Showing papers by "Xidian University published in 2000"

A novel genetic algorithm based on immunity

Abstract: A novel algorithm, the immune genetic algorithm (IGA), is proposed based on the theory of immunity in biology which mainly constructs an immune operator accomplished by two steps: 1) a vaccination and 2) an immune selection. IGA proves theoretically convergent with probability 1. Strategies and methods of selecting vaccines and constructing an immune operator are also given. IGA is illustrated to be able to restrain the degenerate phenomenon effectively during the evolutionary process with examples of TSP, and can improve the searching ability and adaptability, greatly increase the convergence rate.

Multiobjective programming using uniform design and genetic algorithm

Abstract: The notion of Pareto-optimality is one of the major approaches to multiobjective programming. While it is desirable to find more Pareto-optimal solutions, it is also desirable to find the ones scattered uniformly over the Pareto frontier in order to provide a variety of compromise solutions to the decision maker. We design a genetic algorithm for this purpose. We compose multiple fitness functions to guide the search, where each fitness function is equal to a weighted sum of the normalized objective functions and we apply an experimental design method called uniform design to select the weights. As a result, the search directions guided by these fitness functions are scattered uniformly toward the Pareto frontier in the objective space. With multiple fitness functions, we design a selection scheme to maintain a good and diverse population. In addition, we apply the uniform design to generate a good initial population and design a new crossover operator for searching the Pareto-optimal solutions. The numerical results demonstrate that the proposed algorithm can find the Pareto-optimal solutions scattered uniformly over the Pareto frontier.

Proxy multi-signature scheme: a new type of proxy signature scheme

Abstract: Proxy signature schemes allow a proxy signer to generate a proxy signature on behalf of an original signer. However, since in previous proxy signature schemes a proxy signature is created on behalf of only one original signer, these schemes are referred to as proxy mono-signature schemes. A new type of proxy signature scheme is presented called the proxy multi-signature scheme in which a proxy signer can generate a proxy signature on behalf of two or more original signers.

Study of WO3-based sensing materials for NH3 and NO detection

Abstract: Gas sensing materials of WO3 loaded with 1 wt.% metal oxides were prepared and applied for NH3 and NO detection. The measurement of NH3 and NO sensing properties of the materials revealed that WO3+1 wt.% Mg, WO3+1 wt.% Zn, WO3+1 wt.% Mo and WO3+1 wt.% Re characterized good responses to NH3 and NO. As a whole, these materials have low resistance, high sensitivity and fast response to NH3 and NO compared with pure WO3. The possibility of NH3–NO equivalent point sensor was discussed. It can be used for real time monitoring, and controlling the reduction of NO using NH3.

Identity verification in quantum key distribution

Abstract: The security of the previous quantum key distribution protocols, which is guaranteed by the laws of quantum physics, is based on legitimate users. However, impersonation of the legitimate communicators by eavesdroppers, in practice, will be inevitable. In this paper, we proposed a quantum key verification scheme, which can simultaneously distribute the quantum secret key and verify the communicators' identity. Investigation shows that this proposed identity verification scheme is secure.

Oxygen sensors based on semiconducting metal oxides: an overview

Abstract: An overview is given on the current status and future prospects in research and development of oxygen sensors based on semiconducting metal oxides.

Robust recursive least squares learning algorithm for principal component analysis

Abstract: A learning algorithm for the principal component analysis (PCA) is developed based on the least-square minimization. The dual learning rate parameters are adjusted adaptively to make the proposed algorithm capable of fast convergence and high accuracy for extracting all principal components. The proposed algorithm is robust to the error accumulation existing in the sequential PCA algorithm. We show that all information needed for PCA can he completely represented by the unnormalized weight vector which is updated based only on the corresponding neuron input-output product. The updating of the normalized weight vector can be referred to as a leaky Hebb's rule. The convergence of the proposed algorithm is briefly analyzed. We also establish the relation between Oja's rule and the least squares learning rule. Finally, the simulation results are given to illustrate the effectiveness of this algorithm for PCA and tracking time-varying directions-of-arrival.

A fast algorithm for determining the linear complexity of a sequence with period p/sup n/ over GF(q)

Abstract: A fast algorithm is presented for determining the linear complexity of a sequence with period p/sup n/ over GF (q), where p is an odd prime, and where q is a prime and a primitive root (mod p/sup 2/).

A novel genetic algorithim based on immunity

Abstract: A novel optimal algorithm, immune genetic algorithm (IGA), is proposed based on the theory of immunity in biology, which constructs an immune operator accomplished by two steps, a vaccination and an immune selection. The detail processes of realizing IGA are presented. The methods of selecting vaccines and constructing an immune operator are also given. IGA is illustrated to be able to restrain the degenerate phenomenon evidently during the evolutionary process with examples of TSP, improve the searching capability and efficiency, therefore increase the convergent speed greatly.

Advances in theory and applications of fuzzy clustering

Abstract: The summarization and evaluation of the advances in fuzzy clustering theory are made in the aspects including the criterion functions, algorithm implementations, validity measurements and applications. Several important directions for a further study and the application prospects are also pointed out.

On the aspect sensitivity of high resolution range profiles and its reduction methods

Abstract: It has been shown that high resolution radar range profiles (HRRP) can serve as discriminative features for automatic target recognition (ATR) purpose. A HRRP at a single aspect, however, is very sensitive to the aspect change. For microwave radars, aspect change of tenths of 1/spl deg/ can cause drastic changes in HRRP of aircraft-like targets. The aspect sensitivity of HRRP greatly hinders their potential use in automatic target recognition. This paper investigates the phenomenon of aspect sensitivity of HRRP and methods for its reduction.

The application of the Stewart platform in large spherical radio telescopes

Abstract: For the requirement of trajectory tracking of large spherical radio telescopes, a large fine tuning platform based on the Stewart platform is presented in this paper. The mathematical model for kinematics control is developed with coordinate transformation, and a dynamic analysis is made using a Jacobian matrix. Furthermore, the singularity analysis of the designed platform is also made using the determinant of the Jacobian matrix, which has built a solid base for the tracking control. The kinematics accuracy is obtained by position vector analysis. These results have shown the validity of the designed fine tuning platform for the feed source trajectory tracking control of large spherical radio telescopes. ©2000 John Wiley & Sons, Inc.

Classification mechanism of support vector machines

Abstract: The purpose of this paper is to provide an introductory tutorial on the basic ideas behind support vector machines (SVM). The paper starts with an overview of structural risk minimization (SRM) principle, and describes the mechanism of how to construct SVM. For a two-class pattern recognition problem, we discuss in detail the classification mechanism of SVM in three cases of linearly separable, linearly nonseparable and nonlinear. Finally, for nonlinear case, we give a new function mapping technique: By choosing an appropriate kernel function, the SVM can map the low-dimensional input space into the high dimensional feature space, and construct an optimal separating hyperplane with maximum margin in the feature space.

Different focus points images fusion based on wavelet decomposition

Abstract: A new technique is developed for the data fusion of two images. Two spatially registered images with differing focus points are fused by deciding clear objects. At first, an impulse function is defined to describe the image quality of an object. Then the clear region is decided by analyze the wavelet decomposition components of two primary images and two blurred images. The results of the comparison show this method performing better in preserving edge information for the test images than that of other image fusion methods.

Pre-extracting support vectors for support vector machine

Abstract: A new method called center distance ratio method which is able to extract support vectors from given training examples is presented for support vector algorithm. The method greatly reduces the training examples and so improves the speed of support vector machine, while the ability of support vector machine to classify is unaffected. Our experiment results show remarkable improvement of the speed of support vector machine, supporting our idea.

Compensation of scatterer migration through resolution cell in inverse synthetic aperture radar imaging

Abstract: To obtain the inverse synthetic aperture radar image of a target, certain rotation angles of the target with respect to radar line of sight during the coherent integration interval are required, migration of scatterers will take place. Actually, scatterer migration through resolution cells (MTRC) will happen inevitably in high-resolution radar imaging, which will result in image resolution degradation. Scatterer MTRC is discussed, then a simple and an efficient algorithm, the MTRC compensation algorithm (MTRCCA), is proposed to compensate MTRC. The relationship between the MTRCCA, range–doppler and polar formatting algorithms is also discussed. ISAR images from simulated and real data measured in a microwave anechoic chamber are presented to validate the proposed algorithm.

A SVD decomposition of essential matrix with eight solutions for the relative positions of two perspective cameras

Abstract: We improve the robustness of a singular value decomposition method to compute the relative positions between two calibrated perspective cameras. The first one is an optimal step to constrain the essential matrix E to have two equal non-zero and one zero singular values in the presence of noise, which is the sufficient condition for E to be factored as a rotation matrix R and translation vector t. The other contribution is that we have found 4 new possible solutions of R and t to the relative positions of two cameras, which have not been reported in any other SVD methods. Furthermore, these 8 possible solutions are derived directly from the 8 feasible SVD decompositions. Based on the experiments on both simulation data and real images, this method performs very well and the estimation error of R and t are almost at the same level as the noise.

STAP with medium PRF mode for non-side-looking airborne radar

Abstract: Space-time adaptive processing (STAP) has been widely discussed for airborne radar systems to improve the system performance of detecting targets. This is especially true for airborne early warning (AEW) radar, which should find long-range and small radar cross section (RCS) targets such as the stealth aircraft and missiles. However, in existing airborne radar literature, STAP is mainly considered for clutter and jamming rejection in side-looking airborne radar (SLAR) applications. There have been fewer discussions on airborne radar with non-side-ways looking array radar (non-SLAR). The STAP of non-SLAR such as forward looking array radar is also very important and can not be avoided for airborne radar to detect targets in all directions. The STAP of the non-SLAR is studied here. A scheme has been proposed, which is processed by the way of STAP combined with multiple staggered medium pulse repetition frequencies (PRFs). We further study the selection of PRFs in order to make the scheme more available for non-SLAR radar. We analyze two typical non-SLAR cases, i.e., inclined-sideways looking array and forward looking array. We examine this scheme by comparing the performances of three processing systems under the criteria of range-velocity blind zone minimization. Computer simulation results show the multiple-PRFs STAP scheme is feasible for non-SLAR and can be applied to phased-array AEW radar systems.

Learning and tuning of fuzzy membership functions by simulated annealing algorithm

Abstract: Extracting of fuzzy rules and learning of fuzzy membership functions are important and difficult problems in the designing of fuzzy systems. The learning of membership functions for Takaigi-Sugeno fuzzy model is discussed. The learning algorithm of membership functions based on simulated annealing is also presented. Finally, an example is given to demonstrate the validity of this algorithm.

Radar target recognition based on support vector machine

Abstract: Support vector machine is a new kind technique for pattern recognition. We study the classification mechanism of SVM in detail in this paper. Finally, the simulations are done according to SVM algorithm and the results show the advantage of it.

Electrical conduction and oxygen sensing mechanism of Mg-doped SrTiO3 thick film sensors

Abstract: The dependencies of the electrical conduction of Mg-doped SrTiO3 thick film samples on temperature and oxygen partial pressure have been studied. The Mg contents in SrTiO3 were 10 mol%, 20 mol%, 30 mol%, 40 mol% and 50 mol%, respectively. The experimental results show that all samples exhibit p-type semiconduction in the pO2 region 3.8×10−4–2.6×10−1 atm and temperature range 500–900°C. The temperature at which a maximal resistance is observed decreases from 300°C to 100°C in Mg-doped SrTiO3 samples. The 40 mol% Mg-doped SrTiO3 sample reveals the best oxygen sensing properties. Results are discussed based on the X-ray diffraction and the analysis of defect chemistry.

Parameter optimization in FCM clustering algorithms

Abstract: Weighting exponent m is an important parameter in fuzzy c-means (FCM) clustering algorithm, which directly affects the performance of the algorithm and the validity of fuzzy cluster analysis. However, so far the optimal choice of m is still an open problem. A method of selecting the optimal m is proposed in this paper, which is based on the fuzzy decision theory. The experimental results obtained demonstrate its effectiveness and arrive a conclusion that the optimal range of m is [1.5, 2.5] in practical applications.

Detection of sea-surface radar targets based on multifractal analysis

Abstract: A novel method for detecting radar targets and clutter is proposed. The intrinsic difference in the spectrum of the fractal dimension D/sub q/ between sea clutter and the echoes from ship targets is extracted and used to detect ship targets. The experiments show that a higher detection accuracy can be obtained by using the spectrum of the fractal dimension D/sub q/ than by using fractal dimension.

Mobile cluster protocol in wireless ad hoc networks

Abstract: An adaptive mobile cluster protocol is presented, which sustains mobility perfectly and maintains the stability and robustness of network architecture. Furthermore, it is very easy to adopt overlapping clusters for cluster size optimization. Finally, simulation and numerical results show the conclusions.

Immune evolutionary algorithms

Abstract: Three evolutionary algorithms, the immune genetic algorithm (IGA), the immune evolutionary programming (IEP) and the immune evolutionary strategy (IES), are presented based on the immune theory in biology, which are not only convergent but used for solving complex discrete optimization problems as well. They all construct an immune operator accomplished by two components, vaccination and immune selection. The methods for selecting vaccines and constructing an immune operator are also proposed. Simulations show that these algorithms can restrain the degenerate phenomenon and improve the searching capability of the existing algorithms, therefore increase the convergent speed greatly.

User-dependent perfect-scheduling multiple access (UPMA) for wireless ad hoc Internet access

Abstract: A new multiple access protocol for wireless Internet access called user-dependant perfect-scheduling multiple access (UPMA) is proposed. Packet transmissions are scheduled according to the number of active users, packet queue length and round-robin service rule. The number of active users are determined by the proposed self-organizing algorithm. Users in the ad hoc network are divided into clusters by the self-organizing algorithm. UPMA algorithms for star and ad hoc wireless networks are given. Performance analysis shows that UPMA has very high throughput.