Combining the histogram method and the ultrafast segmented model identification of linearity errors algorithm for ADC linearity testing

2016 ◽  
Author(s):  
Weida Chen ◽  
Yongxin Zhu ◽  
Xinyi Liu ◽  
Xinyang Li ◽  
Dongyu Ou
Keyword(s):  
Model Identification ◽  
Histogram Method ◽  
Segmented Model ◽  
Linearity Testing

PI(D) tuning with contextual model identification

2009 ◽  
Author(s):  
Alberto Leva ◽  
Sara Negro ◽  
Alessandro Vittorio Papadopoulos
Keyword(s):  
Model Identification ◽  
Contextual Model

Model Fungsi Transfer Input Ganda untuk Pemodelan Jakarta Islamic Index

2019 ◽  
Vol 7 (3) ◽  
Author(s):  
Nur Laela Fitriani ◽  
Pika Silvianti ◽  
Rahma Anisa
Keyword(s):  
Exchange Rate ◽  
Transfer Function ◽  
Multivariate Time Series ◽  
Model Identification ◽  
Transfer Function Model ◽  
Function Model ◽  
Jones Index ◽  
Multiple Input ◽  
Identification Stage ◽  
Stage Estimation

Transfer function model with multiple input is a multivariate time series forecasting model that combines several characteristics of ARIMA models by utilizing some regression analysis properties. This model is used to determine the effect of output series towards input series so that the model can be used to analyze the factors that affect the Jakarta Islamic Index (JII). The USD exchange rate against rupiah and Dow Jones Index (DJI) were used as input series. The transfer function model was constructed through several stages: model identification stage, estimation of transfer function model, and model diagnostic test. Based on the transfer function model, the JII was influenced by JII at the period of one and two days before. JII was also affected by the USD exchange rate against rupiah at the same period and at one and two days before. In addition, the JII was influenced by DJI at the same period and also at period of one until five days ago. The Mean Absolute Prencentage Error (MAPE) value of forecasting result was 0.70% and the correlation between actual and forecast data was 0.77. This shows that the model was well performed for forecasting JII.

NARMAX Model Identification Using Multi-Objective Optimization Differential Evolution

2018 ◽  
Vol 10 (7) ◽  
Author(s):  
Mohd Zakimi Zakaria ◽  
◽  
Zakwan Mansor ◽  
Azuwir Mohd Nor ◽  
Mohd Sazli Saad ◽  
...  
Keyword(s):  
Differential Evolution ◽  
Model Identification ◽  
Multi Objective Optimization ◽  
Multi Objective

Joint High Speed Sealift (JHSS) Segmented Model Test Data Analysis and Validation of Numerical Simulations

2012 ◽  
Author(s):  
Dominic Piro ◽  
Kyle A. Brucker ◽  
Thomas T. O'Shea ◽  
Donald Wyatt ◽  
Douglas Dommermuth ◽  
...  
Keyword(s):  
Data Analysis ◽  
Numerical Simulations ◽  
Test Data ◽  
Model Test ◽  
High Speed ◽  
Segmented Model
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