AVL树研究与实现

计算机最广为人知的优点之一是其能储存大量的数据,如今随着时代的发展,储存容量更是犹如日进千里一般极速扩展,大容量的硬盘、U盘早已随处可见。然而,要在巨大的数据中搜索出需要的内容却不是一件容易的事,由此,为了能减少在搜索储存数据上的开销,各种适应于不同访问搜索背景的数据结构应运而生。树,便是计算机学科中最基本的数据结构之一,提供了快速的储存和访问性能。该文探究了带有平衡条件的二叉查找树——AVL树的原理,并对其使用C语言进行了实现。     

Accelerating a Recurrent Neural Network to Finite-Time Convergence for Solving Time-Varying Sylvester Equation by Using a Sign-Bi-power Activation Function

Bartels–Stewart algorithm is an effective and widely used method with an O(n ³) time complexity for solving a static Sylvester equation. When applied to time-varying Sylvester equation, the computation burden increases intensively with the decrease of sampling period and cannot satisfy continuous realtime calculation requirements. Gradient-based recurrent neural network are able to solve the time-varying Sylvester equation in real time but there always exists an estimation error. In contrast, the recently proposed Zhang neural network has been proven to converge to the solution of the Sylvester equation ideally when time goes to infinity. However, this neural network with the suggested activation functions never converges to the desired value in finite time, which may limit its applications in realtime processing. To tackle this problem, a sign-bi-power activation function is proposed in this paper to accelerate Zhang neural network to finite-time convergence. The global convergence and finite-time convergence property are proven in theory. The upper bound of the convergence time is derived analytically. Simulations are performed to evaluate the performance of the neural network with the proposed activation function. In addition, the proposed strategy is applied to online calculating the pseudo-inverse of a matrix and nonlinear control of an inverted pendulum system. Both theoretical analysis and numerical simulations validate the effectiveness of proposed activation function.     

An update-based step-wise optimal cache replacement for wireless data access

Many network applications requires access to most up-to-date information. An update event makes the corresponding cached data item obsolete, and cache hits due to obsolete data items become simply useless to those applications. Frequently accessed but infrequently updated data items should get higher preference while caching, and infrequently accessed but frequently updated items should have lower preference. Such items may not be cached at all or should be evicted from the cache to accommodate items with higher preference. In wireless networks, remote data access is typically more expensive than in wired networks. Hence, an efficient caching scheme considers both data access and update patterns can better reduce data transmissions in wireless networks. In this paper, we propose a step-wise optimal update-based replacement policy, called the Update-based Step-wise Optimal (USO) policy, for wireless data networks to optimize transmission cost by increasing effective hit ratio. Our cache replacement policy is based on the idea of giving preference to frequently accessed but infrequently updated data, and is supported by an analytical model with quantitative analysis. We also present results from our extensive simulations. We demonstrate that (1) the analytical model is validated by the simulation results and (2) the proposed scheme outperforms the Least Frequently Used (LFU) scheme in terms of effective hit ratio and communication cost.     

Fast and effective color-based object tracking by boosted color distribution

In this paper, we propose a novel tracking algorithm, boosted color distribution (BCD), for tracking color objects. There exist three contributions in this paper. First, we propose a novel online gentle boost (OGB) algorithm for online learning. The essential idea of OGB is composed of two aspects: online updating candidate weak classifiers, and then choosing and combining them in a boosting way. Second, we design a novel weak classifier, log color feature distribution ratio, which focuses on the difference of color distributions rather than individual samples and provides a simple yet effective manner of mining color features for object tracking. Third, by combining our OGB algorithm and our log color features, we develop a fast yet effective color-based object tracking algorithm. Numerous experiments demonstrate that our tracking algorithm is better than or not worse than some state-of-the-art tracking algorithms on some public sequences.Overall, this paper presents a novel BCD algorithm for color object tracking that achieves good results at a fast speed.     

Uncertain term structure model of interest rate

Term structure models describe the evolution of the yield curve through time, without considering the influence of risk, tax, etc. Recently, uncertain processes were initialized and applied to option pricing and currency model. Under the assumption of short interest rate following uncertain processes, this study investigates the term-structure equation. This equation is first derived for valuing zero-coupon bond. Finally, analytic solutions of the uncertain interest rate equation are given when the process of interest rate is assumed to be the uncertain counterparts of the Ho-Lee model and Vasicek model, respectively.     

Parallel computation of determinants of matrices with multivariate polynomial entries

In this paper we present an extension to the work of Björck et al. for computing the determinants of matrices with univariate or bivariate polynomials as entries to multivariate case. The algorithm supports parallel computation and has been implemented on a multi-core cluster computer system. We show how to use our approach to calculate two unsolved problems, which arise from computational geometry optimization and electric power engineering, and analyze the time complexity as well as bits complexity.     

Creating a live, public short message service corpus: the NUS SMS corpus

Short Message Service (SMS) messages are short messages sent from one person to another from their mobile phones. They represent a means of personal communication that is an important communicative artifact in our current digital era. As most existing studies have used private access to SMS corpora, comparative studies using the same raw SMS data have not been possible up to now. We describe our efforts to collect a public SMS corpus to address this problem. We use a battery of methodologies to collect the corpus, paying particular attention to privacy issues to address contributors’ concerns. Our live project collects new SMS message submissions, checks their quality, and adds valid messages. We release the resultant corpus as XML and as SQL dumps, along with monthly corpus statistics. We opportunistically collect as much metadata about the messages and their senders as possible, so as to enable different types of analyses. To date, we have collected more than 71,000 messages, focusing on English and Mandarin Chinese.     

小型水利工程项目划分分析

以小型水利工程项目划分为对象,从质量监督确认工作角度出发,根据小型水利工程的特点,探讨在现有规程下针对实际不同工程的恰当的项目划分方式,以利参建各方更好地控制工程质量。     

网络防火墙技术发展

网络的高速发展带来便利的同时,也给3G用户带来诸多不便,入侵、病毒传染等问题严重威胁到用户3G网络的正常使用,因此,网络防火墙的发展起到了至关重要的作用,本文就3G网络发展的现状与存在威胁,分析网络防火墙技术的发展,以助于确保用户更好的正常使用.