Dynamics analysis and numerical simulations of a stochastic non-autonomous predator–prey system with impulsive effects

Specific emitter identification (SEI) is a promising technology to discriminate the individual emitter and enhance the security of various wireless communication systems. SEI is generally based on radio frequency fingerprinting (RFF) originated from the imperfection of emitter’s hardware, which is difficult to forge. SEI is generally modeled as a classification task and deep learning (DL), which exhibits powerful classification capability, has been introduced into SEI for better identification performance. In the recent years, a novel DL model, named as complex-valued neural network (CVNN), has been applied into SEI methods for directly processing complex baseband signal and improving identification performance, but it also brings high model complexity and large model size, which is not conducive to the deployment of SEI, especially in Internet-of-things (IoT) scenarios. Thus, we propose an efficient SEI method based on CVNN and network compression, and the former is for performance improvement, while the latter is to reduce model complexity and size with ensuring satisfactory identification performance. Simulation results demonstrated that our proposed CVNN-based SEI method is superior to the existing DL-based methods in both identification performance and convergence speed, and the identification accuracy of CVNN can reach up to nearly 100% at high signal-to-noise ratios (SNRs). In addition, SlimCVNN just has 10% $\sim 30$ % model sizes of the basic CVNN, and its computing complexity has different degrees of decline at different SNRs; there is almost no performance gap between SlimCVNN and CVNN. These results demonstrated the feasibility and potential of CVNN and model compression.

An Efficient Specific Emitter Identification Method Based on Complex-Valued Neural Networks and Network Compression

On the euler's constant

Large-scale real-world radio signal recognition with deep learning

This paper is concerned with the Klein-Gordon equation coupled with the Maxwell equation in the rotationally symmetric bounded domains when a non-homogeneous term breaks the symmetry of the associated functional. Under some suitable assumption on nonlinear perturbation, we obtain infinitely many radially symmetric solutions to the non-homogeneous Klein-Gordon-Maxwell system.

/pdf/a-multiplicity-result-for-the-non-homogeneous-klein-gordon-4xuo31b78i.pdf

A multiplicity result for the non-homogeneous Klein-Gordon-Maxwell system in rotationally symmetric bounded domains

Global Well-Posedness of Solutions to a Class of Double Phase Parabolic Equation With Variable Exponents

This paper focuses on the reach control problem for systems expressed as a class of convex differential inclusions. The purpose is to find affine feedback for the trajectories of the systems to reach and leave an unrestricted facet of a given simplex in a finite time. It is proved that the condition for strong reachability is sufficient and necessary. The sufficient condition for weak reachability is obtained based on the solvability of the reach control problem for linear affine systems. At last, algorithms are designed and numerical examples are given to verify the validity of the results. 

Bin Ge

Papers

A multiplicity result for the non-homogeneous Klein-Gordon-Maxwell system in rotationally symmetric bounded domains

Global Well-Posedness of Solutions to a Class of Double Phase Parabolic Equation With Variable Exponents

Reach control problem for a class of convex differential inclusions on simplices

Multiple Nontrivial Solutions for Superlinear Double Phase Problems Via Morse Theory

The Nehari manifold for double‐phase problems with convex and concave nonlinearities