Variational Bayesian labeled multi-Bernoulli filter with unknown sensor noise statistics

It is difficult to build accurate model for measurement noise covariance in complex back-grounds. For the scenarios of unknown sensor noise variances, an adaptive multi-target tracking algorithm based on labeled random finite set and variational Bayesian (VB) approximation is pro-posed. The variational approximation technique is introduced to the labeled multi-Bernoulli (LMB) filter to jointly estimate the states of targets and sensor noise variances. Simulation results show that the proposed method can give unbiased estimation of cardinality and has better performance than the VB probability hypothesis density (VB-PHD) filter and the VB cardinality balanced multi-target multi-Bernoulli (VB-CBMeMBer) filter in harsh situations. The simulations also confirm the robustness of the proposed method against the time-varying noise variances. The computational complexity of proposed method is higher than the VB-PHD and VB-CBMeMBer in extreme cases, while the mean execution times of the three methods are close when targets are well separated.     

Numerical study of the generation of linear energy transfer spectra for space radiation applications

In analyzing charged particle spectra in space due to galactic cosmic rays (GCR) and solar particle events (SPE), the conversion of particle energy spectra into linear energy transfer (LET) distributions is a convenient guide in assessing biologically significant components of these spectra. The mapping of LET to energy is triple valued and can be defined only on open energy subintervals where the derivative of LET with respect to energy is not zero. Presented here is a well-defined numerical procedure which allows for the generation of LET spectra on the open energy subintervals where, in spite of their singular nature, the spectra are integrable. The efficiency of the numerical procedures is demonstrated by providing examples of computed differential and integral LET spectra and their equilibrium components for historically large SPEs and 1977 solar minimum GCR environments. Due to the biological significance of tissue, all simulations are done with tissue as the target material.     

FDDI令牌环与SAE线性令牌总线的比较研究

分布式分牌传递网络将进入高速实时的航空电子通信系统。本文针对两种典型的令牌传递网络，即美国自动化工程学会（SAE）的线性令牌传递总线（LTPB）与美国国家标准协会（ANSI）的分布式光纤数据接口（FDDI）令牌环进行了各个方面的比较研究，最后给出了比较分析结论。     

A novel approximation of basic probability assignment based on rank-level fusion

Belief functions theory is an important tool in the field of information fusion. However, when the cardinality of the frame of discernment becomes large, the high computational cost of evidence combination will become the bottleneck of belief functions theory in real applications. The basic probability assignment (BPA) approximations, which can reduce the complexity of the BPAs, are always used to reduce the computational cost of evidence combination. In this paper, both the cardinalities and the mass assignment values of focal elements are used as the criteria of reduction. The two criteria are jointly used by using rank-level fusion. Some experiments and related analyses are provided to illustrate and justify the proposed new BPA approximation approach.     

A study on the quintic nonlinear beam vibrations using asymptotic approximate approaches

This paper intends to promote the application of modern analytical approaches to the governing equation of transversely vibrating quintic nonlinear beams. Four new studied methods are Stiffness analytical approximation method, Homotopy Perturbation Method with an Auxiliary Term, Max–Min Approach (MMA) and Iteration Perturbation Method (IPM). The powerful analytical approaches are used to obtain the nonlinear frequency–amplitude relationship for dynamic behavior of vibrating beams with quintic nonlinearity. It is demonstrated that the first terms in series expansions of all methods are sufficient to obtain a highly accurate solution. Finally, a numerical example is conducted to verify the integrity of the asymptotic methods.     

BEST APPROXIMATION BY NORMAL MATRICES WITH SPECTRAL CONSTRAINTS

考虑在给定谱约束和Ｆｒｏｂｅｎｉｕｓ范数意义下用正规矩阵最佳逼近一个给定复方阵的问题。给出了这个问题可解的充分必要条件,提出了求解这个问题的一个数值算法,并给出了一个数值例子。     

航空发动机LQR控制的模糊神经网络方法

针对线性二次型调节器LQR在航空发动机多变量控制中存在的存储量需求太大的问题,提出了相应的自适应神经网络模糊控制方法。根据某型发动机飞行包线内给定工作点的线性化模型,分别设计控制器,并将分别设计的控制器用自适应神经网络模糊推理的方法进行综合,使之成为一个非线性的控制器,由此可以得出其它工作点的LQR设计结果。该方法能够在一定程度上弥补LQR控制的缺陷,仿真实例表明了其有效性。      

求解退化线性代数方程组的小参数法

文章介绍了求解退化线性代数方程组的小参数法,推导出简便的求解公式,给出了小参数的选择方法,并且证明了方法的稳定性和高精度,最后给出了一些数值结果.     

距离及其变化率跟踪数据的数学处理

运用雷达或光学设备对航天飞行器进行跟踪测量可以获得距离及其变化率的观测数据。由于测量设备的精度、环境条件等多方面的原因,这些测量数据都是有误差的。除了测距及距离变化率的随机误差外,还有测距的系统误差。通过建立适当的数学模型,运用样条函数和回归分析方法给出一种估计距离、距离变化率及测距系统误差的方法,该方法很容易实现计算。理论分析和仿真计算表明,该方法具有很高的精度。