Recently, deep learning has been a hot research topic in the field of image super-resolution due to the excellent performance of deep convolutional neural networks. Many large-scale models with very deep structures have been proposed. However, in practical applications, the hardware of ordinary personal computers or smart terminals are obviously not suitable for large-scale deep neural network models. A light-weight Network with Automatic Residual Scaling (ARSN) for single image super-resolution was proposed, which has fewer layers and parameters compared with many other deep learning based methods. In addition, the specified residual blocks and skip connections in this network were utilized for residual scaling, global and local residual learning. The results on test datasets show that this model achieves state-of-the-art performance on both reconstruction quality and running speed. The proposed network achieves good results in terms of performance, speed and hardware consumption， and has high practical value.

Since the heterogeneous multi-agent systems composed of first-order and second-order agents have input and velocity saturation characteristics, the systems cannot achieve consensus. A leaderless distributed controller and a leader-following distributed controller of the heterogeneous multi-agent systems were constructed, and the sufficient conditions ensuring the successful consensus were given. The range of communication gain was calculated by using Lyapunov stability theory and Lasalle invariant set principle. The result of numerical simulation of leaderless heterogeneous multi-agent systems with input and velocity saturation characteristics shows that when the communication gain is not in a proper range, consensus of the leaderless heterogeneous multi-agent systems can not be achieved. However, when the proposed gain selection method is used to select the communication gain, the heterogeneous multi-agent systems can overcome input and velocity saturation characteristics, then consensus of the leaderless heterogeneous multi-agent systems can be achieved. The result of numerical simulation of leader following heterogeneous multi-agent systems with input and velocity saturation characteristics proves that the calculation method of the communication gain is also applicable to the semi-global leader-following consensus control of the heterogeneous multi-agent systems.

Concerning the stationary group consensus problem for the heterogeneous multi-Agent systems, which are composed of first-order Agents and second-order Agents, two stationary group consensus protocols were proposed under fixed interconnection topology and switching interconnection topologies respectively. By constructing Lyapunov-Krasovskii functions, the sufficient conditions, which are formulated as linear matrix inequalities, were obtained for the system converging to the group consensus asymptotically under the group consensus algorithm with identical time-varying communication delay. Finally, the simulation results show that the heterogeneous multi-Agent systems with time delay converg to the group consensus asymptotically under certain conditions.

Concerning the problem that it is difficult for the users in cloud computing to obtain the high-quality and personalized cloud services provided by a large number of cloud providers, a trust model based on user types and privacy protection for the personalized cloud services was proposed. Firstly, the users were divided into familiar users, strange users and normal users according to the transaction history. Secondly, a fair and reasonable trust evaluation Agent was introduced to protect users' privacy, which could evaluate the trust relationship between requesters and providers based on the user types. Lastly, in view of the dynamics of trust, a new updating mechanism combined with the transaction time and transaction amount was provided based on Quality of Service (QoS). The simulation results show that the proposed model has higher transaction success rate than AARep and PeerTrust. The transaction success rate can be increased by 10% and 16% in the harsh environment where the malicious user ratio reaches 70%. This method can improve transaction success rate, and has a strong ability to withstand harsh environments.

In order to improve the communication quality effectively, an approach of changing information transmission rate named VCTRM was proposed. The approach changed the modulation type and the chip transmission rate adaptively according to the current channel status when satellite communicated with ground station. The approach not only overcomes the defect that variable modulation type cannot meet the requirement of Bit Error Rate (BER) in system, but also solves the problem that the variable chip transmission rate can not improve the throughput in bad channel status. Simulation was given on three kinds of information transmission methods with Matlab: variable modulation method, variable chip transmission method and VCTRM method. The simulation results indicate that the proposed approach can not only meet the requirement of the system BER at any time but also get larger throughput than other approaches apparently.