Finance and the technology-trade nexus

This paper sketches the contours of the evolving international/monetary system and examines the various roles of the intemediation mechanisms. Then it examines the extent to which the financial system is independent from the “real economy” and the various ways in which it impacts it. The paper discusses some views in good currency on the dynamics of the technology-trade-finance nexus and shows how the financial system influences organization, location and technology choices in meso-innovation systems. The final section of the paper looks at the policy implications that might be derived from the analysis and suggests some directions for the future research.     

Blind estimation of the PN sequence in lower SNR DS-SS signals with residual carrier

This paper presents a method of singular value decomposition (SVD) plus digital phase lock loop (DPLL) to solve the difficult problem of blind pseudo-noise (PN) sequence estimation in low signal to noise ratios (SNR) direct sequence spread spectrum (DS-SS, DS) signals with residual carrier. Of course, the method needs to know the parameters of DS signal, such as the period and code rate of PN sequence. Firstly, the received signal is sampled and divided into non-overlapping signal vectors according to a temporal window, whose duration is two periods of PN sequence. Then, an autocorrelation matrix is computed and accumulated by the signal vectors one by one. The PN sequence with residual carrier can be estimated by the principal eigenvector of this autocorrelation matrix. Furthermore, a DPLL is used to deal with the estimated PN sequence with residual carrier, it estimates and tracks the residual carrier, removes the residual carrier in the end. Theory analysis and computer simulation results show that this method can effectively realize the PN sequence estimation from the input DS signals with residual carrier in lower SNR.     

A simple method of rapid and automatic color image segmentation for serialized Visible Human slices

In this paper, a rapid and automatic color image segmentation method for the serialized slices of the Visible Human is proposed. The main strategy is based on region growing and pixel color difference. A rapid color similarity computing method is improved and applied for classifying different pixels. An algorithm based on corrosion from four directions is proposed to automatically extract the seed points for the serialized slices. Utilizing this method, the color slice images of the Visible Human body can be segmented in series automatically. Also, the multithreading frame of parallel computing is introduced in the entire segmentation process. This method is simple but rapid and automatic. The primary organs of the Visible Human can be segmented clearly and accurately. The 3D models of these organs after 3D reconstruction are satisfactory. This novel method can provide support to the Visible Human research.     

A GPU-based parallel method for evolutionary tree construction

Evolutionary trees are widely applied in various applications to show the inferred evolutionary relationships among species or entities. Neighbor-Joining is one solution for data-intensive and time-consuming evolutionary tree construction, with polynomial time complexity. However, its performance becomes poorer with the growth of massive datasets. Graphics Processing Units (GPUs) have brought about new opportunities for these time-consuming applications. Based on its high efficiency, a GPU-based parallel Neighbor-Joining method is proposed, and two efficient parallel mechanisms, data segmentation with asynchronous processing and the minimal chain model with bitonic sort, are put forward to speed up the processing. The experimental results show that an average speedup of 25.1 is achieved and even approximately 30 can be obtained with a sequence dataset ranging from 16,000 to 25,000. Moreover, the proposed parallel mechanisms can be effectively exploited in some other high performance applications.     

Robust passive autofocus system for mobile phone camera applications

A robust autofocus system is a ubiquitous function in today’s mobile phone camera applications. However, due to the power consumption and size requirements, it is difficult for the autofocus function to be implemented into the design of mobile phone cameras. This paper presents a passive autofocus system with low computational complexity. This system uses a novel contrast measurement to determine degree of image sharpness, which can better reflect the information about image discontinuities. In order to gauge the performance of this measurement, a modified peak search strategy is used in the experiments. The experimental results from several typical image sequences validate the effectiveness of the proposed method.     

A Non-Line-of-Sight mitigation localization algorithm for sensor networks using clustering analysis

Non-Line-of-Sight propagation of wireless signal has an impact on measured distances in range-based localization and will bias the final localization results. A new localization algorithm is proposed in this paper to mitigate Non-Line-of-Sight errors when there are more than enough anchor nodes deployed around the node to be located. This algorithm utilizes multi-round clustering analysis to filter the pre-located estimators which derive from all possible subsets of measured distances. In each round, the method density-based spatial clustering of applications with noise is adopted. Simulations show that the proposed algorithm can effectively improve localization accuracy not only when the measured distances with Non-Line-of-Sight error are minor but also under the condition that all of them suffer random Non-Line-of-Sight error.     

Containment control of multi‐agent systems by exploiting the control inputs of neighbors

This paper studies the containment control problem for multi‐agent systems consisting of multiple leaders and followers connected as a network. The objective is to design control protocols so that the leaders will converge to a certain desired formation while the followers converge to the convex hull of the leaders. A novel protocol is proposed by exploiting the control input information of neighbors. Both continuous‐time and discrete‐time systems are considered. For continuous‐time systems, it is proved that the protocol is robust to any constant delays of the neighbors' control inputs. For discrete‐time systems, a sufficient condition on the feedback gain for the containment control is given in terms of the time delay and graph information. Some numerical examples are given to demonstrate the results. Copyright © 2013 John Wiley & Sons, Ltd.     

离散时间H∞性能下界研究方法

为了缩小二分法求解最优H∞性能的搜索范围,降低搜索代价,采用状态空间分析法,提出了一种获取H∞性能下界的方法．与一般方法不同,根据此方法所得的下界仅跟H₂ Riccati方程的解有关,而不被卷入该Riccati方程的计算．因此,下界的获取简单．不仅如此,该方法还能揭示最优性能与H∞性能(包括最优控制与H∞控制,最优估计与H∞估计)间的区别和联系、分析多扰动通道对H∞性能的影响以及可预演扰动的有效利用对H∞性能的改善．     

Optimal linear estimation for continuous stochastic systems with random observation delays

This paper is concerned with the linear minimum mean square error estimation for Itô‐type differential equation systems with random delays, where the delay process is modeled as a finite‐state Markov chain. By first introducing a set of equivalent delay‐free observations and then defining two reorganized Markov chains, the estimation problem of random delayed systems is reduced to the one of delay‐free Markov jump linear systems. The estimator is derived by using the innovation analysis method based on the Itô differential formula. And the analytical solution to this estimator is given in terms of two Riccati differential equations that are of finite dimensions. Conditions for existence, uniqueness, and stability of the steady‐state optimal estimator are studied for time‐invariant cases. In this case, the obtained estimator is very easy to implement, and all calculation can be performed off line, leading to a linear time‐invariant estimator. Copyright © 2011 John Wiley & Sons, Ltd.