Current Issue : January-March Volume : 2022 Issue Number : 1 Articles : 5 Articles
The intrinsic endpoint effect of empirical mode decomposition ThEMD) will lead to serious divergence of the intrinsic mode function ThIMF) at the endpoint, which will lead to the distortion of IMF and affect the decomposition accuracy of EMD. In view of this phenomenon, an EMD endpoint effect suppression method based on boundary local feature scale adaptive matching extension was proposed. This method can consider both the change trend of the signal at the endpoint and the change rule of the signal inside. The simulation results showed that the proposed method had better suppression effect on the intrinsic endpoint effect of EMD than the traditional EMD endpoint effect suppression method and achieved high-precision IMF. The endpoint effect suppression method of EMD based on boundary local feature scale adaptive matching extension was used to process the actual blasting seismic signal. The decomposition results showed that the method can effectively suppress the endpoint effect of EMD of blasting seismic signal and are helpful to extract the detailed characteristic parameters of blasting seismic signal....
In this paper, we introduce the concept of complex neutrosophic soft matrices. We define some basic operations including complement, union, and intersection on these matrices. We extend the concept of complex neutrosophic soft sets to complex neutrosophic soft matrices and prove related properties. Moreover, we develop an algorithm using complex neutrosophic soft matrices and apply it in signal processing.In this paper, we introduce the concept of complex neutrosophic soft matrices. We define some basic operations including complement, union, and intersection on these matrices. We extend the concept of complex neutrosophic soft sets to complex neutrosophic soft matrices and prove related properties. Moreover, we develop an algorithm using complex neutrosophic soft matrices and apply it in signal processing....
This paper reviews the state of the art of fiber Bragg gratings (FBGs) as analog all-optical signal processing units. Besides the intrinsic advantages of FBGs, such as relatively low cost, low losses, polarization insensitivity and full compatibility with fiber-optic systems, they have proven to deliver an exceptional flexibility to perform any complex band-limited spectral response by means of the variation of their physical parameters. These features have made FBGs an ideal platform for the development of all-optical broadband filters and pulse processors. In this review, we resume the main design algorithms of signal processors based on FBGs, and we revisit the most common processing units based on FBGs and the applications that have been presented in the literature....
According to the basic principle of piecewise linear classifier and its application in the field of infrared chemical remote sensing monitoring, the characteristics of unilateral piecewise linear classifier applied to the infrared spectrum identification of chemical agents are studied. With the characteristic of separate transmission, the characteristic recovery with the total observed deviation is used for the model.&erelaxation factors are used to replace the constrained conditions that cannot be optimized into constrained separate line segment calculation conditions. Experiments show that the result of signal recovery is better than traditional Wiener filtering and Richardson–Lucy methods....
Unmanned aerial vehicle (UAV) enabled mobile-edge computing (MEC) has been recognized as a promising approach for providing enhanced coverage and computation capability to Internet of Things (IoT), especially in the scenario with limited or without infrastructure. In this paper, we consider the UAV assisted partial computation offloading mode MEC system, where ground sensor users are served by a moving UAV equipped with computing server. Computation bits (CB) and computation efficiency (CE) are two vital metrics describe the computation performance of system. To reveal the CBCE tradeoff, an optimization problem is formulated to maximize the weighted sum of the above two metrics, by optimizing the UAV trajectory jointly with communication resource, as well as the computation resource. As the formulated problem is non-convex, it is difficult to be optimally solved in general. To tackle this issue, we decouple it into two sub-problems: UAV trajectory optimization and resource allocation optimization. We propose an iterative algorithm to solve the two sub-problems by Dinkelbach’s method, Lagrange duality and successive convex approximation technique. Extensive simulation results demonstrate that our proposed resource allocation optimization scheme can achieve better computational performance than the other schemes. Moreover, the proposed alternative algorithm can converge with a few iterations....
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