Dorsolateral prefrontal cortex (DLPFC) activity to "Go" trials, and dorsal anterior cingulate (dACC) activity to "No Go" trials were associated with faster error-free performance; consistent with DLPFC and dACC facilitating proactive and reactive control, respectively.
DLPFC activity to Go trials in EF (vs. Control) blocks was associated with faster error-free performance, r(17) = −0.51, P < 0.05, Figure 3 c, which in turn was negatively associated with trait anxiety, r(17) = 0.50, P < 0.05 (i.e., trait anxiety was linked to longer reactions times (RTs)—hence the positive correlation coefficient), Figure 3 d.
The implications of using a fast error estimator are twofold.
As a result, FTSMC ensure a fast error tracking capability.
To the best of our knowledge this is the fastest error free large signal modulation of any VCSEL at 85 °C.
Here we show that one can extend a theorem from graphics that generates a very fast error measure for an otherwise difficult leave-one-out error analysis.
The experimental results show that the state-compensated ILC scheme using BSN filtering can achieve fast error convergence and keep small steady-state tracking errors close to the system noise level.
Accordingly, these two tools are complementary where the use of ProB suits better in the early conception phases, especially for a fast error debug, and the use of Atelier B comes later to give the proof of properties correctness.
The six neural networks are namely, the logistic sigmoid multi-layered perceptron (LOGMLP), the hyperbolic tangent sigmoid multi-layered perceptron (TANMLP), the fast error back-propagation hyperbolic tangent multi-layered perceptron (error TANMLP), the radial basis function networks (RBFNs), the adaptive TANMLP, and the adaptive RBFN.
