scholarly journals Specification of New Test Waveforms for Static Electricity Meters

2021 ◽  
Author(s):  
Deborah Ritzmann ◽  
Paul Wright
Keyword(s):  
Feature Extraction ◽  
Feature Selection ◽  
Signal Analysis ◽  
Static Electricity ◽  
Signal Representation ◽  
Suitable Test

Recent observations of significant errors in static electricity meter readings have created a need for specification of new standard immunity test waveforms. This paper provides an overview of ongoing signal analysis work towards parsimonious specification of suitable test waveforms including candidate methods for signal representation, feature extraction and feature selection.

scholarly journals Specification of New Test Waveforms for Static Electricity Meters

2021 ◽  
Author(s):  
Deborah Ritzmann ◽  
Paul Wright
Keyword(s):  
Feature Extraction ◽  
Feature Selection ◽  
Signal Analysis ◽  
Static Electricity ◽  
Signal Representation ◽  
Suitable Test

Recent observations of significant errors in static electricity meter readings have created a need for specification of new standard immunity test waveforms. This paper provides an overview of ongoing signal analysis work towards parsimonious specification of suitable test waveforms including candidate methods for signal representation, feature extraction and feature selection.

A novel feature extraction-based ECG signal analysis

2021 ◽  
Author(s):  
Varun Gupta ◽  
Monika Mittal ◽  
Vikas Mittal ◽  
Arvind Kumar Sharma ◽  
Nitin Kumar Saxena
Keyword(s):  
Feature Extraction ◽  
Signal Analysis ◽  
Ecg Signal

Design of Text Categorization System Based on SVM

2012 ◽  
Vol 532-533 ◽  
pp. 1191-1195 ◽  
Author(s):  
Zhen Yan Liu ◽  
Wei Ping Wang ◽  
Yong Wang
Keyword(s):  
Feature Extraction ◽  
Feature Selection ◽  
Text Categorization ◽  
Feature Selection Method ◽  
Extraction Methods ◽  
Support Vector ◽  
Text Representation ◽  
Text Feature ◽  
Categorization System ◽  
Classifier Training

This paper introduces the design of a text categorization system based on Support Vector Machine (SVM). It analyzes the high dimensional characteristic of text data, the reason why SVM is suitable for text categorization. According to system data flow this system is constructed. This system consists of three subsystems which are text representation, classifier training and text classification. The core of this system is the classifier training, but text representation directly influences the currency of classifier and the performance of the system. Text feature vector space can be built by different kinds of feature selection and feature extraction methods. No research can indicate which one is the best method, so many feature selection and feature extraction methods are all developed in this system. For a specific classification task every feature selection method and every feature extraction method will be tested, and then a set of the best methods will be adopted.

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