The central nervous system (CNS) controls the limb movement by modulating multiple skeletal muscles with synergistic modules and neural oscillations with different frequencies between the activated muscles. Several researchers have found intermuscular coherence existing within the synergistic muscle pairs, and pointed out that the intermuscular synchronization existed when functional forces were generated. However, few studies involved the time-varying characteristics of the intermuscular coherence in each synergy module though all activated muscles keep in a dynamic and varying process. Therefore, this study aims to explore the time-varying coherence amongst synergistic muscles during movements based on the combination of the non-negative matrix factorization (NMF) method and the time-frequency coherence (TFC) method. We applied these methods into the electromyogram (EMG) signals recorded from eight muscles involved in the sequence of the wrist movements [wrist flexion (WF), wrist flexion transmission to wrist extension (MC) and wrist extension (WE)] in 12 healthy people. The results showed three synergistic flexor pairs (FCR-PL, FCR-FDS, and PL-FDS) in the WF stage and three extensor pairs (ECU-ECR, ECU-B, and ECR-B) in both MC and WE stages. Further analysis showed intermuscular coherence between each pairwise synergistic muscles. The intermuscular coherence between the flexor muscle pairs was mainly observed in the beta band (15–35 Hz) during the WF stage, and that amongst the extensor muscle pairs was also observed in the beta band during the WE stage. However, the intermuscular coherence between the extensor muscle pairs mainly on gamma band during the MC stage. Additionally, compared to the flexor muscle pairs, the intermuscular coherence of the extensor muscle pairs were lower in the WF stage, and higher in both MC and WE stages. These results demonstrated the time-varying mechanisms of the synergistic modulation and synchronous oscillation in motor-control system. This study contributes to expanded researches for motor control.
Analytical modelling of photovoltaic (PV) array is crucial for studying the current-voltage (I-V) characteristic of PV array and maximum power point tracking. A PV array model generally contains some undetermined parameters and the values of the parameters cannot be measured by sensors. It is difficult to correctly determine those model parameters. They should be estimated based on experimental data. Since the experimental data gathered from the solar panel equipment usually contain random and gross errors, a robust parameter estimation method, correntropy-based parameter estimation (C-PE) is proposed for PV array model considering partial shading condition here. First, the theoretical model of PV array considering partial shading condition is investigated. Second, compared with the most common estimator, weighted least squares (WLS), robustness of the proposed correntropy estimator is analysed by using influence function (IF), and then C-PE method is developed for the PV array model. The WLS-based parameter estimation (WLS-PE) and C-PE methods are used in the simulation example. The results show that the C-PE method is more robust than WLS-PE method. Finally, the experimental data of PV array under ideal condition and partial shading condition are also used to demonstrate the feasibility and effectiveness of C-PE method.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.