- EI核心期刊
A new approach with entropy inspection in wavelet domain is proposed for estimation of the variance of Gaussian noise in images. With advantage of wavelet transform, the entropy of image signal degrades notably with the Gaussian noise entropy unchanging. It denotes that the noise entropy value varies with the noise levels in manner of logarithm. The relation between the entropy values of the noisy image wavelet coefficients and the noise levels is traversed in quantitative form. A formula is given to depict this functional relation. Experiment indicates that such a relation is robust to images. A noise estimation is thus made with the entropy inspection of the noisy image in wavelet domain and the established formula as apriori knowledge. Meanwhile, a simulation shows that the proposed approach can achieve more exact value while little influenced by image details.
An automatic image annotation method based on weighted feature is proposed. Firstly, a weighted feature clustering algorithm is employed on the semantic concept clusters of the image regions. For a given cluster, we determine relevant features based on their statistical distribution and assign greater weights to relevant features as compared to less relevant features．In this way the computing of clustering algorithm can avoid dominated by trivial relevant or irrelevant features. Then, the relationship between clustering regions and semantic concepts is established according to the labeled images in the training set. Under the condition of the new unlabeled image regions, we calculate the conditional probability of each semantic keyword and annotate the new images with maximal conditional probability. Experiments on the Corel image set show the effectiveness of the new algorithm.
A lattice reduction (LR) aided precoding mechanism is proposed for the closedloop multiple input multiple output (MIMO) systems. At the receiver, the channel matrix is quantified by the LR operation and sent back to the transmitter for precoding. This mechanism achieves full receive diversity gain, and furthermore, it results that different subchannels of the equivalent channel matrix are of similar performance, it enables the same modulation and coding scheme for different data streams. Simulation shows that the proposed mechanism has better throughput performance than the existing precoding scheme with the same size of codebook, and the gain is up to 28% when signal to noise ratio (SNR) is 16dB.
Two cases are included in the minimum sensor deployment problems, according to whether the deployed network is desired connected or not. The nonconnected case is studied, to minimize the deployment cost. The proposed problem is formulated as an integer linear program problem, which is proved to be an NPcomplete problem. To approximately derive the optimal solution, the candidate deployment regions are theoretically derived and computed. A greedy algorithm is proposed, where one sensor is iteratively deployed into the maximal coverage number candidate region until all targets are covered. Compared with existing genetic algorithm and the optimal solution, simulation results confirm the effectiveness of the proposed algorithm.
A roleextended by key based on rolebased access control (KRBAC) for encrypted data which integrates the hierarchical keys into the role management is proposed. The traditional role is extended here to a triple through dividing the independent control domain of the key, which consists of the role as well as the control domain of role and key, with partially ordered set relations and security constraints. In addition, an elementlevel finegrained data protection is proposed based on the above model. Analysis shows that the working mode of extendedrole can reduce the number of roles and the complexity of access control and improve the rationality of distribution of privileges, besides, it can provide security infrastructure for the finegrained data protection.
For the characteristics of the vector geospatial data, the construction of the digital watermarking model for the vector geospatial data is proposed based on the magnitude and phase of discrete Fourier transform (DFT). The vector geospatial data is transformed into the DFT domain. The watermark is embedded in the magnitude and phase of the DFT coefficient range, then the watermarked coefficients is performed an inverse DFT (IDFT) and get the embedded vector geospatial data. Experiment shows that the model can assure the data accuracy. It will be robust for the translation, deleting a certain ration vertices at random, rotation, format transformation and scale etc.
A new automated coverage optimization scheme (ACOS) is proposed, which can be used to optimize wireless down link coverage in various kinds of radio access networks. ACOS can work well without manual intervention. Records in measurement report of mobile stations are used to estimate condition of wireless down link coverage and generate accommodation scheme. When transmitting, cells power will be adjusted according to accommodation scheme, optimization is done. Simulations show that, in both weak coverage and excessive coverage situation, the quality of wireless down link coverage is improved by ACOS; the indicators of coverage can achieve objective reference value.
In wireless multiple access relay networks, network coded relay can help two users transmit messages in the same time frequency resource without interference. Base station recovers the origin messages utilizing joint detection, and the achievable rate increases. In multiplerelay scenario, proper relay selection methods can further improve the overall throughput. Since relay selection is a complex optimization problem, to reduce the complexity, the network is modeled as a weighted bipartite graph and relay selection problem turns into the maximum weight matching problem. The Kuhn and Munkres (KM) algorithm and the greedy algorithm are utilized to solve the relay selection for multiaccess network, and Monte Carlo. Simulations show that the KM algorithm achieves a bit higher ergodic capacity than that of greedy algorithm.
In wireless sensor network, a novel network coding scheme based on sociality was proposed. Firstly, the design process was described in details and the advantages and shortcoming of the scheme was discussed as well. Then, the process of coding and decoding with random linear codes was expounded. Finally, the simulation using NS2 showed that this scheme is better than the traditional network coding scheme in improving the overall network performance.
The calculation method of monostatic radar cross section (RCS) is analyzed based on method of moment. When calculation of RCS is started by looping over angles, only the right voltage matrix is effected with the changes of the incidence wave. The left impedance matrix is not changed. Based on the characteristic, a new fast calculation method of monostatic RCS using Gauss elimination method is proposed. The elimination procedure is recorded when the monostatic RCS of the first angle is calculated, and the impedance matrix is transferred into product factors matrix. When the monostatic RCS of the other angles are calculated, only the right voltage matrix is calculated follow the elimination procedure of the first angle, thus the monostatic RCS calculating speed of the whole scale angels will be quickened greatly.
A resource allocation algorithm that maximizes proportional fairness factor is proposed in the orthogonal frequency division multiple access based amplifyandforward beamforming relay systems. Based on the convex optimization, the algorithm jointly optimizes power allocation, subcarrier pairing, relay selection and user selection. Both analysis and simulation indicate that the proposed algorithm can achieve fairness of resource allocation and employ beamforming effectively to enhance the system capacity with low computational complexity.
A proactive decodeandforward opportunistic relay protocol with multiinterference at the relays and the destination is proposed. The maximum ratio combining scheme is deployed at the destination where direct link is considered. And the outage probabilities over the independent nonidentical Rayleigh fading channels is derived with multiinterference affected relay and destination nodes. MonteCarlo simulations are requested to verify the analysis. Furthermore, it is concluded that relay selection protocols considering the multiple interference nodes are much better than the schemes without considering the interference. The proposed protocols can reduce the effect of interference on the system.
To solve the web service selection problem with hybrid quality of service（QoS） and lots of service composition plans, a hybrid qosclustering web services composition algorithm (CHQoS_WSCA) based on multiattribute decision making theory is presented. Not only CHQoS_WSCA takes all possible QoS expression types (real numbers, interval numbers, triangular fuzzy numbers and intuitionistic fuzzy numbers) into consideration, it also can effectively solve the service selection algorithm performance problem with largescale composition plans.
In current communications, error probability estimation mainly relies on Monte Carlo simulation. A method based on the radius of decision region to estimate the word error rate (WER) is presented. The Bernoulli experiment samples is replaced with the samples of radius, that can reduce the required number of samples due to the more information provided by radii. Meanwhile, the geometry of decision region is of little to do with the signal to noise ratio (SNR), so the same group of radii can be used to estimate the different error probability at any SNR without repeated measure in different groups of radii under every SNR.
A new denoising algorithm based on pulse coupled neural network (PCNN) system and local Wiener filter is presented. The mechanism of synchronous pulse of PCNN is employed to revise the image wavelet coefficients, according to the feather of different image pixels. Also, an adaptive linking coefficient β is proposed. Based on the improved wavelet coefficients, the local Wiener filter is used to estimate signal variance better. Experiments show the proposed scheme can get higher peak signaltonoise ratio than NeighShrink and Wiener algorithm, and better vision effect.
In wireless networks including IEEE 802.11 networks, it is known that the node mobility leads to extensive shortduration communication. To achieve the timebound fairness between the meeting flows and keep relatively high network throughput, the optimal packet size to obtain the optimal link throughput in the errorprone channel is analyzed. The channel bit error rate and flow contending time is given. The timebound fairness problem of two meeting flows is addressed using the packet size adjustment. Finally, the optimal packet size is concluded. Simulations show that during the short meeting term, the channel contention fairness of the meeting flows can be ensured and the network throughput is kept relatively high when using the proposed optimal packet size.
The channel state vector is sparse under the conditions of low spectral efficiency. Based on compressed sensing technology, a low complexity collaborative spectrum sensing method is proposed to reduce the redundancy of each user in the cognitive radio networks. The processing speed and the efficiency of the single cognitive node are improved through the sparse measurement matrix. The fusion center reconstructs the observed data by the iterative algorithm of factor graph, dramatically reducing the computation. According to the frequency usage, the cognitive nodes adjust the sampling rate adaptively to ensure the maximum efficiency in the whole networks.
Fast control channel selection algorithm for cognitive radio is proposed. Firstly, the delay caused by signal transmitting and processing is utilized to achieve fast control information exchange. Secondly, the process of spectrumhole selection is optimized, that will decrease the number of the spectrum holes used for control channel. Finally, the control channel interruption, caused by the reappearance of primary users on spectrum hole, is significantly avoided. Derivations and simulations prove the increase of the performance on the above mentioned aspects.
An adaptive channel hopping algorithm that can be used in wireless mesh sensor networks is designed. The nodes themselves select proper channels independently and use them to communicate with its neighbors automatically. Once a pair of nodes find their current channel had been deteriorated, they abandoned the current channel and choose reserved channels at once, so the reliability of the network is improved. The algorithm makes use of multichannels efficiently. It is concluded that the algorithm is practicable in the network with moderate density and the topology is relatively static.
A variable structural multimodel method is propose based on a duallayered grid (DLGVSMM) for state estimation of hybrid system. The total model set of DLGVSMM is composed of a basic grid. The structure of the new method can be adaptively tuned and an amendatory model grid C which can move freely in the space of system mode. Firstly, the likely model set technique is used to adjust the topology structure of the M. Then, the central position of C produced by the adaptive grid approach is further used to produce the adaptive amendatory model grid C. Finally, the total estimation can be obtained by optimal information fusion. Simulations demonstrate that the proposed DLGVSMM wiil improve the tracking performance at a limited extra computational cost.
An algorithm is designed to recognize satellites in the sky based on phase difference of a series of images in frequency domain. It is complicated and difficult to recognize the satellites merely through stars’ characteristics because the satellites traced are always surrounded by a large number of stars. One frame image in a series of images is compensated and compared with its adjacent frame. From the comparison, the odd object can be recognized by the character of Fourier phase difference. Then frame subtraction method is used to eliminate fake objects. Finally the movement of tracing object is described. Meanwhile an improved algorithm of image binarization based on twodimension histogram is designed to strength its antinoise ability. At the end the experiment shows that the error between this algorithm recognition and human capture is less than one pixel.
In order to shorten the idle time in offline scheduling, a modified hybrid online & offline with Shortest propogation delay first based (HSPD) scheduling is proposed. Due to the round trip time (RTT) influence on the upstream idle time, a scheduling condition parameter is defined to further classify online and offline status based on the diversity of the propogation delay. The network performance is evaluated through analysis and simulation. Results indicate that HSPD scheduling achieves better performance compared with the MDBA1 algorithm and SPD first based offline scheduling especially under light or medium loaded traffic.
Timing synchronization schemes for orthogonal frequency division multiplexing （OFDM）based power line communication system is discussed. Based on the traditional method, a new algorithm is proposed to attenuate the interference over multipath channel. Matlab simulation proves that the proposed approach can improve the system performance over multipath channel. It also has fewer hardware consumptions and lower complexity.
An energyefficient data gathering protocol based on zones and tree is proposed. The correlated zones are constructed based on the correlation difference among the sensing data. The data inside each correlated zone is aggregated and its transmission rate is adjusted. Then a data gathering tree is built based on nodes’ residual energy and distance in betweens. Simulations show that the proposed protocol outperforms existing data gathering protocols in terms of energy consumption and network lifetime.
It is analyzed that efficient certificateless strong proxy signature scheme is proven insecure against the public key replacement attack. The adversary can not only forge valid proxy delegation by substituting the public keys of the original signer, but it can also forge the proxy signatures of the proxy signer by substituting the public keys of the original signer and the proxy signer. An improved scheme is presented to resist against these attacks.
A new downlink spatial coordination scheme is proposed for orthogonal frequency division multiple access (OFDMA) systems to mitigate intersector interference, in which the minimum mean square error (MMSE) precoding is utilized to improve the performance of edge users at neighbor sector. The design of precoding matrix is simplified by separating the objective functions that maximizes expected signal power and minimizes interference leakage in different resource groups. System level simulation demonstrates that the proposed scheme can significantly alleviate intersector interference, while maintain sector average throughput. The superiority is distinct even when imperfect CSIT is caused by limited codebook and increased feedback granularity.
A linear equation system for designing hybrid filter banks (HFB) is presented on the basis of solving the coefficients of the synthesis filter banks derived from the perfect reconstruction (PR) conditions. The relationtions between the PR conditions and each different solution situations are discussed regarding the consistent and inconsistent equation case. The general solution and the lower bound of the reconstruction error are given. A second order cone programming based methodology for designing PRHFB is proposed to get the unique solution with the constrains of minimizing the stopband energy of the synthesis filter banks, which can also be used to calculate the minimum norm solution of the equation. Simulations show that this approach can get the unique solution and satisfy the system PR conditions effectively.
In order to detect distributed denial of service (DDoS) attack effectively, a new method is described. Firstly, HilbertHuang transform (HHT) is introduced into the process of network traffic signal to obtain corresponding marginal spectrum. Then its Hurst parameter is calculated. Next, the detection threshold is determined by means of training Hurst parameters of marginal spectrums of experimental data with the goal of seeking the maximum composite index. Finally it can be judged whether DDoS attack happened or not through comparison with above threshold. Experimental results verified the feasibility of this method.