Optimal pricing and inventory policy with order cancelations under the cash-on-delivery payment scheme

Considering a periodic review system where the online seller allows the customers to pay when the products are delivered to them（referred as cash-on-delivery payment scheme in this paper）,the authors investigate the seller＇s joint pricing and inventory control policy with a finite planning horizon.In particular,the authors incorporate the customers＇ possible order cancellation behavior with the cash-on-delivery scheme.It can be proven that the base-stock list price policy is optimal under mild conditions.The authors also analyze the impact of the customers＇ forward looking behavior on the optimal policy.     

Azimuth resolution improvement for spaceborne SAR images with quasi-non-overlapped Doppler bandwidth

The azimuth resolution improvement problem is solved via a coherent combination of synthetic aperture radar （SAR） ima-ges with the quasi-non-overlapped Doppler bandwidth. Prior to the spectra combination, SAR images should be coregistered, while phase biases induced by topography, atmospheric propagation delays and baseline measurement errors should be calibrated. However, the coregistration accuracy suffers from large Doppler decorrelation caused by the quasi-non-overlapped Doppler band-width. Furthermore, the method used to estimate phase biases from interferogram of azimuth prefiltered SAR image pairs wil fail when there is no overlapped spectrum. The fringe simulation and maximum sharpness optimization are adopted to deal with the problems. Accordingly, a novel algorithm to coherently synthesize SAR images is presented. The experiment with the Terra SAR X-band （TerraSAR-X） satel ite data validates the performance of the presented method.     

Higher-order principal component pursuit via tensor approximation and convex optimization

Recovering the low-rank structure of data matrix from sparse errors arises in the principal component pursuit （PCP）. This paper exploits the higher-order generalization of matrix recovery, named higher-order principal component pursuit （HOPCP）, since it is critical in multi-way data analysis. Unlike the convexification （nuclear norm） for matrix rank function, the tensorial nuclear norm is stil an open problem. While existing preliminary works on the tensor completion field provide a viable way to indicate the low complexity estimate of tensor, therefore, the paper focuses on the low multi-linear rank tensor and adopt its convex relaxation to formulate the convex optimization model of HOPCP. The paper further propose two algorithms for HOPCP based on alternative minimization scheme： the augmented Lagrangian alternating direction method （ALADM） and its truncated higher-order singular value decomposition （ALADM-THOSVD） version. The former can obtain a high accuracy solution while the latter is more efficient to handle the computationally intractable problems. Experimental results on both synthetic data and real magnetic resonance imaging data show the applicability of our algorithms in high-dimensional tensor data processing.     

Multi-dimensional scattering properties diagnosis system of scale aircraft model in an anechoic chamber

Aiming at the concept of ＂diagnosis＂, a simple and effective broadband radar cross section （RCS） measurement system is constructed, and some multi-dimensional scattering properties diagnosis techniques are presented based on the system. Firstly, a stepped-frequency signal is employed to achieve high range resolution, combining with a variety of signal processing tech- niques. Secondly, cross-range resolution is gained with a rotating table, and the high-resolution two-dimensional （2-D） imaging of the scale model is obtained by the microwave imaging theory. Finally, two receiving antennas with a small distance in altitude are used, and the three-dimensional （3-D） height distribution of scattering points on the scale model is extracted from the phase of images. Some typical bodies and a scale aircraft model are diagnosed in an anechoic chamber. The experimental results show that, after scaling with a metal sphere, the accurate one- dimensional （l-D） RCS pattern of the model is obtained, and it has a large dynamic range. When the bandwidth of the transmitting signal is 4 GHz, the resolution of the 2-D image can reach to 0.037 5 m. The 3-D height distribution of scattering points is given by interferometric measurement. This paper provides a feasible way to obtain high-precision scattering properties parameters of the scale aircraft model in a conventional rectangular anechoic chamber.     

SIFT与核局部不变映射结合的特征描述算法

为更好地实现图像跟踪,寻找更具鲁棒性和计算简便的特征描述子,提出了一种基于核局部不变映射的尺度不变特征转换(scale invariant feature transform, SIFT)特征描述算法。该算法在继承SIFT算法良好性质的基础上,依据不同空间尺度下能量特征差异性,对尺度内的子图像层数进行细化,以提高稳定特征点的数量。此外,借助核方法的映射特性,解决了局部不变映射法丢失非线性高维特征的问题,形成一种基于核局部不变映射的非线性降维法,进而对特征描述子进行特征重划。实验结果表明,在图像尺度缩放、旋转、模糊、亮度变化等多种场景下,相较现有的主成分分析 SIFT算法,该描述子不但取得更多的稳定特征点,而且计算速度也得到大幅提升。     

Chaos and Nonlinear Feedback Control of the Arch Micro-Electro-Mechanical System

This paper addresses a nonlinear feedback control problem for the chaotic arch microelectro- mechanical system with unknown parameters, immeasurable states and partial state-constraint subjected to the distributed electrostatic actuation. To reflect inherent properties and design controller, the phase diagrams, bifurcation diagram and Poincare section are presented to investigate the nonlinear dynamics. The authors employ a symmetric barrier Lyapunov function to prevent violation of constraint when the arch micro-electro-mechanical system faces some limits. An RBF neural network system integrating with an update law is adopted to estimate unknown function with arbitrarily small error. To eliminate chaotic oscillation, a neuro-adaptive backstepping control scheme fused with an extended state tracking differentiator and an observer is constructed to lower requirements on measured states and precise system model. Besides, introducing an extended state tracking differentiator avoids repeated derivative for the virtual control signal associated with conventional backstepping. Finally, simulation results are presented to illustrate feasibility of the proposed scheme.     

Data-Driven Leader-Follower Output Synchronization for Networked Non-Linear Multi-Agent Systems with Switching Topology and Time-Varying Delays

This paper studies the output synchronization problem for a class of networked non-linear multi-agent systems with switching topology and time-varying delays. To synchronize the outputs, a leader is introduced whose connectivity to the followers varies with time, and a novel data-driven consensus protocol based on model free adaptive control is proposed, where the reference input of each follower is designed to be the time-varying average of the neighboring agents’ outputs. Both the case when the leader is with a prescribed reference input and the case otherwise are considered. The proposed protocol allows for time-varying delays, switching topology, and does not use the agent structure or the dynamics information implicitly or explicitly. Sufficient conditions are derived to guarantee the closed-loop stability, and conditions for consensus convergence are obtained, where only a joint spanning tree is required. Numerical simulations and practical experiments are conducted to demonstrate the effectiveness of the proposed protocol.     

基于前景理论的订货问题

针对需求不确定条件下的订货问题,传统订货模型都是基于期望效用理论,该理论假设决策者是完全理性的,这不符合决策者的现实决策行为,而前景理论正是描述不确定条件下个体实际决策行为的理论。应用前景理论,针对需求不确定条件下零售商的订货行为,建立了新订货模型,并与传统订货模型做了实证比较分析。结果表明,在我国早餐订货过程中,零售商并不是完全理性的,其倾向于风险规避,会适度减少订货量,基于前景理论的订货模型能够更好的描述零售商的订货行为。     

An equivalency condition of nonsingularity in nonlinear semidefinite programming

<正> In this paper,an equivalency condition of nonsingularity in nonlinear semidefinite programming,which can be viewed as a generalization of the equivalency condition of nonsingularity for linearsemidefinite programming,is established under certain conditions of convexity.