Traditional recognition methods for face local features have a low recognition rate, so the recognition method for face local features based on the fuzzy algorithm and intelligent data analysis was ...designed. Firstly, the wavelet denoising method was used to reduce the noise of face images, and adaptive template matching was performed on the obtained images. Then, the face information was encoded, and the face features were identified to locate the face features. On this basis, the principal components of the face were analyzed to obtain the global features of the face. Finally, through the candidate set of facial local feature recognition, the extraction of face local features, and the fusion of face local features, the recognition of local face features were realized. The experimental results show that the average recognition rate of this method is 88.84% in a noise environment and 97.3% in noise-free environment. It can accurately recognize the face local features, can meet the needs of recognition of the face local features, and has certain practical application significance.
This technical note focuses on analyzing a new model transformation of uncertain linear discrete-time systems with time-varying delay and applying it to robust stability analysis. The uncertainty is ...assumed to be norm-bounded and the delay intervally time-varying. A new comparison model is proposed by employing a new approximation for delayed state, and then lifting method and simple Lyapunov-Krasovskii functional method are used to analyze the scaled small gain of this comparison model. This new approximation results in a much smaller error than the existing ones. Based on the scaled small gain theorem, new stability criteria are proposed in terms of linear matrix inequalities. Moreover, it is shown that the obtained conditions can be established through direct Lyapunov method. Two numerical examples are presented to illustrate the effectiveness and superiority of our results over the existing ones.
Vehicular computation offloading is a well-received strategy to execute delay-sensitive and/or compute-intensive tasks of legacy vehicles. The response time of vehicular computation offloading can be ...shortened by using mobile edge computing that offers strong computing power, driving these computation tasks closer to end users. However, the quality of communication is hard to guarantee due to the obstruction of dense buildings or lack of infrastructure in some zones. Unmanned Aerial Vehicles (UAVs), therefore, have become one of the means to establish communication links for the two ends owing to its characteristics of ignoring terrain and flexible deployment. To make a sensible decision of computation offloading, nevertheless vehicles need to gather offloading-related global information, in which Software-Defined Networking (SDN) has shown its advances in data collection and centralized management. In this paper, thus, we propose an SDN-enabled UAV-assisted vehicular computation offloading optimization framework to minimize the system cost of vehicle computing tasks. In our framework, the UAV and the Mobile Edge Computing (MEC) server can work on behalf of the vehicle users to execute the delay-sensitive and compute-intensive tasks. The UAV, in a meanwhile, can also be deployed as a relay node to assist in forwarding computation tasks to the MEC server. We formulate the offloading decision-making problem as a multi-players computation offloading sequential game, and design the UAV-assisted Vehicular computation Cost Optimization (UVCO) algorithm to solve this problem. Simulation results demonstrate that our proposed algorithm can make the offloading decision to minimize the Average System Cost (ASC).
This paper investigates the problem of robust finite frequency (FF) H∞ filtering for two-dimensional (2-D) Roesser models with polytopic uncertainties. Our attention is focused on designing filters ...guaranteeing the robustly asymptotic stability and FF H∞ disturbance attenuation level of the filtering error system. By the parameter-dependent idea and the generalized Kalman–Yakubovich–Popov lemma for 2-D Roesser models, the existence conditions of robust FF H∞ filters are obtained in terms of solving an optimization problem, which is more general than the existing results. An example is given to validate the proposed methods. The contribution of the paper is twofold: (1) systematic methods are proposed for designing FF H∞ filters for Roesser models; (2) an improved strategy has been presented to deal with the robust H∞ filter design for Roesser models.
Restricted frequency-domain specifications (RFDSs) are often encountered in control system design. In this technical note, we investigate the problem of static output-feedback (SOF) controller ...synthesis subject to a class of RFDSs. Motivated by the generalized Kalman-Yakubovich-Popov lemma and the two-stage strategy for SOF stabilization, a necessary and sufficient condition for the existence of an SOF controller satisfying an RFDS is first derived, and is then used to construct a heuristic approach to computing the SOF gain. The heuristic approach includes two stages: first designing an initial full-information (FI) controller and then computing an SOF gain. Moreover, a heuristic method is proposed to optimize the initial FI controller. Numerical examples are presented to demonstrate the effectiveness of the proposed design method. The main contribution of the technical note is extending the two-stage idea to SOF controller synthesis subject to RFDSs. In addition, the underlying relationship between some typical two-stage approaches to SOF stabilization is revealed.
A simple, practical, and highly efficient synthesis of pyrazoles and indazoles via copper-catalyzed direct aerobic oxidative C(sp2)–H amination has been reported herein. This process tolerated a ...variety of functional groups under mild conditions. Further diversification of pyrazoles was also investigated, which provided its potential for drug discovery.
With the advancement in the development of the Internet of Things (IoT) technology, as well as the industrial IoT, various applications and services are benefiting from this emerging technology such ...as smart healthcare systems, virtual realities applications, connected and autonomous vehicles, to name a few. However, IoT devices are known for being limited computation capacities which is crucial to the device’s availability time. Traditional approaches used to offload the applications to the cloud to ease the burden on the end user’s devices, however, greater latency and network traffic issues still persist. Mobile Edge Computing (MEC) technology has emerged to address these issues and enhance the survivability of cloud infrastructure. While a lot of attempts have been made to manage an efficient process of applications offload, many of which either focus on the allocation of computational or communication protocols without considering a cooperative solution. In addition, a single-user scenario was considered. Therefore, we study multi-user IoT applications offloading for a MEC system, which cooperatively considers to allocate both the resources of computation and communication. The proposed system focuses on minimizing the weighted overhead of local IoT devices, and minimize the offload measured by the delay and energy consumption. The mathematical formulation is a typical mixed integer nonlinear programming (MINP), and this is an NP-hard problem. We obtain the solution to the objective function by splitting the objective problem into three sub-problems. Extensive set of evaluations have been performed so as to get the evaluation of the proposed model. The collected results indicate that offloading decisions, energy consumption, latency, and the impact of the number of IoT devices have shown superior improvement over traditional models.
This paper is concerned with the problem of robust finite frequency (FF) H∞ filtering for uncertain two-dimensional (2-D) discrete-time systems in the Fornasini–Marchesini local state-space (FM LSS) ...model with polytopic uncertain parameters. The goal of the paper is to design filters such that the FF H∞ norm of the filtering error system has a specified upper bound for all uncertainties. In light of a recently developed generalized bounded real lemma, a linear matrix inequality-based approach is proposed for robust FF H∞ filter analysis and design. It is demonstrated that the presented approach to robust FF H∞ filter design covers the latest standard H∞ filtering result. Moreover, it is shown that the existing results specialized for the Roesser model, when applied to the FM LSS model through a model transformation, are much more restrictive than the proposed results in the paper, further justifying this work.
A novel and versatile method for the synthesis of 2H-imidazoles via iron-catalyzed 3 + 2 annulation from readily available oxime acetates with vinyl azides has been developed. This denitrogenative ...process involved N–O/N–N bond cleavages and two C–N bond formations to furnish 2,4-substituted 2H-imidazoles. This protocol was performed under mild reaction conditions and needed no additives or ligands. Furthermore, this is a green reaction involving oxime acetate as internal oxidant, acetic acid, and nitrogen as byproducts.
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