No abstract

An adaptive approach to select analysis window parameters for linear frequency modulated (LFM) signals is proposed to obtain the optimal 3 dB signal-to-noise ratio (SNR) in the shorttime Fourier transform (STFT) domain. After analyzing the instantaneous frequency and instantaneous bandwidth to deduce the relation between the window length and deviation of the Gaussian window, high-order statistics is used to select the appropriate window length for STFT and get the optimal SNR with the right time-frequency resolution according to the signal characteristic under a fixed sampling rate. Computer simulations have verified the effectiveness of the new method.

Featured with high accuracy, an integrated multi-omics model of PET/MRI-based radiomics could be the first non-invasive investigation for disease risk stratification and guidance of treatment in patients with primary ccRCC.

In this paper, an event-triggered adaptive control scheme is proposed for the gun control system of a tank subject to not only external disturbances but also uncertain modeling errors and unknown parameters. Compared with the existing results, the upper bound function of modeling errors is unknown. Therefore, the traditional event-triggered control method cannot be applied directly to handle the effect caused by the modeling errors. To solve this problem, a smooth function sg(•) is introduced to estimate the bound of modeling errors, such that their effects on system stability are successfully compensated. The simulation results are provided to illustrate the effectiveness of the proposed control scheme. INDEX TERMS Gun control system, adaptive control, event-trigger control, modeling error.

No abstract