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In this paper, we consider the robust $ H_{\infty} $ state estimation (SE) problem for a class of discrete time-varying uncertain neural networks (DTVUNNs) with uniform quantization and time-delay under variance constraints. In order to reflect the actual situation for the dynamic system, the constant time-delay is considered. In addition, the measurement output is first quantized by a uniform quantizer and then transmitted through a communication channel. The main purpose is to design a time-varying finite-horizon state estimator such that, for both the uniform quantization and time-delay, some sufficient criteria are obtained for the estimation error (EE) system to satisfy the error variance boundedness and the $ H_{\infty} $ performance constraint. With the help of stochastic analysis technique, a new $ H_{\infty} $ SE algorithm without resorting the augmentation method is proposed for DTVUNNs with uniform quantization. Finally, a simulation example is given to illustrate the feasibility and validity of the proposed variance-constrained robust $ H_{\infty} $ SE method.

This paper deals with the asymptotic behavior of solution to the linearized ellipsoidal BGK model in torus. We prove that the solution converges exponentially to the equilibrium in the weighted Sobolev spaces with polynomial weight. Our exponential decay rate $$e^{-\lambda t}$$ is optimal in the sense that $$\lambda >0$$ equals to the spectral gap of the linearized operator in the standard Hilbert space. Our strategy is taking advantage of the quantitative spectral gap estimates in a smaller reference Hilbert space, the factorization method, and the enlargement of the functional space for the associated semigroup.

In this paper, we deal with two fractional boundary value problems which have linear growth and quadratic growth about the fractional derivative in the nonlinearity term. By using variational methods coupled with the iterative methods, we obtain the existence results of solutions. To the best of the authors’ knowledge, there are no results on the solutions to the fractional boundary problem which have quadratic growth about the fractional derivative in the nonlinearity term.

In this paper, we recognize the finite propagation speed of the solution for the relativistic Bhatnagar-Gross-Krook model of the Marle-type near equilibrium regime in the whole space [Formula: see text]. The global solutions vanish outside a modified line cone ⟨ x⟩ = aMt with a, M > 1. Moreover, one can see that the slope of the modified line cone aM can be as close as to the maximum speed of the relativistic transport part. This means that the propagation speed is optimal.

In this paper, we consider the asymptotic behavior of solutions to the linear spatially homogeneous Boltzmann equation for hard potentials without angular cutoff. We obtain an optimal rate of exponential convergence towards equilibrium in a L1-space with a polynomial weight. Our strategy is taking advantage of a spectral gap estimate in the Hilbert space L 2 ( μ − 1 2 ) and a quantitative spectral mapping theorem developed by Gualdani et al. (2017).

This work deals with the Cauchy problem and the asymptotic behavior of the solution of the fermion equation in the Sobolev spaces with a polynomial weight in the torus. We first investigate the linearized equation and obtain the optimal exponential decay rate for the associated semigroup. Our strategy is taking advantage of quantitative spectral gap estimates in smaller reference Hilbert space, the factorization method and the enlargement of the functional space. We then turn to the nonlinear equation and prove the global existence and uniqueness of solutions in a close-to-equilibrium regime. Moreover, we prove an exponential stability for such a solution with the optimal decay rate given by the semigroup decay of the linearized equation.