Improving SNR for DSM Linear Systems Using Probabilistic Error Correction and State Restoration: A Comparative Study

2006 ◽  
Author(s):  
M. Ashouei ◽  
S. Bhattacharya ◽  
A. Chatterjee
Keyword(s):  
Comparative Study ◽  
Error Correction ◽  
Linear Systems ◽  
Probabilistic Error

scholarly journals Comparative Study of Heart Rate, Blood Pressure and Selective Attention of Subjects Before and After Music

2019 ◽  
Vol 4 (1) ◽  
pp. 625-628
Author(s):  
Nisha Ghimire ◽  
Renu Yadav ◽  
Soumitra Mukhopadhyay
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Reaction Time ◽  
Comparative Study ◽  
Error Correction ◽  
Vital Signs ◽  
Stroop Test ◽  
Before And After ◽  
Paired T Test ◽  
After Error

Introduction: Studies have shown different views regarding the effect of music in vitals e.g Heart rate (HR), Blood pressure (BP) and atiention. The effect of preferred music with lyrics in vitals and reaction time in stroop test has not been performed in Nepalese students so, we conducted the study. Objective: To find out the change in HR, BP and reaction time in Stroop test before and after their preferred music with lyrics. Methodology Thirty male medical and paramedical students aged 25.27 ± 2.0 participated in study. The vital signs and reaction time in Stroop test before and after music was taken. Results Paired-t test was used to compare means before and after exposure to music. The means are expressed as Mean ± SD. Heart rate (HR) increased after exposure to music (66.33±9.51 Vs 67.2±8.44) (p<.05). The error in Stroop test was less after music (.66±.49 Vs.63±.66) (p<.05). The reaction time after error correction decreased post exposure to music (24.117±4.61Vs23.29±4.45) (p<.05). Conclusion The heart rate increased after exposure to music. The errors decreased after listening to music which also decreased reaction time.

On an internal multimodel control for non-linear systems: a comparative study

2008 ◽  
Vol 5 (4) ◽  
pp. 320 ◽  
Author(s):  
Dhaou Soudani ◽  
Mongi Naceur ◽  
Kamel Ben Saad ◽  
Mohamed Benrejeb
Keyword(s):  
Comparative Study ◽  
Linear Systems ◽  
Non Linear ◽  
Non Linear Systems

scholarly journals A Comparative Study of Stochastic Model Predictive Controllers

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2078
Author(s):  
Edwin González ◽  
Javier Sanchis ◽  
Sergio García-Nieto ◽  
José Salcedo
Keyword(s):  
Model Predictive Control ◽  
Stochastic Model ◽  
Comparative Study ◽  
Linear Systems ◽  
Predictive Control ◽  
Probabilistic Constraints ◽  
Numerical Examples ◽  
Model Predictive Controllers ◽  
Predictive Controllers ◽  
Stochastic Model Predictive Control

A comparative study of two state-of-the-art stochastic model predictive controllers for linear systems with parametric and additive uncertainties is presented. On the one hand, Stochastic Model Predictive Control (SMPC) is based on analytical methods and solves an optimal control problem (OCP) similar to a classic Model Predictive Control (MPC) with constraints. SMPC defines probabilistic constraints on the states, which are transformed into equivalent deterministic ones. On the other hand, Scenario-based Model Predictive Control (SCMPC) solves an OCP for a specified number of random realizations of uncertainties, also called scenarios. In this paper, Classic MPC, SMPC and SCMPC are compared through two numerical examples. Thanks to several Monte-Carlo simulations, performances of classic MPC, SMPC and SCMPC are compared using several criteria, such as number of successful runs, number of times the constraints are violated, integral absolute error and computational cost. Moreover, a Stochastic Model Predictive Control Toolbox was developed by the authors, available on MATLAB Central, in which it is possible to simulate a SMPC or a SCMPC to control multivariable linear systems with additive disturbances. This software was used to carry out part of the simulations of the numerical examples in this article and it can be used for results reproduction.

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