VARIATION MINIMIZATION BASED ELECTROCARDIOGRAM ARTIFACTS REMOVAL FOR LOCAL FIELD POTENTIALS FROM NEUROSTIMULATOR

Variation Minimization Based Electrocardiogram Artifacts Removal for Local Field Potentials From Neurostimulator

Local field potential (LFP) recorded by sensing-enabled neurostimulators provided chronic observation of deep brain activities for the research of brain disorders.However, the contamination from the electrocardiogram (ECG) deteriorated the extraction Turmeric of effective information from LFP.This study proposed a novel algorithm based on minimizin

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Epidemiological pattern of blunt trauma chest in Western India

Introduction: Chest injuries constitute an important aspect of Portable Sinks trauma.Despite high mortality rates, but the majority of patients with thoracic injuries can be managed by a simple intervention like tube thoracostomy.Aims and Objective: The aim of this study is to analyze the epidemiological pattern of chest injury and assess the outco

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Determination of Planetary Boundary Layer height with Lidar Signals Using Maximum Limited Height Initialization and Range Restriction (MLHI-RR)

The planetary boundary layer height (PBLH) is a vital parameter to characterize the surface convection, which determines the diffusion of air pollutants.The accurate inversion of PBLH is extremely important for the study of aerosol concentrations, in order to predict air quality and provide weather forecast.Aerosol lidar, a powerful remote sensing

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Hyperspectral Image Classification Based on Fusion of Guided Filter and Domain Transform Interpolated Convolution Filter

In recent years, the spatial texture features obtained by filtering have become a hot research topic to improve hyperspectral image classification, but spatial correlation information is often lost in spatial texture information extraction.To solve this problem, a spectral-spatial classification method based on guided filtering and by the algorithm

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