Nonlinear Rescaling of Control Laws with Application to Stabilization in the Presence of Magnitude Saturation

Motivated by some recent results on the stabilization of homogeneous systems, we present a gain-scheduling approach for the stabilization of non-linear systems. Given a one-parameter family of stabilizing feedbacks and associated Lyapunov functions, we show how the parameter can be rescaled as a function of the state to give a new stabilizing controller. In the case of homogeneous systems, we obtain generalizations of some existing results. We show that this approach can also be applied to nonhomogeneous systems. In particular, the main application considered in this paper is to the problem of stabilization with magnitude limitations. For this problem, we develop a design method for single-input controllable systems with eigenvalues in the left closed plane

Accurate photonic temporal mode analysis with reduced resources

The knowledge and thus characterization of the temporal modes of quantum light fields is important in many areas of quantum physics ranging from experimental setup diagnosis to fundamental-physics investigations. Recent results showed how the auto-correlation function computed from continuous-wave homodyne measurements can be a powerful way to access the temporal mode structure. Here, we push forward this method by providing a deeper understanding and by showing how to extract the amplitude and phase of the temporal mode function with reduced experimental resources. Moreover, a quantitative analysis allows us to identify a regime of parameters where the method provides a trustworthy reconstruction, which we illustrate experimentally

Preferred levels for background ducking to produce esthetically pleasing audio for TV with clear speech

In audio production, background ducking facilitates speech intelligibility while allowing the background to fulfill its purpose, e.g., to create ambience, set the mood, or convey semantic cues. Technical details for recommended ducking practices are not currently documented in the literature. Hence, we first analyzed common practices found in TV documentaries. Second, a listening test investigated the preferences of 22 normal-hearing participants on the Loud- ness Difference (LD) between commentary and background during ducking. Highly personal preferences were observed, highlighting the importance of object-based personalization. Sta- tistically significant difference was found between non-expert and expert listeners. On average, non-experts preferred LDs that were 4 LU higher than the ones preferred by experts. A sta- tistically significant difference was also found between Commentary over Music (CoM) and Commentary over Ambience (CoA). Based on the test results, we recommend at least 10 LU difference for CoM and at least 15 LU for CoA. Moreover, a computational method based on the Binaural Distortion-Weighted Glimpse Proportion (BiDWGP) was found to match the median preferred LD for each item with good accuracy (mean absolute error = 1.97 LU ± 2.50)