scholarly journals An investigation of time efficiency in wavelet-based Markov parameter extraction methods

1998 ◽  
Author(s):  
A. Robertson ◽  
K. Park
Keyword(s):  
Parameter Extraction ◽  
Extraction Methods ◽  
Time Efficiency ◽  
Markov Parameter

Open quantum system parameters for light harvesting complexes from molecular dynamics

2015 ◽  
Vol 17 (38) ◽  
pp. 25629-25641 ◽  
Author(s):  
Xiaoqing Wang ◽  
Gerhard Ritschel ◽  
Sebastian Wüster ◽  
Alexander Eisfeld
Keyword(s):  
Molecular Dynamics ◽  
Quantum System ◽  
Open Quantum System ◽  
Light Harvesting ◽  
Parameter Extraction ◽  
Extraction Methods ◽  
Light Harvesting Complexes ◽  
System Parameters ◽  
Open Quantum ◽  
The Difference

We elucidate the difference between various parameter extraction methods and demonstrate sensitivity to molecular dynamics equilibration.

Analysis of Electrocardiogram Data Compression Techniques

2020 ◽  
pp. 930-970
Author(s):  
Anukul Pandey ◽  
Barjinder Singh Saini ◽  
Butta Singh ◽  
Neetu Sood
Keyword(s):  
Performance Evaluation ◽  
Performance Measures ◽  
Parameter Extraction ◽  
Extraction Methods ◽  
Walsh Transform ◽  
Ecg Compression ◽  
And Performance ◽  
Electrocardiogram Ecg ◽  
Ecg Database ◽  
Ecg Data

In this Chapter, a MATLAB-based approach is presented for compression of Electrocardiogram (ECG) data. The methodology employs in three different domains namely direct, transformed and parameter extraction methods. The selected techniques from direct ECG compression methods are TP, AZTEC, Fan, and Cortes. Moreover selected techniques from transformed ECG compression methods are Walsh Transform, DCT, and Wavelet transform. For each of the technique, the basic implementation of the algorithm was explored, and performance measures were calculated. All 48 records of MIT-BIH arrhythmia ECG database were employed for performance evaluation of various implemented techniques. Moreover, based on requirements, any basic techniques can be selected for further innovative processing that may include the lossless encoding.

Parameter Extraction Methods of Thin Film Photovoltaic Panel using Five Enhanced Models

2017 ◽  
Author(s):  
Ilham Nassar-Eddine ◽  
Karima Et-Torabi ◽  
Redouane Rmaily ◽  
Abdel ilah Fake ◽  
Abdellatif Obbadi ◽  
...  
Keyword(s):  
Thin Film ◽  
Parameter Extraction ◽  
Extraction Methods ◽  
Photovoltaic Panel

Data mining analysis of the influences of electrocardiogram P-wave morphology parameters on atrial fibrillation

2021 ◽  
pp. 1-8
Author(s):  
Chen-Sen Ouyang ◽  
Yenming J. Chen ◽  
Jinn-Tsong Tsai ◽  
Yiu-Jen Chang ◽  
Tian-Hsiang Huang ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Heart Rate ◽  
Cardiac Disease ◽  
Parameter Extraction ◽  
Extraction Methods ◽  
P Wave ◽  
Increased Risk ◽  
Wave Morphology ◽  
Ecg Database ◽  
Morphology Parameters

Atrial fibrillation (AF) is a type of paroxysmal cardiac disease that presents no obvious symptoms during onset, and even the electrocardiograms (ECG) results of patients with AF appear normal under a premorbid status, rendering AF difficult to detect and diagnose. However, it can result in deterioration and increased risk of stroke if not detected and treated early. This study used the ECG database provided by the Physionet website (https://physionet.org), filtered data, and employed parameter-extraction methods to identify parameters that signify ECG features. A total of 31 parameters were obtained, consisting of P-wave morphology parameters and heart rate variability parameters, and the data were further examined by implementing a decision tree, of which the topmost node indicated a significant causal relationship. The experiment results verified that the P-wave morphology parameters significantly affected the ECG results of patients with AF.

Research on the Feature Parameter Extraction of Wheat Seeds’ Bad Point Based on Image Processing

2014 ◽  
Vol 644-650 ◽  
pp. 4140-4143
Author(s):  
Zhe Wen ◽  
Qian Dong ◽  
Jie Zhu ◽  
Ya Bin Fan
Keyword(s):  
Image Processing ◽  
Feature Extraction ◽  
Parameter Extraction ◽  
Extraction Methods ◽  
Automatic Extraction ◽  
Wheat Seed ◽  
Manual Operation ◽  
Feature Parameter ◽  
Wheat Seeds

It is very important that study the feature parameter extraction of bad point of wheat seeds based on image processing for judging the quality of wheat. Using image processing extract and analyze the collected images information, and based on the collected information analyze the bad point information of wheat seed, then extract the feature parameters. Traditional bad point’s feature extraction methods are completed by the manual operation, and the efficient is lower. Currently, by means of image processing technology can extract the bad point’s feature of wheat seed automatically. To this end, the research status of seed feature extraction based on image processing are reviewed and prospected. Experiments show that the method can better complete the bad point’s feature automatic extraction and recognition of wheat seeds.

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