deblurring. Inspired by the fact that a fractional order calculation can inhibit the noise and preserve the texture information of the image, a fractional order dark channel prior is proposed for image deblurring in this paper. It is appropriate for kernel estimation where input images and intermediate images are processed by using a fractional order dark channel prior. Furthermore, the non-convex problem is solved by the half-quadratic splitting method, and some metrics are used for deblurring image quality assessment. Finally, quantitative and qualitative experimental results show that the proposed method achieves state-of-the-art results on synthetic and real blurry images.

of automation in anaesthesia is to estimate the concentration of hypnotic drugs in different compartments of the body including primary, rapid peripheral (muscle), slow peripheral (bones, fat) and effect site (brain) compartment based on Pharmacokinetics (PK) and Pharmacodynamics (PD) model. This paper aimed to regulate the hypnosis level with estimating the Propofol concentrations using a linear observer in feedback control strategy based on Integral Super-Twisting Sliding Mode Controller (ISTSMC). The drug concentration in plasma of the silico patients accurately estimated in nominal transient. The results show that tracking errors between the actual output in form of BIS level and linearized output nearly approaches to zero in the maintenance phase of anesthesia to ensure the controller response on sliding phase with optimum performances by achieving desired hypnotic level 50 on BIS. The robustness of control strategy is further ensured by adding measurement noise of electromagnetic environment of operation theatre distracting signal quality index of the output BIS level.

for the output-feedback control with a supervisor enforcing a reset rule at each switching instant are considered respectively. Furthermore, some comparison between these two methods are also given.

and density obtained by conventional prestack AVO inversion, BI can be calcu lated indirectly using the Rickman formula. However, the conventional AVO inversion based on Zoeppritz approximation assumes that incident angle is small and elastic parameters change slowly, which afects the inversion accuracy of the three elastic parameters. Additionally, using these three elastic parameters to obtain BI indirectly also leads to cumulative errors of the inversion results. Therefore, we propose an inversion method based on BI_Zoeppritz equation to directly estimate VP, VS and BI. The BI_Zoeppritz equation is an exact Zoeppritz equation for BI, which is used as the forward operator for the proposed method. The multi-objective function of the inversion method is optimized by a fast nondominated sorting genetic algorithm (NSGA II). An initial model and an optimized search window are used to improve the inversion accuracy. The test results of model data and actual data reveal that this method can directly obtain the BI with high precision. In addition, the stability and noise immunity of the proposed method are verifed by the seismic data with random noise.

can be approximated using these bounds. In the first part of this work, an interval state estimator for such systems is designed to deal with these component faults and uncertainties. The result is then extended to find an interval state estimator for a noncooperative LTV discrete-time system subject to component faults and uncertainties by similarity transformation of coordinates. The proposed interval state estimator guaranteed bounds on the observed states that are consistent with the system states. The observer convergence is also ensured. The designed method is simple and easy to be implemented. Two numerical examples are given to show the effectiveness of the proposed method.