高速SDRAM控制器的嵌入式设计

为适应高数据吞吐速率的应用场合,在分析同步动态随机存储器(SDRAM)控制器工作原理的基础上,研究支持高数据处理效率可连续读写操作的存储控制算法。利用现场可编程门阵列设计SDRAM嵌入式存储控制器,采用CMD命令形式,根据猝发长度分配连续读写延时,通过数据通道控制与读写操作协同工作提高数据处理效率。测试结果表明,该控制器运行频率高于100 MHz,数据处理效率大于95%,适用于视频采集数据缓存及大型LED显示控制中。     

需求依赖广告费用和销售价格的newsboy型产品库存模型

在假定随机需求是关于销售价格和广告费用的一般函数的前提下,提出一个新的ｎｅｗｓｂｏｙ模型,给出了寻求最优广告费用、销售价格及订货量的分析方法,并且还分析了需求的不确定性对最优销售价格和广告策略的影响．最后,通过数值实例验证了模型的求解过程并得到相关管理启示．     

一种安全有效的基于身份的门限签密方案

签密是一种将加密和数字签名技术结合在一起的思想,它比采用先签名后加密的方法具有更高的效率.基于双线性对技术,提出了一种新的基于身份的门限签密方案.它利用决策双线性Diffie-Hellman(DBDH)问题的困难性在随机预言模型下给出了方案的语义安全性证明,并利用计算Diffie-Hellman(CDH)问题的困难性证明了方案的不可伪造性,同时指出方案具有较高的效率.     

Cops and Robbers from a distance

Cops and Robbers is a pursuit and evasion game played on graphs that has received much attention. We consider an extension of Cops and Robbers, distance k Cops and Robbers, where the cops win if at least one of them is of distance at most k from the robber in G. The cop number of a graph G is the minimum number of cops needed to capture the robber in G. The distance k analogue of the cop number, written c_k(G), equals the minimum number of cops needed to win at a given distance k. We study the parameter c_k from algorithmic, structural, and probabilistic perspectives. We supply a classification result for graphs with bounded c_k(G) values and develop an O(n^2s+3) algorithm for determining if c_k(G)≤s for s fixed. We prove that if s is not fixed, then computing c_k(G) is NP-hard. Upper and lower bounds are found for c_k(G) in terms of the order of G. We prove that

     

An efficient secure proxy verifiably encrypted signature scheme

Verifiably encrypted signature is an important cryptographic primitive, it can convince a verifier that a given ciphertext is an encryption of signature on a given message. It is often used as a building block to construct an optimistic fair exchange. In this paper, we propose a new concept: a proxy verifiably encrypted signature scheme, by combining proxy signature with a verifiably encrypted signature. And we formalize security model of proxy verifiably encrypted signature. After a detail construction is given, we show that the proposed scheme is provably secure in the random oracle model. The security of the scheme is related to the computational Diffie–Hellman problem.     

A poly-hybrid PSO optimization method with intelligent parameter adjustment

This paper presents results on a new hybrid optimization method which combines the best features of four traditional optimization methods together with an intelligent adjustment algorithm to speed convergence on unconstrained and constrained optimization problems. It is believed that this is the first time that such a broad array of methods has been employed to facilitate synergistic enhancement of convergence. Particle swarm optimization is based on swarm intelligence inspired by the social behavior and movement dynamics of bird flocking, fish schooling, and swarming theory. This method has been applied for structural damage identification, neural network training, and reactive power optimization. It is also believed that this is the first time an intelligent parameter adjustment algorithm has been applied to maximize the effectiveness of individual component algorithms within the hybrid method. A comprehensive sensitivity analysis of the traditional optimization methods within the hybrid group is used to demonstrate how the relationship among the design variables in a given problem can be used to adjust algorithm parameters. The new method is benchmarked using 11 classical test functions and the results show that the new method outperforms eight of the most recently published search methodologies.     

On the number of higher order Delaunay triangulations

Higher order Delaunay triangulations are a generalization of the Delaunay triangulation that provides a class of well-shaped triangulations, over which extra criteria can be optimized. A triangulation is order-k Delaunay if the circumcircle of each triangle of the triangulation contains at most k points. In this paper we study lower and upper bounds on the number of higher order Delaunay triangulations, as well as their expected number for randomly distributed points. We show that arbitrarily large point sets can have a single higher order Delaunay triangulation, even for large orders, whereas for first order Delaunay triangulations, the maximum number is 2ⁿ⁻³. Next we show that uniformly distributed points have an expected number of at least 2^{ρ₁n(1+o(1))} first order Delaunay triangulations, where ρ₁ is an analytically defined constant (ρ₁≈0.525785), and for k>1, the expected number of order-k Delaunay triangulations (which are not order-i for any i<k) is at least 2^{ρ_kn(1+o(1))}, where ρ_k can be calculated numerically.     

Random linear-quadratic mathematical models: Computing explicit solutions and applications

This paper deals with the study of linear random population models and with a random logistic model (where parameters are random variables). Assuming appropriate conditions, the stochastic processes solutions are obtained under closed form using mean square calculus. Expectation and variance expressions for the stochastic processes solutions are given and illustrative examples are included.     

A comparative runtime analysis of heuristic algorithms for satisfiability problems

The satisfiability problem is a basic core NP-complete problem. In recent years, a lot of heuristic algorithms have been developed to solve this problem, and many experiments have evaluated and compared the performance of different heuristic algorithms. However, rigorous theoretical analysis and comparison are rare. This paper analyzes and compares the expected runtime of three basic heuristic algorithms: RandomWalk, (1+1) EA, and hybrid algorithm. The runtime analysis of these heuristic algorithms on two 2-SAT instances shows that the expected runtime of these heuristic algorithms can be exponential time or polynomial time. Furthermore, these heuristic algorithms have their own advantages and disadvantages in solving different SAT instances. It also demonstrates that the expected runtime upper bound of RandomWalk on arbitrary k-SAT (k?3) is O(n(k−1)), and presents a k-SAT instance that has Θ(n(k−1)) expected runtime bound.     

Data reductions, fixed parameter tractability, and random weighted d-CNF satisfiability

Data reduction is a key technique in the study of fixed parameter algorithms. In the AI literature, pruning techniques based on simple and efficient-to-implement reduction rules also play a crucial role in the success of many industrial-strength solvers. Understanding the effectiveness and the applicability of data reduction as a technique for designing heuristics for intractable problems has been one of the main motivations in studying the phase transition of randomly-generated instances of NP-complete problems.In this paper, we take the initiative to study the power of data reductions in the context of random instances of a generic intractable parameterized problem, the weighted d-CNF satisfiability problem. We propose a non-trivial random model for the problem and study the probabilistic behavior of the random instances from the model. We design an algorithm based on data reduction and other algorithmic techniques and prove that the algorithm solves the random instances with high probability and in fixed-parameter polynomial time O(dknm) where n is the number of variables, m is the number of clauses, and k is the fixed parameter. We establish the exact threshold of the phase transition of the solution probability and show that in some region of the problem space, unsatisfiable random instances of the problem have parametric resolution proof of fixed-parameter polynomial size. Also discussed is a more general random model and the generalization of the results to the model.