47 results about "Power iteration" patented technology

A system and method for predicting victims and detecting fake accounts in OSNs, comprising: a feature-based classifier for predicting victims by classifying, with a classification probability, a target variable of each user in the OSN social graph; a graph-transformer for transforming the social graph into a defense graph by reassigning edge weights to incorporate victim predictions using the classification probability, a graph-based detector for detecting fake users by computing through the power iteration method a probability of a random walk to land on each node in the defense graph after 0(log n) steps, assigning to each node a rank value equal to a node's landing probability normalized by the node degree, sorting the nodes by their rank value and estimating a detection threshold such that each node whose rank value is smaller than the detection threshold is flagged as representing a fake account.

A system and method for detecting fake accounts in OSNs is proposed to aid the OSN provider 20 against fake users, wherein a social graph G of the OSN, with n nodes, a non-Sybil region GH and a Sybil region GS, is obtained and the following steps are performed:a trust value T(i)(v) is computed through i power iterations on each node v of the social graph G, i=0, 1, . . . O(log n)the power iterations distribute the trust value T(i)(v) from each node v to its neighbour nodes,after O(log n) power iterations, ranking nodes by a degree-normalized trustT^v=T(w)(v)deg(v)in order to obtain a ranked list of nodes,detecting fake accounts based on the obtained ranked listassigning intervals in the ranked list to a fake portion, determined by manual inspection means of the OSN provider, based on the degree-normalized trust of the nodes belonging to the intervals.

An iterative mantissa calculator calculates a quotient mantissa for a divide mode or a result mantissa for a square-root mode. The calculator includes at least first and second summing devices. In the divide mode, each summing device calculates a respective estimated partial remainder W[j+1] for the next iteration, j+1, as 2*W[j]−Sj+1*D, where W[j] is the estimated partial remainder for the current iteration calculated during the prior iteration, Sj+1 is the quotient bit estimated for the next iteration, and D is the respective divisor bit. The estimated quotient bit for the next iteration is selected based on the calculated partial remainder. In the square-root mode, the first summing device calculates 2W[j]−2S[j]Sj+1, where W[j] is the estimated partial remainder and Sj+1 is the estimated result generated during the current iteration, j. A shift register shifts the value of the estimated result, Sj+1, to generate −Sj+12·2−(j+1), which is summed with the result from the first summing device to generate the estimated partial remainder for the square root mode.

A method and system for beamforming communication in high throughput wireless communications. Analog beamforming involves constructing analog beamforming coefficients for beamforming communication on a wireless channel. Constructing analog beamforming coefficients includes selecting a signal tap from a multi-tap wireless channel for beamforming communication, wherein the selected signal tap has a higher signal quality relative to other signals taps, and determining beamforming coefficients for the selected tap by iterative acquisition of the coefficients based on power iteration.

Producing multiple independent fields from many phased acoustic transducers represents a difficult computational problem. By first dividing up each field to its own group of transducers and then treating each group as an element with adjustable phase, one can minimize the field-to-field interference through a power iteration solution. These solutions can be further refined by including tracking information from users in the space and how they shadow or reflect the acoustic fields.

A method surpresses clutter in a space-time adaptive processing system. The method achieves low-complexity computation via two steps. First, the method utilizes an improved fast approximated power iteration method to compress the data into a much smaller subspace. To further reduce the computational complexity, a progressive singular value decomposition (SVD) approach is employed to update the inverse of the covariance matrix of the compressed data. As a result, the proposed low-complexity STAP procedure can achieve near-optimal performance with order-of-magnitude computational complexity reduction as compared to the conventional STAP procedure.

The invention belongs to the technical field of wireless communication, and particularly relates to a method for reducing antenna training overhead of iterative beam forming by utilizing inter-channel sparsity in a wireless multiple input multiple output (MIMO) communication system. The invention provides an iterative beam forming method of a millimeter wave precoding system, and is used for overcoming the defect of high antenna training overhead of a power iteration method of a large-scale MIMO system. According to the method, the spatial sparsity of a millimeter wave channel is utilized, and the estimation problem of receiving vectors of millimeter wave MIMO antenna training is converted into a sparse reconstruction problem so that the loss is reduced by utilizing the correlation theory of compression perception.

The invention relates to a fast convergence decoding algorithm for LDPC codes, which belongs to the field of communication technology. The fast convergence decoding algorithm is characterized in that external information becomes more and more reliable during the iteration process, namely external information of LDPC codes for two successive iterations represents the changing directions of LLR values of variable nodes, and properly increasing external information in the prior iteration can effectively accelerate the iterative convergence speed, therefore, the algorithm can obtain the decoding speed which is faster than the decoding method of standard lamination minimal sum, and meanwhile, the algorithm can also be spread to disk storage systems.

The invention provides a resource allocation and interference suppression method based on non-cooperative game in an LTE system. First, a multi-cell LTE network interference model is established by adoption of soft frequency reuse, and then, a utility function based on the price mechanism is established through consideration on users' demand for quality of service and energy consumption based on the non-cooperative game theory, a power iteration algorithm maximizing the utility function is given, and resource allocation and interference suppression can be realized through iterative solution. Joint interference management and resource allocation in a multi-user multi-cell multi-carrier LTE system can be realized. Through ICI suppression and inter-cell signal interference noise ratio balancing, inter-cell interference is reduced while energy is saved. The throughput and the network coverage of cell edge users in the system can be effectively improved under the condition of without increasing additional power consumption. Only pricing information exchange is needed between the cells, and distributed implementation is easy in actual systems. Therefore, the resource allocation and interference suppression method of the invention has good application prospect.

The invention belongs to the technical field of wireless communications, particularly relates to a method for reducing iterative beam forming antenna training expenses through a channel space sparse characteristic in a wireless multiple input multiple output (MIMO) communication system, and provides an iterative beam forming method based on the channel space sparse characteristic. The method comprises the steps that sparse modeling is carried out through a geometric model of a sparse multipath channel; initialization is carried out; beam forming vector quantity training is received; the beam forming vector quantity training is sent. The space sparse characteristic of the millimeter wave channel is utilized, the estimating problem of vector quantity receiving in millimeter wave MIMO antenna training is converted into a sparse rebuilding problem, and therefore correlation theories of compressed sensing are utilized, and the expense of a power iteration method is further lowered by 50-60 percent with quite low performance losses.

The invention discloses a block chain transaction network node importance ranking method. The method comprises the steps that A, a transaction network topological graph is generated; B, background nodes are added; C, edges from non-background nodes to the background nodes are added; D, edges from the background nodes to all the non-background nodes are added; E, a probability transfer matrix is generated, and an initial importance score is given to each node; F, power iteration is performed on the probability transfer matrix H; G, whether convergence is performed is judged, if yes, the step His executed, and if not, the step F is returned to and executed; and H, the background nodes are deleted, and the importance scores of the remaining nodes are obtained. By the adoption of the method,the importance ranking result of the block chain transaction network nodes can better conform to the nature of a block chain transaction network, and the fairness and credibility of importance rankings of the block chain transaction network nodes can be improved.

The invention discloses a multi-relay-selection and power distribution method based on the system interrupt probability. The multi-relay-selection and power distribution method based on system interrupt probability is specific to an amplification forward (AF) cooperative communication network under the condition that the power of each user and the total power are limited, and treats the minimization of the system interrupt probability as the target. A sequencing idea is introduced, the qualities of relays are sequenced according to contribution factors of the system interrupt probability from each relay nodes, exhaustible search is effectively avoided, and the frequency of power distribution is reduced through a simple power iteration method. The multi-relay-selection method is quite similar to an optimal power distribution exhaustible traversal scheme in performance, and compared with the optimal power distribution exhaustible traversal scheme in which each possibly existing relay set adopts optimal power distribution, the complexity of the multi-relay-selection and power distribution method based on the system interrupt probability is largely reduced.

The invention discloses a graph regularization sparse coding-based magnetic resonance super-undersampled K data imaging method which comprises the following steps: (a) performing graph regularization sparse coding expression on a double-layer Bergman iteration frame to obtain an image sparse model; (b) updating a learning dictionary and a sparse coefficient on the inner-layer iteration of double-layer Bergman iteration by introducing an auxiliary variable and an alternate solving technology; (c) performing image updating on the outer-layer iteration of the double-layer Bergman iteration to obtain an imaging result by utilizing a part of super-undersampled K data as constraints. According to the method, a proximity graph is established to code local structural data and dig geometric data constraints thereof by introducing adaptive dictionary learning into graph regularization sparse coding, so that image data can be sparsely expressed better; in addition, an image with more complex local geometric characteristics can be processed, a local image structure can be effectively captured, more image details can be recovered, and an obtained image result is higher in fidelity.

A system and method for detecting fake accounts in OSNs is proposed to aid the OSN provider 20 against fake users, wherein a social graph G of the OSN, with n nodes, a non-Sybil region GH and a Sybil region GS, is obtained and the following steps are performed:a trust value T(i)(v) is computed through i power iterations on each node v of the social graph G, i=0, 1, . . . O(log n)the power iterations distribute the trust value T(i)(v) from each node v to its neighbor nodes,after O(log n) power iterations, ranking nodes by a degree-normalized trustT^v=T(w)⁡(v)deg⁡(v)in order to obtain a ranked list of nodes,detecting fake accounts based on the obtained ranked listassigning intervals in the ranked list to a fake portion, determined by manual inspection means of the OSN provider, based on the degree-normalized trust of the nodes belonging to the intervals.

The invention discloses a heterogeneous cellular network energy efficiency optimization method based on independent sets, and belongs to the technical field of wireless communication. The method comprises the following steps that firstly, a transmission power initial value is given for each user, and independent sets of sub-channel users are determined based on a macro cell, a family base station user transmission power and sub-channel characteristics; secondly, a candidate matching scheme of the sub-channels and the independent sets is built, and a partial optimal sub-channel distribution scheme is determined based on sub-channel combined energy efficiency optimization; thirdly, a sub-channel matching scheme is given, user transmission power iteration and sub-channel matching updating are executed; fourthly, the above steps are repeated until a convergence condition is met, and a family base station user sub-channel and power combined optimization distribution scheme is obtained. The heterogeneous cellular network energy efficiency optimization method based on the independent sets can effectively guarantee the QoS requirement of heterogeneous cellular network macro users and family base station users, achieve spectrum resource sharing, and improve the spectrum utilization rate and network comprehensive performance.

The invention relates to the technical field of digital signal processing, and provides a rapid signal subspace estimation method, which comprises the following steps of: obtaining an initial observed signal of a receiving antenna array element according to an observed data model; constructing new observed data, and iterating the new observed data; constructing a conversion matrix according to an iteration result; and obtaining a column vector of the conversion matrix. In the method provided by the invention, a plurality of stages of Wiener filtering forward iteration are performed on a data level to obtain the conversion matrix for a forward iteration process, and the conversion matrix is further computed rapidly by utilizing the unitary properties of a Householder matrix, thereby obtaining a group of standard base vectors of a signal subspace; and the Householder conversion of the plurality of stages for Wiener filtering forward iteration so as not only to further reduce computational complexity, but also to ensure the numerical robustness of an algorithm under finite accuracy.

The invention belongs to the technical field of wireless communications, and particularly relates to a method for reducing antenna training overhead of iterative beam forming by using sparsity among channels in a wireless multiple input multiple output (MIMO) communication system. The invention provides an iterative beam forming method based on compressed sensing. According to the method, the estimation problem of a reception vector in millimeter-wave MIMO antenna training is transformed into a sparse reconstruction problem by using the spatial sparsity of millimeter-wave channels, so that the overhead of a power iteration method is further reduced by 50-60% with tiny performance loss using the relevant theory of compressed sensing.

The invention belongs to the technical field of wireless communication, and particularly relates to a method for rapidly obtaining a plurality of beamforming singular vectors at the same time by performing iteration through the channel reciprocity of a time division duplex system in a wireless multiple input multiple output (MIMO) communication system. The invention provides a rapid iteration antenna training method based on an LANCZOS algorithm. The convergence speed of an LANCZOS method is higher than that of a power iteration method, and a plurality of pairs of receiving-transmitting end beamforming singular vectors of multi-stream beamforming can be obtained by only one stage of iteration, so that the overhead of an antenna training stage is reduced exponentially, and antenna training is finished rapidly. The method has great practical significance.

The invention provides a communication optimization method and system for dynamic Monte Carlo parallel simulation. The method comprises the steps of constructing a communication data structure; constructing a graph topology structure of a neighbor process; starting an out-of-process iteration; selecting a sub-region from multiple sub-regions according to a preset order; conducting data communication between a current selected sub-region of a process and the neighbor process through a constructed communication data structure; ending the iteration. The invention further provides the communication optimization system for the dynamic Monte Carlo parallel simulation. According to the technical scheme, the graph topology structure of the process is constructed, a neighbor set communication function is adopted to replace an original point-to-point communication function, so that the complexity of communication time is reduced; through the optimization of program processes, an optimal sub-region iterative order is selected, partial communication operation in two adjacent consecutive iterations are merged, and therefore partial communication redundant data are reduced, the synchronization waiting time between the processes is shortened, and the load is more balanced.

The embodiment of the invention provides an offshore unmanned aerial vehicle communication coverage optimization method and system, and the method comprises the steps: dividing a target sea area corresponding to an unmanned aerial vehicle into a plurality of areas, wherein each area comprises the same number of user terminals; performing power iteration on any region based on a non-orthogonal multiple access technology to enable the reachable data communication rates of the user terminals to be equal so as to obtain an optimal fair user rate in any region; and based on the optimal fair user rate, allocating the signal transceiving power of the unmanned aerial vehicle in each region to enable the reachable data communication rates of all user terminals in the target sea area to be equal. Under the condition of traditional average power distribution, the fairness problem in the NOMA system is more obvious than that in an OMA system (an orthogonal multiple access system), the fairness problem is effectively solved through a new power distribution scheme, and the communication quality of a far-end user with a poorer channel is effectively improved.

The embodiments of the invention provide a wireless energy transmission method and system. The method comprises: acquiring uplink pilot information sent by a terminal, and estimating downlink channel information according to the uplink pilot information; calculating an initial pre-coding combination coefficient based on large-scale channel fading information, a reference transmitting power value and the number of antennas; calculating an initial Lagrange multiplier based on the large-scale channel fading information, the initial pre-coding combination coefficient and a preset pre-coding combination coefficient formula; broadcasting the initial Lagrange multiplier to other base stations, and receiving initial Lagrange multipliers sent by the other base stations and corresponding to the other base stations one by one; adjusting the transmitting power based on the Lagrange multiplier array and a power iteration formula; on the basis of the adjusted transmitting power, calculating a pre-coding combination coefficient after the transmitting power is updated, then calculating an energy code for pre-coding the energy to be transmitted, and transmitting the pre-coded energy to the terminal. The method and the system improve the energy transmission efficiency of multiple energy sources.

A radar beam forming method based on the power iteration generalized Rayleigh quotient algorithm is implemented through the following steps: 1. setting echo signals of a radar receiving array; 2. calculating a sampling covariance matrix; 3. carrying out eigenvalue decomposition on the sampling covariance matrix; 4. calculating the optimal principal eigenvector of a radar beam former; 5. calculating a weight vector of the radar beam former; 6. judging whether a ratio between the weight vector of the radar beam former during the current iteration and the weight vector of the radar beam former during the previous iteration satisfies a designated condition or not, obtaining the optimal weight of the radar beam former and carrying out Step 7 if the ratio satisfies the designated condition, andcarrying out Step 4 if the ratio does not satisfy the designated condition; and 7. forming radar beams. The method provided by the invention has the advantages that the calculation amount and the calculation complexity can be greatly reduced, so that quick achievement of radar beam forming can be facilitated; and interferences and noises can be effectively inhibited, so that the method can be usedfor the radar beam forming under the condition of steering vector mismatch during radar signal processing.

The invention discloses a power iteration hybrid beam forming method based on beam selection, which comprises the following steps: firstly, selecting a group of best beam forming vectors from a codebook to form an analog domain beam forming matrix of a transmitting and receiving end by the transmitting and receiving end through carrying out beam phase control on a training sequence; and then basedon a power iteration mode, continuously iteratively updating the randomly generated initial digital domain beamforming matrix by utilizing the reciprocity of the obtained analog domain beamforming matrix and the channel, so that the initial digital domain beamforming matrix tends to be optimal. According to the method, the advantages of a beam selection method and a power iteration method are integrated, meanwhile, respective defects are overcome, the implementation complexity of hybrid beam forming is reduced, and the beam forming performance of a wireless communication system is improved.

The invention relates to a method and a system for detecting an abnormal account of an online social network. The method comprises the steps of generating a simple graph according to a user relationship data set of an online social network; calculating the importance of each node through a node importance evaluation algorithm according to the simple graph, wherein the importance of the nodes comprises the in-degree centrality, the near centrality and the intermediary centrality of the nodes; fusing the importance of each node to obtain an importance fusion value of each node; taking the importance fusion value of each node as the weight of the corresponding node, and converting the simple graph into a weighted graph; combining the weight and the out-degree of each node in the weighted graph to carry out power iteration of trust seed transmission, and endowing each node in the weighted graph with a corresponding trust value; and determining the account corresponding to the node with thesmaller trust value in the weighted graph as an abnormal account. According to the invention, the accuracy of abnormal account detection can be improved.

The invention relates to a fast convergence decoding method for LDPC codes, which belongs to the field of communication technology. The fast convergence decoding method is characterized in that external information becomes more and more reliable during the iteration process, namely external information of LDPC codes for two successive iterations represents the changing directions of LLR values of variable nodes, and properly increasing external information in the prior iteration can effectively accelerate the iterative convergence speed, therefore, the method can obtain the decoding speed which is faster than the decoding method of standard lamination minimal sum, and meanwhile, the method can also be spread to disk storage systems.

The invention belongs to the technical field of wireless ranging and positioning, specifically discloses a vehicle ranging method based on hybrid correlation reception and error iteration. The methodmainly comprises five steps: A. performing an autocorrelation calculation on a received signal of an IEEE802.11p protocol, performing a fixed window sliding calculation on the result and then meaning,wherein the result is Mc; B. making a short preamble as a template signal and performing a cross-correlation calculation between the template signal and a frequency shift correction signal of the received signal, and then correlating with the autocorrelation result Mc; C. grouping the hybrid correlation results, wherein each group has 9 samples with interval 16, and summing respectively to obtaina time delay estimation sequence Sopt; D. calculating the mean absolute error madG of all samples before the Sopt maximum in the summation sequence, if not satisfies with madG[1]>0.9 and madG[10]<0.01, setting Sopt[PeakIndex] to 0 to continue the loop iteration, and otherwise, returning the subscript PeakIndex corresponding to the Sopt maximum value; and E. calculating the distance according to PeakIndex. The vehicle ranging method based on the hybrid correlation reception and the error iteration can improve the accuracy of the vehicle ranging in environments with multipath, non-direct view and high Doppler frequency shift.

The invention discloses a power line communication signal denoising method based on a power iteration ICA algorithm. The power line communication signal denoising method specifically comprises the following steps of 1, collecting original mixed signals of a power line; step 2, preprocessing the mixed signal in the step 1 to enable the mixed signal to be close to the basic assumption of ICA (Independent Component Analysis); 3, selecting a proper ICA unmixing mode, and solving a power iteration formula; carrying out power iteration ICA decomposition on the mixed signal preprocessed in the step 2 to obtain two groups of independent demixing signals; and step 4, recognizing the two groups of decomposed unmixing signals, comparing preset thresholds, judging to obtain a communication signal and a noise signal, and completing signal-noise recognition. According to the power line communication signal de-noising method based on the power iteration ICA algorithm, the power iteration ICA algorithm is used for executing signal de-mixing, noise suppression is achieved, high efficiency and accuracy of communication are met, and the real-time performance and communication quality of a power line communication system are better improved.

The invention discloses a large-scale MIMO low-complexity hybrid precoding method and system, and belongs to the technical field of wireless communication precoding, and the method comprises the steps: carrying out the initialization of related parameters, and completing the design process of hybrid precoding through an extended power iteration method; and obtaining a pre-coding matrix by using an EPI algorithm, and generating a signal to be sent. The parameter initialization comprises setting the number MN of transmitting antennas, the number K of user antennas and a channel transmission matrix H; first N maximum singular values and feature vectors of the channel matrix are acquired by using an EPI algorithm; a hybrid precoding matrix is obtained by using the feature vector; and finally, a to-be-sent signal is generated by using the hybrid precoding matrix, and the transmission rate and the operation complexity of the hybrid precoding are calculated and compared. Compared with a theoretical value, the method has the advantages of faster convergence, lower complexity and lower cost.