Showing papers in "Science in China Series F: Information Sciences in 2010"

L 1/2 regularization

Abstract: In this paper we propose an L 1/2 regularizer which has a nonconvex penalty. The L 1/2regularizer is shown to have many promising properties such as unbiasedness, sparsity and oracle properties. A reweighed iterative algorithm is proposed so that the solution of the L 1/2 regularizer can be solved through transforming it into the solution of a series of L 1 regularizers. The solution of the L 1/2 regularizer is more sparse than that of the L1 regularizer, while solving the L 1/2 regularizer is much simpler than solving the L 0 regularizer. The experiments show that the L 1/2 regularizer is very useful and efficient, and can be taken as a representative of the Lp (0 p < 1) regularizer.

Robust adaptive fuzzy backstepping output feedback tracking control for nonlinear system with dynamic uncertainties

Abstract: In this paper, an adaptive fuzzy output feedback control approach based on backstepping design is proposed for a class of SISO strict feedback nonlinear systems with unmeasured states, nonlinear uncertainties, unmodeled dynamics, and dynamical disturbances. Fuzzy logic systems are employed to approximate the nonlinear uncertainties, and an adaptive fuzzy state observer is designed for the states estimation. By combining backstepping technique with the fuzzy adaptive control approach, a stable adaptive fuzzy output feedback robust control is constructed recursively, in which nonlinear damping terms and a dynamical signal are introduced to counteract the nonlinear uncertainties and dominate the dynamic disturbances, respectively. It is proved that the proposed adaptive fuzzy control approach guarantees that all the signals of the closed-loop system are semi-globally uniformly bounded, and the tracking error converges to a small neighborhood of the origin. Simulation studies are included to illustrate the effectiveness of the proposed approach.

CCA-secure unidirectional proxy re-encryption in the adaptive corruption model without random oracles

Abstract: Up to now, it is still an open question of how to construct a chosen-ciphertext secure unidirectional proxy re-encryption scheme in the adaptive corruption model. To address this problem, we propose a new unidirectional proxy re-encryption scheme, and prove its chosen-ciphertext security in the adaptive corruption model without random oracles. Compared with the best known unidirectional proxy re-encryption scheme proposed by Libert and Vergnaud in PKC’08, our scheme enjoys the advantages of both higher efficiency and stronger security.

Asymmetric encryption and signature method with DNA technology

Abstract: This paper proposes DNA-PKC, an asymmetric encryption and signature cryptosystem by combining the technologies of genetic engineering and cryptology. It is an exploratory research of biological cryptology. Similar to conventional public-key cryptology, DNA-PKC uses two pairs of keys for encryption and signature, respectively. Using the public encryption key, everyone can send encrypted message to a specified user, only the owner of the private decryption key can decrypt the ciphertext and recover the message; in the signature scheme, the owner of the private signing key can generate a signature that can be verified by other users with the public verification key, but no else can forge the signature. DNA-PKC differs from the conventional cryptology in that the keys and the ciphertexts are all biological molecules. The security of DNA-PKC relies on difficult biological problems instead of computational problems; thus DNA-PKC is immune from known attacks, especially the quantum computing based attacks.

Information entropy for ordinal classification

Abstract: Ordinal classification plays an important role in various decision making tasks. However, little at- tention is paid to this type of learning tasks compared with general classification learning. Shannon information entropy and the derived measure of mutual information play a fundamental role in a number of learning algo- rithms including feature evaluation, selection and decision tree construction. These measures are not applicable to ordinal classification for they cannot characterize the consistency of monotonicity in ordinal classification. In this paper, we generalize Shannon’s entropy to crisp ordinal classification and fuzzy ordinal classification, and show the information measures of ranking mutual information and fuzzy ranking mutual information. We discuss the properties of these measures and show that the proposed ranking mutual information and fuzzy ranking mutual information are the indexes of consistency of monotonicity in ordinal classification. In addition, the proposed indexes are used to evaluate the monotonicity degree between features and decision in the context of ordinal classification.

Color image enhancement based on HVS and PCNN

Abstract: To enhance color images more effectively, a novel strategy is presented in this paper. We firstly translate the image to be enhanced from RGB space into HIS space, secondly keep its H component unchanged, and thirdly stretch its S component exponentially, and at last process its I component in the following manner: couple both the gray value and the spatial information into an inner activity item of corresponding neuron, integrate the human visual system into a dynamic component of corresponding neuron, and compare the inner activity item with dynamic component to obtain the enhanced image. Experiments demonstrate the effectiveness and validity of our strategy.

Direct adaptive neural control for stabilization of nonlinear time-delay systems

Abstract: This paper is concerned with the problem of adaptive neural control for uncertain nonlinear strict-feedback time-delay systems with unknown virtual control coefficients Radial basis function (RBF) neural networks are employed to directly approximate unknown virtual control signals, and then the adaptive neural control law is constructed by Lyapunov-Krasovskii functionals and backstepping In order to avoid encountering a large number of adaptive parameters when using RBF neural networks as function approximators, an unknown constant, instead of unknown neural weights themselves, is employed as the estimated parameter This technique makes only one adaptive parameter tuned online, thus significantly alleviating the burdensome computation Meanwhile, some continuous functions are introduced to overcome the design difficulty originating from the use of one adaptive parameter The proposed adaptive control guarantees the boundedness of all the signals in the closed-loop system Simulation studies are presented to illustrate the effectiveness of the scheme

Receding horizon control for multi-UAVs close formation control based on differential evolution

Abstract: Close formation flight is one of the most complicated problems on multi-uninhabited aerial vehicles (UAVs) coordinated control. Based on the nonlinear model of multi-UAVs close formation, a novel type of control strategy of using hybrid receding horizon control (RHC) and differential evolution algorithm is proposed. The issue of multi-UAVs close formation is transformed into several on-line optimization problems at a series of receding horizons, while the differential evolution algorithm is adopted to optimize control sequences at each receding horizon. Then, based on the Markov chain model, the convergence of differential evolution is proved. The working process of RHC controller is presented in detail, and the stability of close formation controller is also analyzed. Finally, three simulation experiments are performed, and the simulation results show the feasibility and validity of our proposed control algorithm.

A maximum principle for partially observed optimal control of forward-backward stochastic control systems

Abstract: This paper studies an optimal control problem for partially observed forward-backward stochastic control system with a convex control domain and the forward diffusion term containing control variable. A maximum principle is proved for this kind of partially observable optimal control problems and the corresponding adjoint processes are characterized by the solutions of certain forward-backward stochastic differential equations in finite-dimensional spaces. One partially observed recursive linear-quadratic (LQ) optimal control example is also given to show the application of the obtained maximum principle. An explicit observable optimal control is obtained in this example.

Efficient signcryption between TPKC and IDPKC and its multi-receiver construction

Abstract: The primitive signcryption provides authenticity and privacy simultaneously. In this paper, we present efficient signcryption schemes between the traditional public key cryptosystem (TPKC) and the identity based cryptosystem (IDPKC). In contrast, all the existing signcryption schemes available in the literature, to our knowledge, are limited to within one type of cryptosystem. We also discuss them in the multi-receiver setting. Formal security proofs are provided to guarantee the security for our schemes, in the random oracle model, under the hardness of the bilinear Diffie-Hellman problem.

Research on trusted computing and its development

Abstract: Trusted computing is a novel technology of information system security. It has become a new tide in worldwide information security area and achieved inspiring accomplishment. In China, the initiative research of trusted computing is not late, and the achievements are plentiful and substantial. Our country is in the front rank of the world in trusted computing. This paper comprehensively illustrates the recent development in theory and technology of trusted computing, introduces some improvements in trusted computing in our country, and proposes our opinions and viewpoints towards the existing problems in trusted computing and its future development.

Principles and construction of MSD adder in ternary optical computer

Abstract: The two remarkable features of ternary values and a massive unit with thousands bits of parallel computation will make the ternary optical computer (TOC) with modified signed-digit (MSD) adder more powerful and efficient than ever before for numerical calculations. Based on the decrease-radix design presented previously, a TOC can satisfy either a user requiring huge capacity for data calculations or one with a moderate amount of data, if it is equipped with a prepared adder. Furthermore, with the application of pipelined operations and the proposed data editing technique, the efficiency of the prepared adder can be greatly improved, so that each calculated result can be obtained almost within one clock cycle. It is hopeful that by employing a MSD adder, users will be able to enter a new dimension with the creation of a new multiplier, new divider, as well as new matrix operator in a TOC in the near future.

An adaptive hybrid optimizer based on particle swarm and differential evolution for global optimization

Abstract: This paper presents extensive experiments on a hybrid optimization algorithm (DEPSO) we recently developed by combining the advantages of two powerful population-based metaheuristics—differential evolution (DE) and particle swarm optimization (PSO). The hybrid optimizer achieves on-the-fly adaptation of evolution methods for individuals in a statistical learning way. Two primary parameters for the novel algorithm including its learning period and population size are empirically analyzed. The dynamics of the hybrid optimizer is revealed by tracking and analyzing the relative success ratio of PSO versus DE in the optimization of several typical problems. The comparison between the proposed DEPSO and its competitors involved in our previous research is enriched by using multiple rotated functions. Benchmark tests involving scalability test validate that the DEPSO is competent for the global optimization of numerical functions due to its high optimization quality and wide applicability.

Centroid-based semi-fragile audio watermarking in hybrid domain

Abstract: Many previous (semi-) fragile audio watermarking schemes adopt binary images as watermarks, which reduce the security of watermarking systems. On the other hand, the content-based or feature-based second generation digital watermarking has limited applicability, and its partial feature points may be damaged by watermarking operations and various common signal processing. To overcome these problems, in this paper, a novel centroid-based semi-fragile audio watermarking scheme in hybrid domain is proposed. The theoretical lower limit of signal to noise ratio (SNR) for objective evaluation of the imperceptibility of watermarked audio signal is deduced, and the watermark embedding capacity and the tamper detection ability are theoretically analyzed. In the proposed scheme, first, the centroid of each audio frame is computed, then Hash function is performed on the obtained centroid to get the watermark, after that, the audio sub-band which carries centroid of audio frame is performed with discrete wavelet transform (DWT) and discrete cosine transform (DCT), and finally the encrypted watermark bits are embedded into the hybrid domain. Theoretical analysis and experimental results show that the proposed scheme is inaudible and applicable to different types of audio signals. Furthermore, its ability of tamper detection and tolerance against common signal processing operations are excellent. Comparing with the existing schemes, the proposed scheme can effectively authenticate the veracity and integrity of audio content, and greatly expand the applicability of the content-based audio watermarking scheme.

Research on the application of 4-weighted fractional Fourier transform in communication system

Abstract: The paper reveals the relationship between the weighting coefficients and weighted functions via the research of coefficients matrix and based on the original definition of 4-weighted fractional Fourier transform (4-WFRFT). The multi-parameters expression of weighting coefficients are given. Moreover, the 4-WFRFT of discrete sequences is defined by introducing DFT into it, which makes it suitable for digital communication systems. After analyzing the properties of WFRFT, a typical scheme for modulation/demodulation is proposed, which could make the statistics properties of the real and image part on both of the time and frequency domain and the phase properties have a significant variation. Such a variation could be controlled by the adjustment of transform parameters. If the WFRFT of multi-parameters is implemented, it will be more difficult to intercept and capture the modulated signals than normal.

Monocular vision-based iterative pose estimation algorithm from corresponding feature points

Abstract: To determine the relative pose between an object and a single camera using 2D-to-3D point correspondences, a kind of iterative methods based on inverse projection ray approach is proposed. An iterative algorithm which is divided into depth recovery stage and absolute orientation stage is also proposed. In the first stage, the optimal translation vector is first computed in terms of rotation matrix via least square method, then the depths of the observed points are estimated by projecting the estimated point orthogonally to the inverse projection ray defined by the image point, and finally 3D points are reconstructed using the estimated depths from previous step. In the second stage, the optimal rotation matrix is estimated by applying Umeyama algorithm to fitting of the 3D model points and 3D estimated points. The above two stages are repeated until the result converges. The global convergence of the two-stage iterative algorithm is proven based on the global convergence theorem. Finally, a spacecraft docking application is implemented to test the effectiveness and convergence of the proposed algorithm by mathematical simulation and physical simulation.

Target classification with low-resolution radar based on dispersion situations of eigenvalue spectra

Abstract: Most low-resolution radar systems, especially ground surveillance radar systems, work at relatively low pulse repeat frequency (PRF) and with short time-on-target (TOT) (duration in scanning). Low PRF leads to Doppler ambiguity and short TOT results in low Doppler resolution, which poses a problem to target classification with low-resolution radar based on the jet engine modulation (JEM) characteristic of radar echo. From the pattern classification viewpoint, we propose a method of using dispersion situations of JEM eigenvalue spectra to categorize aeroplanes into three kinds, namely turbojet aircraft, prop aircraft and helicopter. We analyze the mathematical model of JEM echoes consisting of a series of line spectra and regard them as a sum of several series of harmonious waves. Classification features can be extracted based on the harmonious wave sum model. Some schemes for extracting features from echoes within or between pulses are proposed. Low-dimensional features are extracted to reduce computation burden. Our methods do not compensate for the fuselage echoes and are insensitive to the variation of fuselage Doppler. The feasibility of our methods is demonstrated by simulation experiment.

Feedback image encryption algorithm with compound chaotic stream cipher based on perturbation

Abstract: In this paper, two new one-dimensional chaotic functions are designed using Devaney chaotic definition. And a dynamically shifting compound chaotic function is constructed based on the two new one-dimensional chaotic functions. The properties of compound chaotic functions are also proved. A new feedback image encryption algorithm is designed using the new compound chaos and an image pixel permutation, 3D baker scheme is described in detail. In the scheme, a new dynamic block dividing the 3D baker is put forward using the compound chaotic map, and the key space expands. In order to produce avalanche effect and sensitivity of cipher to plaintext, the round times are designed to control the cycle. The entropy analysis, difference analysis, weak-key analysis, statistical analysis, cipher random analysis, and cipher sensibility analysis depending on key and plaintext are introduced to test the security of the new scheme of image encryption. The tests show that the image encryption method passes the random tests of NIST FIPS 140-2(2001) and SP 800-22 standards. This paper also solves the problem of short periods and low precision of one-dimensional chaotic function by perturbation.

Basin filling algorithm for the circular packing problem with equilibrium behavioral constraints

Abstract: With the background of the satellite module layout design, the circular packing problem with equilibrium behavioral constraints is a layout optimization problem and NP-hard problem in math. For lack of a powerful optimization method, this problem is hard to solve. The energy landscape paving (ELP) method is a class of stochastic global optimization algorithms based on the Monte Carlo sampling. Based on the quasiphysical strategy and the penalty function method, the problem is converted into an unconstrained optimization problem. Here by combining the improved ELP method, the gradient method based on local search and the heuristic configuration update mechanism, a new global search algorithm, basin filling algorithm, is put forward. The numerical results show that the proposed algorithm is effective to solving the circular packing problem with equilibrium behavioral constraints, and is easy to be popularized to other layout optimization problems.

Research on allocation efficiency of the redistributed pseudo inverse algorithm

Abstract: Allocation efficiency is an important performance index to measure the quality of the allocation algorithm. In order to compute the efficiency, the volume of the subset of attainable moments must be solved. The efficiency of the redistributed pseudo inverse (RPI) algorithm depends on the choice of the pseudo-inverse matrix. The subset of attainable moments of RPI is a complex non-convex polyhedron. By analyzing two-dimensional and three-dimensional allocation problems with a “micro-element” method, here we propose an approximate calculation algorithm to compute the volume of the non-convex polyhedron. In order to improve the allocation efficiency of RPI, genetic algorithm is used to find the best pseudo-inverse matrix. The simulation results show that the best pseudo-inverse matrix can be easily chosen by the proposed method and the high allocation efficiency is achieved.

Pinning control of general complex dynamical networks with optimization

Abstract: This paper addresses optimal pinning control of general complex dynamical networks. A pinning scheme with linear feedback is proposed to globally exponentially stabilize a network onto a homogeneous state. In particular, we answer an important and fundamental question about pinning control: how to select an optimal combination between the number of pinned nodes and the feedback control gain? Three illustrative examples are provided to show the effectiveness of the proposed technique.

A survey on impulse-radio UWB localization

Abstract: Impulse radio ultra-wideband (IR-UWB) technique has good performance in the application of high-precision localization since it possesses unique properties such as large instantaneous bandwidth and high time resolution. Making IR-UWB localization technology a growing hot topic in recent research field, therefore, it is necessary for us to give an overview of it in this paper. The TOA estimation, error analysis, NLOS identification and NLOS localization are studied in details based on the ranging methods. Simultaneously the UWB localization applications and practical problems are pointed out. At last, we outline the challenges for further research of IR-UWB localization.

Design of robust output-feedback repetitive controller for class of linear systems with uncertainties

Abstract: Repetitive control, which adds a human-like learning capability to a control system, is widely used in many fields This paper deals with the problem of designing a robust repetitive-control system based on output feedback for a class of plants with time-varying structured uncertainties A continuous-discrete two-dimensional hybrid model is established that accurately describes the features of repetitive control so as to enable independent adjustment of the control and learning actions A sufficient condition for the robust stability of the repetitivecontrol system is given in terms of a linear matrix inequality The condition is then used to obtain the parameters of the repetitive controller Finally, a numerical example demonstrates the effectiveness of the method

Studies and advances on joint source-channel encoding/decoding techniques in flow media communications

Abstract: Joint source-channel coding/decoding (JSCC/JSCD) techniques in flow media communications have become a state-of-the-art and one of the challenging research subjects in the spatial communication area They have great application prospective and deep impact in various manned space flights, satellite missions, mobile radio communications and deep-space explorations In the last few years, there have been influential achievements in JSCC/JSCD studies This paper aims at an introduction to the basic principles of joint source-channel optimal design A general summarization and classification for various existing JSCC/JSCD methods is addressed Also presented is a JSCD scheme based on variable-length coding, capable of providing reliable resolutions for flow media data transmission in spatial communications

Fault prediction model based on evidential reasoning approach

Abstract: In order to deal with fault prediction problems that involve both quantitative and qualitative information for nonlinear complex system, a new fault prediction model is established based on the evidential reasoning (ER) approach, and an optimal learning algorithm for training ER-based prediction model is presented based on the mean square error (MSE) criterion. This prediction model inherits the advantages of ER approach, which can deal with precise data, incomplete data and fuzzy data with nonlinear characteristic. In this model, the input signals transformed using rule based information transformation technique, are aggregated by analytical ER approach, and then the outputs of prediction model are constructed according to the types of system outputs. In addition, two fault decision criteria are defined to conduct fault identification. To overcome the difficulty in determining model parameters accurately and subjectively, a nonlinear optimization model is constructed and the optimal parameters are obtained. Two experimental studies are conducted to evaluate the performance of the proposed model. The results show that the established prediction model and the presented parameters optimization methods can deal with fault prediction problem effectively.

An improved line-of-sight method for visibility analysis in 3D complex landscapes

Abstract: This paper presents an efficient method for implementing visibility analysis on complex landscapes based on an improved LOS (line of sight) algorithm. The method determines the viewshed by analyzing the geometric relationship between the target points and viewpoint. It differentiates the visibility of the target points by the elevation information. Eventually the visual results related to the given viewpoint are rendered on three-dimensional landscapes. The visibility of some target points is computed by comparing their elevations with the viewpoint’s height, thus is able to enhance the efficiency of the visibility analysis. This method can not only be applied in the visibility analysis of forest scenes, but also used in the analysis of the urban environment. Experiments show that the proposed method results in high efficiency and precision.

The discrete multiple-parameter fractional Fourier transform

Abstract: As a generalization of the Fourier transform (FT), the fractional Fourier transform (FRFT) has many applications in the areas of optics, signal processing, information security, etc. Therefore, the efficient discrete computational method is the vital fundament for the application of the fractional Fourier transform. The multiple-parameter fractional Fourier transform (MPFRFT) is a generalized fractional Fourier transform, which not only includes FRFT as special cases, but also provides a unified framework for the study of FRFT. In this paper, we present in detail the discretization method of the MPFRFT and define the discrete multiple-parameter fractional Fourier transform (DMPFRFT). Then, we utilize the tensor product to define two-dimensional multiple-parameter fractional Fourier transform (2D-MPFRFT) and the corresponding two-dimensional discrete multiple-parameter fractional Fourier transform (2D-DMPFRFT). Finally, as an application, a novel image encryption method based on 2D-DMPFRFT is proposed. Numerical simulations are performed to demonstrate that the proposed method is reliable and more robust to blind decryption than several existing methods.

A mathematical model for concept granular computing systems

Abstract: Extent-intent and intent-extent operators are introduced between two complete lattices in this paper and a mathematical model for concept granular computing system is established. We proved that the set of all concepts in this system is a lattice with the greatest element and the least element. This framework includes formal concept lattices from formal contexts, L fuzzy concept lattices from L fuzzy formal contexts and three kinds of variable threshold concept lattices, i.e. the extension and the intension of a concept are a crisp set and a crisp set, a crisp set and a fuzzy set, a fuzzy set and a crisp set, respectively. Finally, some iterative algorithms for constructing concepts are proposed and they are proved to be optimal concepts under some conditions in this system.

Analysis of microwave brightness temperature of lunar surface and inversion of regolith layer thickness: Primary results of Chang-E 1 multi-channel radiometer observation

Abstract: In China’s first lunar exploration project, Chang-E 1 (CE-1), a multi-channel microwave radiometer was aboard the satellite, with the purpose of measuring microwave brightness temperature from lunar surface and surveying the global distribution of lunar regolith layer thickness. In this paper, the primary 621 tracks of swath data measured by Chang-E 1 microwave radiometer from November 2007 to February 2008 are collected and analyzed. Using nearest neighbor interpolation based on the sun incidence angle in observations, global distributions of microwave brightness temperature from lunar surface at lunar daytime and nighttime are constructed. Using the three-layer model (the top dust-soil, regolith and underlying rock media) for microwave thermal emission of lunar surface, the measurements of brightness temperature and dependence upon latitude, frequency and FeO+TiO2 content, etc. are discussed. On the basis of the ground measurements at Apollo landing sites, the observed brightness temperature at these locations are validated and calibrated by numerical three-layer modeling. Using the empirical dependence of physical temperature upon the latitude verified by the measurements at Apollo landing sites, the global distribution of regolith layer thickness is then inverted from the brightness temperature data of CE-1 at 3 GHz channel. Those inversions at Apollo landing sites are compared with the Apollo in situ measurements. Finally, the statistical property of regolith thickness distribution is analyzed and discussed.

Advanced information feedback strategy in intelligent two-route traffic flow systems

Abstract: The optimal information feedback has a significant effect on many socioeconomic systems like stock market and traffic systems aiming to make full use of resources. In this paper, we study dynamics of traffic flow with real-time information. The influence of a feedback strategy named vehicle number feedback strategy (VNFS) is introduced, in which we only calculate the vehicle number of first 500 route sites from the entrance. Moreover, the two-route traffic system has only one entrance and one exit, which is different from those in the previous work. Our model incorporates the effects of adaptability into the cellular automaton models of traffic flow, and simulation results by adopting this optimal information feedback strategy have demonstrated higher efficiency in controlling spatial distribution of traffic patterns than the other three information feedback strategies, i.e., TTFS, MVFS and CCFS.