In this paper, the problem of non-negative edge consensus of undirected networked linear time-invariant systems is addressed by associating each edge of the network with a state variable, for which a distributed algor...
详细信息
In this paper, the problem of non-negative edge consensus of undirected networked linear time-invariant systems is addressed by associating each edge of the network with a state variable, for which a distributed algorithm is constructed. Sufficient conditions referring only to the number of edges are derived for non-negative edge consensus of the networked systems. Subsequently, the linear programming method and a low-gain feedback technique are introduced to simplify the design of the feedback gain matrix for achieving the non-negative edge consensus. It is found that the low-gain feedback technique has a good effect on the non-negative edge consensus of the networked systems subject to input saturation. Numerical simulations are presented to verify the effectiveness of the theoretical results.
Non-orthogonal multiple access(NOMA)technique is an expert on channel differences *** this paper,a dual-hop NOMA-based cooperative relaying network where a best relay is selected as an active node to accomplish the co...
详细信息
Non-orthogonal multiple access(NOMA)technique is an expert on channel differences *** this paper,a dual-hop NOMA-based cooperative relaying network where a best relay is selected as an active node to accomplish the communication between a source and a destination is *** assume that both decode-and-forward(DF)and amplify-and-forward(AF)protocols are applied to the selected *** metrics that ergodic sum-rate and outage probability are investigated,and the closed-form expressions of the latter for DF and AF protocols are *** and simulation results are conducted to verify the validity of the theoretical analysis,in which we can see that the NOMA based DF relaying is better than the NOMA based AF relaying and other existing NOMA-based cooperative communication schemes.
The tradeoff between efficiency and model size of the convolutional neural network(CNN)is an essential issue for applications of CNN-based algorithms to diverse real-world *** deep learning-based methods have achieved...
详细信息
The tradeoff between efficiency and model size of the convolutional neural network(CNN)is an essential issue for applications of CNN-based algorithms to diverse real-world *** deep learning-based methods have achieved significant improvements in image super-resolution(SR),current CNNbased techniques mainly contain massive parameters and a high computational complexity,limiting their practical *** this paper,we present a fast and lightweight framework,named weighted multi-scale residual network(WMRN),for a better tradeoff between SR performance and computational *** the modified residual structure,depthwise separable convolutions(DS Convs)are employed to improve convolutional operations’***,several weighted multi-scale residual blocks(WMRBs)are stacked to enhance the multi-scale representation *** the reconstruction subnetwork,a group of Conv layers are introduced to filter feature maps to reconstruct the final high-quality *** experiments were conducted to evaluate the proposed model,and the comparative results with several state-of-the-art algorithms demonstrate the effectiveness of WMRN.
This paper proposes a fast and robust algorithm for classification and recognition of ships based on the Principal Component Analysis (PCA) method. The three-dimensional ship models are achieved by modeling software o...
详细信息
This paper proposes a fast and robust algorithm for classification and recognition of ships based on the Principal Component Analysis (PCA) method. The three-dimensional ship models are achieved by modeling software of MultiGen, and then they are projected by Vega simulating software for two-dimensional ship silhouettes. The PCA method as against the Back-Propagation (BP) neural network method for simulated ship recognition using training and testing experiments, we can see that there is a sharp contrast between them. Some recognition results from simulated data are presented, the correct recognition rate of PCA method improved rapidly for each of the five ship types than that of neural network method, the number of times a ship type is recognized as one of the other ships is reduced greatly.
Parameters selection of support vector machine is the key issue that impacts its accurate performance. A method for support vector regression machine with standard particle swarm optimization (SPSO) algorithm is propo...
详细信息
In this paper, a rectangular microwave filter with rectangular groove is designed. The filter adopts symmetrical three-stage structure. The first section is the slot line waveguide section to realize the input / outpu...
详细信息
This paper introduces a broadband microwave bandpass filter. The structure of the filter is a filter cavity formed by two balanced dielectric sheets. On the two dielectric sheets, the relative face of the microwave in...
详细信息
C-mode imaging is one of the ultrasound imaging modalities. Compared with other modalities, e.g. A-mode, B-mode, M-mode, and Doppler, C-mode is mainly developed and used in industry testing. The potential of C-mode im...
详细信息
This paper explores the application of the Bowyer-Watson algorithm for constructing Delaunay triangulations on Riemannian manifolds, with a particular focus on karst terrain and channel detection scenarios. We define ...
详细信息
This paper introduces a microwave filter with pentagram grooves, which belongs to an artificial surface plasmon (SSPPs) type microwave bandpass *** filter adopts a two-stage structure. The first section is a slot-line...
详细信息
暂无评论