long as IEEE DataPort allows it or as long as I can or . I might also upload same data externally to other site.

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