- EI核心期刊
Pilot design schemes and their corresponding channel estimation methods for orthogonal frequency division multiplexing(OFDM)system based on compressed sensing theory are studied. With the channel sparse impulse response and slow varying character, a joint sparse model (JSM) for the channel estimation in OFDM system is proposed. With such joint sparse model, the channel estimations of continuous OFDM symbol periods are converted into a sparse vectors recovery problem with joint sparse model, which improves the estimation performance. Different channel estimation methods for shortwave OFDM system are compared. Simulation shows that the proposed compressed sensing based channel estimation scheme brings out better performance compared with conventional least square channel estimation method and symbol-by-symbol compressed sensing channel estimation method. Simulation also shows that the proposed method has better estimation performance under time-variant channel.
A cellular differential evolution (cDE)algorithm based on orthogonal crossover is presented. The opposition-based learning initialization is used to search better solution in the initial stage, the local search within cellular neighbourhood structure is presented to tune the selection pressure instead of the control parameters. And the parallel evolution mechanism of cellular automata is given to ensure the diversity of the evolution population. In addition, the orthogonal crossover is adopted to accelerate the convergence speed with multi-element repeated trials. The performance of the cDE algorithm is evaluated on a suite of classic benchmark functions and compared favorably with the canonical DE and several DE variants. Simulation shows the proposed algorithm has better convergence performance and higher calculation accuracy.
One of the goals of optical imaging and image processing is super-resolution imaging. In order to reduce the registration error and costly problem facing in multiple sub-pixel image registration fusion method to achieve super-resolution, a compressive sensing method is introduced for super-resolution imaging, it benefits from the general sparse representation feature of most nature images. Based on the classical 4-f optical architecture, the phase will contain more information than the amplitude in frequency domain, a compressed imaging method with pure phase modulation in the frequency domain is proposed. The original high-resolution image information can be recovered from the low-dimensional measurements recorded with a single exposure by various algorithms. Numerical results demonstrate that the proposed can effectively achieve random modulation of image information and high-quality reconstruction, which can be considered as a promising scheme for physics implementation of compressed imaging with high reconstruction signal to noise ratio and less reconstruction time, especially for large-scale image.
A new recommendation method based on manifold ranking and social matrix factorization is proposed, in which the social similarities among users are calculated by means of manifold ranking, the objective function of ratings matrix factorization is constructed via the regularization technique, with the differences among users' preferences as the penalty of objective function, the social similarities are infused into the low-rank matrix factorization. Experiments show that this method achieves higher precisions and lower root mean square error/mean absolute error (RMSE/MAE) value than other that of cognate methods.
Additional items of sensitivity of objective and constraint functions are generated through analyzing the corresponding functions objective functions and constraints. Two models of optimization design for reliability are proposed based on the additional items of sensitivity. According to the limitations of information for objective functions obtained from different evaluators, the objective functions and the evaluators' assessment based on gray system theory was allocated in a certain range. The expert assessment method is presented to calculate the weight coefficients of the objective functions. Reliability-based robust optimization design of cylindrical helix spring is achieved by using the optimization toolbox and symbolic toolbox of Matlab. Numerical examples prove that the proposed approach which provided the theoretic basis for the reliability design of the mechanical elements has a higher precision and reliability.
In order to improve the perception ability of multimedia processing, a transcale interpolation model is proposed for the dynamic image sequences. Firstly, the visual attention regions are obtained by utilizing visual saliency detection from the viewpoint of users, so as to determine the outstanding regions of dynamic image sequences. Secondly, coherency sensitive hashing is adopted and high quality interpolation frames are generated when the time scale is changed. Finally, the energy function of the target images is defined, so the quality of visual attention regions could be improved when the resolution scale is changed. Experiments show that the proposed model achieves better interpolation results.
To improve the timeliness of detecting topics in retrospective topic detection, an improved locality sensitive Hashing (LSH) algorithm is proposed and applied in constructing hierarchical topic model for web news. Firstly, the news content feature is excavated, and the topic feature is excavated using latent dirichlet allocation model. Then the non-binary content eigenvector and topic eigenvector are converted to binary feature space. Finally, news articles are clustered in order using binary content eigenvector and binary topic eigenvector by LSH, and the hierarchical topic-content news topic model is generated. Experiments prove the following results: extracting content feature and topic feature can express the news exactly; converting content eigenvector and topic eigenvector to unified binary space can reduce the time complexity of clustering, and thus increase the efficiency of topic detection while ensure the accuracy and semantic expansibility.
It is common that the topic-granularity of social tags is not consistent with correspondent document, and some tags cannot describe the topic of the document content. The existing topic models-based tag recommendation did not address the foregoing problems simultaneously as well. Motivated by the fact, the proposed novel topic model allows different granularity of word topics and tag topics, and assumes that the tags can originate from a general distribution unrelated to the content. Experimental results show that the proposed model outperforms content relevance model (CRM) and tag- logical device address (tag-LDA) on two different social tagging corpora in both perplexity and mean average precision.
The maximum likelihood detection algorithm for multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) system is difficult to realize in hardware and the performance of traditional channel estimation is poor, in order to solve these problems, a joint estimation detection algorithm is proposed. To revise estimated channel using the discrete Fourier transform-least square algorithm for channel estimation and the space alternating generalized expectation maximization algorithm, the iterative signal detection is realized by combining the improved particle swarm optimization algorithm. Simulations show that the proposed algorithm can estimate the channel state information and detect data as well with less iteration number whose performance is much better than the traditional detection algorithm under the same bit error rate. There is only 1 dB difference between the bit error rate performance and the maximum likelihood detection algorithm under ideal channel.
A forgery attack on Yang bo et al.'s certificate-based signature scheme was presented. It is found that the "honest-but-curious" certificate authority could forge a valid signature in any message on behalf of any user by choosing random parameters without knowing the secret value of the user. Analysis describes that the reason of insecurity of the original scheme is that the commitment value R computed in the stage of certificate generation is not used as an input of the hash function in the stage of signature generation. An improved scheme was proposed by adding R to the hash function. The improved scheme is as efficient as the original scheme. It is provably secure under the intractability of discrete logarithm problem.
A dynamic data delivery algorithm is proposed which is composed by data transmission strategy and queue management mechanism. It can be applied to heterogeneous delay tolerant mobile sensor networks. Firstly judge each node whether it can transmit messages directly to the sink; then calculate the node's forward probability at different time. Thereafter the forward probability is calculated based on energy consumption and transmission delay. Each node forwards message by the right method. Queue management obey different survival time and transmission counts of different nodes. Simulations show that this data algorithm has a better effectiveness.
A detection method was proposed to analyze the malicious behavior on Android, that combines hidden-Markov model (HMM) with support vector machine (SVM) for modeling as well as construct model for behaviors like networking and data accessing. This model takes advantage of both HMM and SVM and overcomes the shortcomings inside, and it is suitable for classification using dynamic behavior sequences. Experiments show that this method can capture the abnormal behaviors with high accuracy rate and lower false positive rate.
As a result of relative stability of social relations between people in opportunistic networks, an interest community detecting method is proposed by quantifying the interests of nodes and comparing the similarity with the interest properties of nodes. Utilizing the communities generated by moving nodes and comprehensively considering the community property of nodes and the contact information among nodes, an interest community routing (ICR) scheme is presented. The ICR scheme is divided into two parts: routing within the community and routing among communities. The nodes which in the same community and contact more frequently with the destination node will be chosen as relay nodes. Simulations demonstrate the rationality and effectiveness of ICR, and shows that ICR can efficiently reduce the average overhead ratio and decrease delivery delay and increase the delivery ratio.
Current semantic cache consistent maintenance strategy is difficult to adapt to frequent mobility, hand off and disconnect network environments. The article propose a new semantic cache scheme using mobile agent technology to maintain the cache consistency. Firstly, mobile agents MSSAg and MTAg are designed based on SMC-architecture. Secondly, the process of maintain cache consistency is discussed in two cases: without hand-off and with hand-off. Experiments show that the proposed cache maintenance method could reduce cache consistency restore time and save data communication cost effectively. It is particularly efficient for using in frequent mobility, hand off and disconnect network environments.
Random competition (RC) scheduling algorithm is proposed. This algorithm is applied to joint scheduling between cells edge users of different adjacent areas, which belongs to the category of collaborative scheduling algorithm. In addition, collaborative scheduling scheme based on random competition for the edge of relay-enhanced cell is proposed based on this algorithm. In order to avoid co-frequency interference and improve the transmission performance of the cell edge areas, we introduce the collaborative relay cluster in the edge of relay-enhanced cell where resource conflicts would appear and apply RC scheduling algorithm among collaborative relay cluster. Simulation results suggest that the proposed method can reduce the users' interference of the adjacent cells, and improve the cell edge throughput. Moreover, the scheduling fairness between cell center and edge can be enhanced.
3D-Beamforming is a promising technique for mobile wireless communication systems to improve the system performance and realize green communications. By exploring the vertical dimension of the spatial area, 3D-Beamforming could enhance the signal to interference plus noise ratio of the received signal, raise the spectrum utilization rate and improve the energy efficiency. The fundamental theory of array antenna's 3D-Beamforming is studied. The half-power beam width (HPBW)of the beam at vertical dimension has been computed by Matlab simulation under influence of different factor. Simulation shows that horizontal angular does not affect the basic level of HPBW, with the increase of vertical angular, the HPBW increase significantly, but it can be decreased by adding more antenna array unit.
To solve the problem of access control among different security domains in networks, an access control model is presented based on role and trust degree. Each role associates with a trust value, the role evaluation weights are defined in terms of user's role rank and the trust degree is calculated according to the role evaluation weights and role behavior. Direct trust degree, recommendation trust degree and feedback trust degree are introduced in this model to achieve fine-grained access control. The three trust degrees mentioned above participate in the comprehensive trust degree evaluation by adjusting their weights. Simulation is conducted in local area network environment in which a web system is used to construct an access control model with multi-domain. Experiment demonstrates that the model is of higher security, expansibility and flexibility.
In order to improve the efficiency of the proxy signature scheme based on lattice, the authors use the lattice signature, without trapdoors and transmission technology with matrix, with small norm to construct a proxy signature scheme. The transmission technology with matrix with small norm is also used to control the dimension of proxy signature secret key such that its dimension is smaller than that of original signature secret key. Its security is based on the hardness of small integer solution problem. Compared with other results over lattice, the size of proxy signature secret key and proxy signature is reduced.
A buffer insertion method of a rapid timing optimization under process variation is proposed. The method carries out graph transformation on wire net in routing area, and so the random problem becomes a deterministic problem i.e. the buffer insertion problem for reducing time delay will be equivalent to statistics the shortest path problem. Moreover, we propose a valid node storage algorithm, which is optimized in constructing the graph process, and is greatly improving the memory space and working efficiency. In experiment section, the method is firstly used in 90 nm, 65 nm and 45 nm process global interconnect buffer insertion and analysis, and the insertion results are consistent with reference result, which confirms the validity of this method. Meanwhile, the algorithm was applied to two kinds of actual interconnect nets in integrated circuit: simple wire net and tree type wire net, which gets perfect timing optimization results based 17 inserted buffers and 3 inserted buffers respectively.
Current researches on content centric networking routing mainly focus on selecting the best routing path from forwarding information base (FIB). The path leads the requests to the server, so only the on-path caches are currently used, which results in low utilization of the in-network caches. More caches can be exploited if more FIB faces are used for multipath routing, but it will bring a lot of redundancies. To solve these problems, a content trace multi-path routing (CTMR) scheme is proposed. In this scheme, Interest packet is sent to the caches along with the traces of the former Data packet. Therefore, the Interest packets are routed to the in-network cache resources before they routing to the server, the utilization of the in-network caches is increased with a little redundancy, while the server load is decreased. Simulation shows that the CTMR decreases the server load about 10% and reduces the mean hops compared with the existing schemes. The cache hit rate in CTMR is increased about 20% relative to the single path routing. The redundancy in CTMR is reduced by more than 10% with the similar cache hit rate relative to the multipath routing.
Recent subspace clustering research results suffer from two problems: firstly, they typically scale exponentially with the data dimensionality or the subspace dimensionality of clusters. Secondly, present methods are often sensitive to input parameters. To overcome these limitations, a subspace clustering algorithm based on united entropy matrix ( UEM ) is presented. In the method, entropy is used to filter out redundant attributes and UEM is used to store united entropy of each two attributes. This method finds all interesting subspaces in UEM by searching all-one sub matrix. Finally, all subspace clusters can be gotten by clustering on interesting subspaces. The evaluation on both synthesis and real datasets show that our approach outperforms traditional subspace clustering methods and provides enhanced quality for finding subspace clusters with higher dimensions.
Comprehensive information theory and information transition are for research-oriented theory of intelligent, comprehensive information emotional theory and information emotion interaction are for research of human mind. This paper purposed a new mental calculation model-need influence from cognitive-emotional interaction mechanism, established a model of certainty need. The emotional-informational layer combined three-dimensional structure of information (Comprehensive Information Theory), emotions (PAD model) and expected information, According to Siminov's emotional motivation theory, we established information-emotion interaction model, based on the correspondence between basic emotions and PAD, we analyzed the formation and migration of emotional state mechanism, emotional state from surprise to the joy during migration process, the formation of information-emotional needs, the internal mechanism of cognitive and emotional conversion, migration, variation theory system.
The accuracy of perceptual evaluation of speech quality (PESQ) in assessing speech codec in Chinese environment was investigated, an improved algorithm was proposed. Due to the lack of research about PESQ evaluate speech codecs under Chinese environment, an experiment was done based on Chinese speech database to get accuracy of PESQ for evaluate two codecs under Chinese database. And the reason of the experiment result was analyzed. In order to improve the accuracy of PESQ for speech codec, an improved PESQ algorithm was proposed.
On the basis of analyzing electric vehicle power station operation mode and aiming at the dynamic changes of power station requirements, a two-phase mathematic programming model based on power station center is presented for dynamic vehicle routing problem. And a new adaptive genetic algorithm is designed for dynamic vehicle routing problem. Aiming at the real time of dynamic vehicle scheduling problem, the two-phase solution of "initial path stage" and "real-time dynamic scheduling stage" are established, which optimizes sub-routes through continuously updating information and inserting the dynamic needs power stations. Simulation validates the effectiveness of the model and the algorithm.