1.

ON THE OPTIMIZATION OF VLSI ALLOCATION IN HIGHLEVEL SYNTHESIS





He Zhongli Zhou Dian Hu Qingsheng Zhuang Zhenquan《电子科学学刊(英文版)》,2000年第17卷第3期


Allocation is one of main tasks in the highlevel synthesis. It includes module , functional unit allocation, storage allocation and interconnection allocation. This paper models the allocation problem as cluster analysis and applies a new algorithm, neighbor state transition (NST) algorithm, for cluster optimization. It is proved that the algorithm produces an asymptotically global optimal solution with the upper bound on the cost function (1 O(1/n)2ε)F*, When F" is the cost of the optimum solution, n is the problem size and e is a positive parameter arbitrarily close to zero. The numerical examples show that the NST algorithm produces better results compared to the other known methods.

2.

Two new upper bounds of the solution for the continuous algebraic Riccati equation and their application





XIA YaPing CAI ChenXiao YIN MingHui ZOU Yun《中国科学:信息科学(英文版)》,2015年第5期


In this paper, for the solution of the continuous algebraic Riccati equation(CARE), we derived two new upper matrix bounds. Compared with the existing results, the newly obtained bounds are less conservative and more practical, which means that the condition for the existence of the upper bounds derived here is much weaker. The advantage of the results is shown by theoretical analysis and numerical examples. Moreover, in redundant optimal control, when we increase the columns of the input matrix, some sufficient conditions are presented to strictly decrease the largest singular value of the feedback matrix by utilizing these upper bounds.We also give some examples to illustrate the effectiveness of these sufficient conditions.

3.

A Nonheuristic Approach to the General Two Water Jugs Problem





YiuKwong Man《通讯和计算机》,2013年第7期


The two water jugs problem is a famous problem in recreational mathematics, problemsolving, artificial intelligence, neuroscience, computer programming and cognitive psychology. The methods of solutions are usually based on heuristics or search methods such as BFS （breadth first search） or DFS （depth first search）, which could be time and memory consuming. In this paper, we present a nonheuristic approach to solve this problem, which can be modeled by the Diophantine equation mx＋ ny  d, where m, n denote the capacities of the jugs and d denotes the amount of water to be determined, with 0 〈 m 〈 n and 0 〈 d 〈 n. By simple additions and subtractions only, the special solutions （x, y） can be found very easily by using the nonHeuristic approach, which correspond to the number of times of the water jugs being fully filled in the whole water pouring process. Also, a simple formula for determining an upper bound on the total number of pouring steps involved is derived, namely 2（m ＋ n  2）, based on the method of linear congruence. Due to its simplicity and novelty, this approach is suitable for either hand calculation or computer programming. Some illustrative examples are provided.

4.

一种基于边缘特征的聚类学习新方法





刘道海 方毅 黄樟灿《计算机科学》,2002年第29卷第2期


According to mankind‘‘‘‘s actual classing procedure for substance,this paper puts forward a new Clustering Learning based on Edge Character(CLEC) approach that is different from some traditional methods.This approach does not depend on the number of class sorts that is very difficult to be gotten accurately and for which the result is rather sensitive.On the other hand,CLEC is fit in the processing to distribution data.The experiments sufficiently proved the efficacy of this approach.

5.

The upper bound of the minimal number of hidden neurons for the parity problem in binary neural networks 被引次数：1





LU Yang YANG Juan WANG Qiang HUANG ZhenJin《中国科学:信息科学(英文版)》,2012年第7期


Binary neural networks (BNNs) have important value in many application areas.They adopt linearly separable structures,which are simple and easy to implement by hardware.For a BNN with single hidden layer,the problem of how to determine the upper bound of the number of hidden neurons has not been solved well and truly.This paper defines a special structure called most isolated samples (MIS) in the Boolean space.We prove that at least 2 n 1 hidden neurons are needed to express the MIS logical relationship in the Boolean space if the hidden neurons of a BNN and its output neuron form a structure of AND/OR logic.Then the paper points out that the n bit parity problem is just equivalent to the MIS structure.Furthermore,by proposing a new concept of restraining neuron and using it in the hidden layer,we can reduce the number of hidden neurons to n .This result explains the important role of restraining neurons in some cases.Finally,on the basis of Hamming sphere and SP function,both the restraining neuron and the n bit parity problem are given a clear logical meaning,and can be described by a series of logical expressions.

6.

A Taxonomy of Exact Methods for Partial MaxSAT





Mohamed El Bachir Menai Tasniem Nasser AlYahya《计算机科学技术学报》,2013年第28卷第2期


Partial Maximum Boolean Satisfiability (Partial MaxSAT or PMSAT) is an optimization variant of Boolean satisfiability (SAT) problem, in which a variable assignment is required to satisfy all hard clauses and a maximum number of soft clauses in a Boolean formula. PMSAT is considered as an interesting encoding domain to many reallife problems for which a solution is acceptable even if some constraints are violated. Amongst the problems that can be formulated as such are planning and scheduling. New insights into the study of PMSAT problem have been gained since the introduction of the MaxSAT evaluations in 2006. Indeed, several PMSAT exact solvers have been developed based mainly on the DavisPutnamLogemannLoveland (DPLL) procedure and Branch and Bound (B&B) algorithms. In this paper, we investigate and analyze a number of exact methods for PMSAT. We propose a taxonomy of the main exact methods within a general framework that integrates their various techniques into a unified perspective. We show its effectiveness by using it to classify PMSAT exact solvers which participated in the 2007～2011 MaxSAT evaluations, emphasizing on the most promising research directions.

7.

Variables Bounding Based Retiming Algorithm





宫宗伟 林争辉 陈后鹏《计算机科学技术学报》,2002年第17卷第6期


Retiming is a technique for optimizing sequential circuits.In this paper,we discuss this problem and propose an improved retiming algorithm based on varialbes bounding.Through the computation of the lower and upper bounds on variables,the algorithm can significantly reduce the number of constratints and speed up the execution of retiming.Furthermore,the elements of matrixes D and W are computed in a demanddriven way,which can reduce the capacity of memory,It is shown through the experimental results on ISCAS89 benchmarks that our algorithm is very effective for largescale seuqential circuits.

8.

Interval Arithmetic and Its Application to Electrical Circuits





Nacira Diffellah Fouzia Hamadache Fouzia Hamadachel＇ and Khier Benmahammed《计算机技术与应用:英文》,2013年第8期


Interval arithmetic is an elegant tool for practical work with inequalities, approximate numbers, error bounds, and more generally with certain convex and bounded sets. In this section we give a number of simple examples showing where intervals and ranges of functions over intervals arise naturally. Interval mathematics is a generalization in which interval numbers replace real numbers, interval arithmetic replaces real arithmetic, and interval analysis replaces real analysis. Interval is limited by two bounds： lower bound and upper bound. The present paper introduces some of the basic notions and techniques from interval analysis needed in the sequel for presenting various uses of interval analysis in electric circuit theory and its applications. In this article we address the representation of uncertain and imprecise information, the interval arithmetic and its application to electrical circuits.

9.

A unified extending method for contentignorant web page clustering





Shi Lin Chen Chen《电子科学学刊(英文版)》,2010年第27卷第1期


The contentignorant clustering method takes advantages in time complexity and space complexity than the content based methods. In this paper, the authors introduce a unified expanding method for contentignorant web page clustering by mining the “clickthrough” log, which tries to solve the problem that the “clickthrough” log is sparse. The relationship between two nodes which have been expanded is also defined and optimized. Analysis and experiment show that the performance of the new method has improved, by the comparison with the standard contentignorant method. The new method can also work without iterative clustering.

10.

Pricebased interference avoidance game in the Gaussian interference channel





JING ZhenHai BAI BaoMing & MA Xiao State《中国科学:信息科学(英文版)》,2012年第2期


This paper considers a distributed interference avoidance problem employing frequency assignment in the Gaussian interference channel(IC).We divide the common channel into several subchannels and each user chooses one subchannel for transmission in such a way that the total interference in the IC is minimum.This mechanism named interference avoidance in this paper can be modeled as a competitive game model.And a completely autonomous distributed iterative algorithm called distributed interference avoidance algorithm(DIA)is adopted to achieve the Nash equilibrium(NE)of the game.Due to the selfoptimum,the DIA is a suboptimal algorithm.Therefore,through introducing an optimal compensation(or price)into the competitive game model,we successfully develop a compensationbased game model to approximate the optimal interference avoidance problem.Moreover,an optimal algorithm called iterative optimal interference avoidance algorithm(IOIA)is proposed to reach the optimality of the interference avoidance scheme.We analyze the implementation complexity of the proposed algorithm which is only O(N),with N standing for the number of users in the IC.We also give the proof on the convergence of the proposed algorithm.The performance upper bound and lower bound are derived for the IOIA algorithm.The simulation results show that the IOIA does reach the optimality under the condition of interference avoidance mechanism.

11.

Finite horizon optimal control of discretetime nonlinear systems with unfixed initial state using adaptive dynamic programming





Qinglai WEI Derong LIU《控制理论与应用(英文版)》,2011年第9卷第3期


In this paper, we aim to solve the finite horizon optimal control problem for a class of discretetime nonlinear systems with unfixed initial state using adaptive dynamic programming (ADP) approach. A new εoptimal control algorithm based on the iterative ADP approach is proposed which makes the performance index function converge iteratively to the greatest lower bound of all performance indices within an error according to ε within finite time. The optimal number of control steps can also be obtained by the proposed εoptimal control algorithm for the situation where the initial state of the system is unfixed. Neural networks are used to approximate the performance index function and compute the optimal control policy, respectively, for facilitating the implementation of the εoptimal control algorithm. Finally, a simulation example is given to show the results of the proposed method.

12.

Double Barrier Coverage in Dense Sensor Networks





蒋承东 陈国良《计算机科学技术学报》,2008年第23卷第1期


When a sensor network is deployed to detect objects penetrating a protected region, it is not necessary to have every point in the deployment region covered by a sensor. It is enough if the penetrating objects are detected at some point in their trajectory. If a sensor network guarantees that every penetrating object will be detected by two distinct sensors at the same time somewhere in this area, we say that the network provides double barrier coverage （DBC）. In this paper, we propose a new planar structure of Sparse Delaunay Triangulation （SparseDT）, and prove some elaborate attributes of it. We develop theoretical foundations for double barrier coverage, and propose efficient algorithms with NS2 simulator using which one can activate the necessary sensors to guarantee double barrier coverage while the other sensors go to sleep. The upper and lower bounds of number of active nodes are determined, and we show that highspeed target will be detected efficiently with this configuration.

13.

NEAR OPTIMAL CLUSTERHEAD SELECTION FOR WIRELESS SENSOR NETWORKS





Zhu Xiaorong Shen Lianfeng《电子科学学刊(英文版)》,2007年第24卷第6期


Clustering in wireless sensor networks is an effective way to save energy and reuse band width. To our best knowledge, most of the clustering protocols proposed in literature are of a dynamic type, where cluster heads are selected in each period, followed by cluster formation. In this paper, a new static type clustering method called Hausdorff clustering, which is based on the location of sensor nodes as well as communication efficiency and network connectivity, is proposed. The cluster head, however, is rotated within the cluster by a fuzzy logic algorithm that optimizes the network lifetime. Simulation results show that this approach can significantly increase the lifetime of the sensor network.

14.

Explicitform complex orthogonal design for spacetime block codes





LI Yuan YUAN Chen KAN HaiBin《中国科学:信息科学(英文版)》,2013年第6期


In this paper,we present a construction of complex orthogonal design for spacetime block codes in any number of antennas.Our construction achieves both the maximal rate and minimal delay.So far as we know,our construction is the first explicitform construction,which has asymptotically optimal time complexity and space complexity.And new representation of complex orthogonal design might bring advantages in analyzing some properties.In addition,when the number of antennas n ≡ 1,2,3(mod 4),our construction satisfies transceiver signal linearization property,which allows for design of low complexity channel equalizers and interference suppressing filters.

15.

New Robust Exponential Stability Analysis for Uncertain Neural Networks with Timevarying Delay 被引次数：3





YongGang Chen WeiPing Bi《国际自动化与计算杂志》,2008年第5卷第4期


In this paper, the global robust exponential stability is considered for a class of neural networks with parametric uncertainties and timevarying delay. By using Lyapunov functional method, and by resorting to the new technique for estimating the upper bound of the derivative of the Lyapunov functional, some less conservative exponential stability criteria are derived in terms of linear matrix inequalities (LMIs). Numerical examples are presented to show the effectiveness of the proposed method.

16.

L 2gain analysis and antiwindup design of discretetime switched systems with actuator saturation





XinQuan Zhang Jun Zhao《国际自动化与计算杂志》,2012年第9卷第4期


This paper investigates L2gain analysis and antiwindup compensation gains design for a class of discretetime switched systems with saturating actuators and L2 bounded disturbances by using the switched Lyapunov function approach.For a given set of antiwindup compensation gains,we firstly give a sufficient condition on tolerable disturbances under which the state trajectory starting from the origin will remain inside a bounded set for the corresponding closedloop switched system subject to L2 bounded disturbances.Then,the upper bound on the restricted L2gain is obtained over the set of tolerable disturbances.Furthermore,the antiwindup compensation gains aiming to determine the largest disturbance tolerance level and the smallest upper bound of the restricted L2gain are presented by solving a convex optimization problem with linear matrix inequality(LMI) constraints.A numerical example is given to illustrate the effectiveness of the proposed design method.

17.

A survey on delayed feedback control of chaos 被引次数：1





Yuping TIAN Jiandong ZHU Guanrong CHEN《控制理论与应用(英文版)》,2005年第3卷第4期


This paper introduces the basic idea and provides the mathematical formulation of the delayed feedback control （DFC） methodology, which has been widely used in chaos control. Stability analysis including the wellknown odd number linfitation of the DFC is reviewed. Some new developments in characterizing the limitation of the DFC are presented. Various modified DFC methods, which are developed in order to overcome the odd number limitation, are also described. Finally, some open problems in this research field are discussed.

18.

NOTE ON THE JOHNSON'S BOUNDS AND GRAHAM'S BOUNDS FOR CONSTANT WEIGHT CODES





杨义先《电子科学学刊(英文版)》,1988年第5卷第3期


This paper presents four classes of codes which meet the Johnson's upper bound and twoclasses of codes which have gone beyond the Graham's lower bound.

19.

A Fuzzy Similaritybased Clustering Optimized by Particle Swarm Optimization





CHEN Donghui LIU Zhijing WANG Zonghu《电子学报:英文版》,2013年第3期


Traditional fuzzy clustering algorithms based on objective function is unable to determine the optimum number of clusters, sensitive to the initial cluster centers, and easily sunk into the issue of local optimum. A Fuzzy similaritybased clustering （FSBC） algorithm is proposed in this paper. This method consists three phases： first, the objective function is modified by integrating Fuzzy Cmeans （FCM） and Possibilistic Cmeans （PCM） method; second, using the density function from data for similaritybased clustering to automatically generate initial prototype without requesting users to specify; finally, the iteration process optimized by Particle swarm optimization （PSO） to obtain appropriate adjustment parameters that can provide better results, which avoids the local minimum problems of traditional methods. The experimental results on the synthetic data and UCI standard data sets show that the proposed algorithm has greater searching capability, less computational complexity, higher clustering precision.

20.

An upper （lower） bound for Max （Min） CSP





HUANG Ping ;YIN MingHao《中国科学:信息科学(英文版)》,2014年第57卷第7期


The random constraint satisfaction problem(CSP)instances generated by Model RB have been widely used in the field of CSP and have some nice features.In this paper,we consider two optimization versions of CSP,i.e.,the maximum constraint satisfaction problem(MaxCSP)and the minimum satisfaction problem(MinCSP)of Model RB.The problem of the MaxCSP is how to find an assignment to all the variables such that the maximum number of constraints are satisfied and the problem of MinCSP is how to find an assignment to all the variables such that the minimum number of constraints are satisfied.We use the first moment method to prove that when r2α(1/p1)(or p2α/(2α+r)),an upper bound of MaxCSP can be derived.Similarly,we can prove that when r2α(1/p1)(or p2α/(2α+r)),a lower bound of MinCSP can be derived.
