scholarly journals Real-time myoelectric control of a multi-fingered hand prosthesis using principal components analysis

2012 ◽  
Vol 9 (1) ◽  
pp. 40 ◽  
Author(s):  
Giulia C Matrone ◽  
Christian Cipriani ◽  
Maria Carrozza ◽  
Giovanni Magenes
Keyword(s):  
Principal Components Analysis ◽  
Real Time ◽  
Principal Components ◽  
Myoelectric Control ◽  
Hand Prosthesis ◽  
Components Analysis

scholarly journals Online Evaluation for the Accuracy of Electronic Voltage Transformer Based on Recursive Principal Components Analysis

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5576
Author(s):  
Zhenhua Li ◽  
Yangang Zheng ◽  
Ahmed Abu-Siada ◽  
Mengyao Lu ◽  
Hongbin Li ◽  
...  
Keyword(s):  
Principal Components Analysis ◽  
Real Time ◽  
Principal Components ◽  
Smart Grids ◽  
Voltage Transformer ◽  
Output Data ◽  
Reliable Technique ◽  
Term Operation ◽  
Calibration Methods ◽  
Components Analysis

The electronic voltage transformer (EVT) has received much attention with the recent global trend to establish smart grids and digital substations. One of the main issues of the EVT is the deterioration of its performance with long-term operation which affects the control and protection systems it is employed for and hence the overall reliability of the power grids. This calls for the essential need for a reliable technique to regularly assess the accuracy of operating EVT in real-time. Unfortunately, traditional calibration methods cannot detect the incipient EVT performance change in real-time. As such, this paper presents a new online method to evaluate the accuracy of the EVT. In this regard, the Q-statistic is calculated based on the recursive principal components analysis (RPCA) using the output data of EVT to map up the changes of metering error on the electric–physics relationship. By employing the output data of the EVT along with the power grid characteristics, the performance of the EVT is evaluated without the need for a standard transformer, as per the current industry practice. Results show that the proposed method can assess the EVT with a 0.2 accuracy class.

Diagnoses Generated by Numerical Taxonomic Methods Applied to Standard Blood Variables

1980 ◽  
Vol 19 (04) ◽  
pp. 205-209
Author(s):  
L. A. Abbott ◽  
J. B. Mitton
Keyword(s):  
Liver Cirrhosis ◽  
Renal Disease ◽  
Principal Components Analysis ◽  
Discriminant Function ◽  
Principal Components ◽  
Discriminant Function Analysis ◽  
Chronic Renal Disease ◽  
Function Analysis ◽  
Infectious Hepatitis ◽  
Components Analysis

Data taken from the blood of 262 patients diagnosed for malabsorption, elective cholecystectomy, acute cholecystitis, infectious hepatitis, liver cirrhosis, or chronic renal disease were analyzed with three numerical taxonomy (NT) methods : cluster analysis, principal components analysis, and discriminant function analysis. Principal components analysis revealed discrete clusters of patients suffering from chronic renal disease, liver cirrhosis, and infectious hepatitis, which could be displayed by NT clustering as well as by plotting, but other disease groups were poorly defined. Sharper resolution of the same disease groups was attained by discriminant function analysis.

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