94 results about "Linear complexity" patented technology

The invention relates to the communications field and provides parallel encoding device and a method for a low density parity-check code (LDPC). By adopting the practice of step-by-step encoding combined with the serial-parallel approach, a concatenated encoding scheme with linear complexity combining with pre-encoding and parallel convolution coding structures is provided thereby. The encoding device for realizing the encoding scheme mainly comprises an information storage unit, a pre-encoding unit and an encoding unit (comprising a data distribution unit and a convolution coding unit) as well as a v (0) verification bit generating unit. The encoding device of the invention adopts a circular shift register and a model 2 adder, which is easy to realize and avoid multiplication operation of vector and matrix. Complexity of the encoding device is reduced. The encoding device provided by the invention features good expansibility. A plurality of basic encoders are used for parallel encoding so that encoding efficiency can be improved by many times compared with the single basic encoding device. Therefore, when hardware complexity permits, parallel structures can be applied as much as possible, which greatly improves encoding efficiency.

The invention discloses an implementation method and an implementation system for resisting quantum computation attack based on CPK public key system. The implementation method comprises the steps of: adopting a method of changing computational complexity into linear complexity, adopting a method of providing incomplete discrimination condition, turning quantum computation into meaningless infinite-solution or multiple-solution equation. The implementation system comprises a public key generation module, a digital signature module, and a secret key transference module. According to the invention, the generation and distribution of a secret key are integrated, therefore complexity of secret key management is simplified substantially; and the system safety is ensured by carrying out a generation process of a public key inside an E2ROM chip. No external support is needed in the signature and encryption operation of CPK, thereby improving the operating efficiency greatly.

A method for automatically reconstructing topographical information for a given mesh, altering the mesh by introducing, deleting, or splitting existing polygons when needed. An OctTree space decomposition is used to achieve a log2-complexity search method to find the closest vertex in the polygonal soup to a given point in space. Linear complexities are used to find triangles connected to a given vertex and all triangles connected to a given triangle. The triangles are split to enforce conductivity.

This invention relates to a method for extracting a core content of a webpage based on text-tag density. The method comprises four steps of preprocessing webpage source code, estimating the range of the core content of the webpage, determining the boundary of the core content and deleting residual tags. In the step of preprocessing webpage source code, extract core elements of title, summary, description, and so on from an original webpage text, and delete the tags unrelated to the core content of the webpage in the original webpage text so as to acquire a pending text. In the step of estimating the range of the core content of the webpage, determine a general range of the core content of the webpage. In the step of determining the boundary of the core content, separately determine precise start and stop positions of the core content of the webpage text. In the step of deleting residual tags, take out the core content part and delete residual tags to acquire the core content of the webpage, which is convenient to be analyzed and processed. By adoption of this method, the DOM (Document Object Model) structure of a webpage document is unnecessary to be analyzed; the theme and the content of the webpage are not limited; the processing procedure has linear complexity; and this method is applicable to the technical applications of extracting the core contents of various kinds of webpages, denoising webpages, and so on.

The invention provides a method and a system of computer aided translation, which utilize the aided translation information as intermediate information, the user memory bank and the dictionary in computer translation so as to correct and improve the computer automatic translation result based on the computer translation result, wherein by adopting the candidate phrase querying method based on the AC automation, the candidate phrase query problem is solved within linear complicity, and the efficiency of aided translation is greatly improved; the sorting problem of the phrases of different sets is solved by adopting the candidate phrase sorting method based on Kalman filter, and the weight of the candidate phrase sets is continuously optimized by analyzing the translation history of the user, so as to improve the precision in recommending the candidate phrases.

The invention discloses a method and a system for simulating an on-chip power supply network. The method comprises the following steps: step 1, reading in an SPICE (simulation program with integrated circuit emphasis) netlist; step 2, establishing a power supply network topological diagram; step 3, establishing a matrix equation Ax=b, wherein A is an electric conduction matrix of n*n, x is a knot voltage vector to be solved of the power supply network, b is current and n is number of thin grid points; and step 4, solving a roughened operator by utilizing a grid point dual polymerization algorithm, and solving the matrix equation by utilizing the roughened operator. The invention provides a static simulation project for the power supply network, and the simulation project is more stable and efficient, and less in occupied memory, and has linear complexity, under the condition that the solving precision appointed by the user is satisfied, the project can achieve an analysis of a knot voltage drop of the power supply network in an appointed form of the SPICE net list in a way that the operation time is reduced and the memory is used as little as possible.

The present invention relates to a method and a system for creating three-dimensional models of objects from sets of arbitrary three-dimensional entities obtained from target surfaces. It also provides an efficient method for individually refining the alignment of curves to improve the accuracy of the surface model with a linear complexity with respect to the number of curves. The principle behind the invention is that a set of three-dimensional entities, at their approximate positions, creates a field from which the surface can be extracted. The field is constructed in a manner such that the three-dimensional entities are attracted toward the extracted surface. This attraction is used to accurately register each three-dimensional entity with respect to extracted surface. Through iterations, both the field and the entity positions are refined.

The present invention discloses an adaptive guided filtering-based digital vein image enhancement method. Based on the defects of an original guided filter, a novel local adaptive weighted guided filtering method is put forward based on an edge detection operator under a condition that the linear complexity of the guided filter is not changed. The quality of an image enhanced by using the method provided by the invention is better than the quality of an image enhanced by using a guided filtering-based enhancement method in three objective image quality indicators, namely, contrast, sharpness and local structure similarity. As indicated by a recognition experiment, the method of the invention is also advantageous in recognition rate. Thus, the effectiveness of the adaptive guided filtering-based digital vein image enhancement method is fully embodied.

The invention discloses a Gibbs sampling-based ultra-dense heterogeneous network optimal cell range expansion bias adjustment method. The method includes the following steps that: inter-cell bias influence relation diagram is constructed; small cells are grouped based on the bias influence relation diagram; a user judges candidate service cells; user number, signal to interference plus noise power and effectiveness update information are interacted between adjacent cells; and cell range expansion bias sampling is carried out based on Gibbs sampling. With the method adopted, ultra-dense heterogeneous network optimal cell range expansion bias, with optimizing any rate related system effectiveness adopted as a target, can be obtained with linear complexity and minimal iterations.

A method of channel encoding and channel decoding in a multiple access communication system wherein the channel decoding requirements increase linearly and not exponentially as the number of users increase. A channel encoder converts alphabetic symbols into a preselected geometric representation of a hexagonal lattice known as a symbol constellation. A channel decoder converts the received symbol constellation into a replication of the alphabetic symbols. Each user has a specially defined symbol set that allows the linear-complexity decoding operation.

A method to achieve full diversity without sacrificing bandwidth and with a linear complexity in a wireless system includes the steps of orthogonally transmitting a plurality of signals utilizing multiple antennas using a corresponding plurality of precoders in a plurality of time slots, which precoders are designed using the channel information to cancel interference among the plurality of signals while achieving a maximum possible diversity of NM with low complexity for at least two users each having N transmit antennas and one receiver with M receive antennas, separating the signals in the receiver using the orthogonality of the transmitted signals, and decoding the signals independently to provide full diversity to the at least two users.

The invention provides a nonlinear pseudorandom sequence generator, comprising a shift register unit and a feedback logic unit. The feedback logic unit comprises a linear feedback logic unit, a nonlinear feedback logic unit and a synthetic unit. The input end of the linear feedback logic unit is correspondingly connected with the state output end of the shift register unit according to own primitive trinomial feedback function, while the output end thereof is connected with one input end of the synthetic unit; the input end of the nonlinear feedback logic unit is correspondingly connected with the state output end of the shift register unit according to own nonlinear characteristic function, while the output end thereof is connected with another input end of the synthetic unit; and the synthetic unit comprises an exclusive-OR gate, the input end of the synthetic unit is respectively connected with the output end of the linear feedback logic unit and the output end of the nonlinear feedback logic unit, and the output end of the synthetic unit is connected with the input end of the shift register. The pseudorandom sequence generated by the generator has high linear complexity and long cycle, and the generation method is simple.

The invention discloses a safe frequency hopping sequence construction method based on evolution codes. The method includes the following steps of synchronously changing carrier frequency through a group of pseudorandom sequences by communication receiving and sending sides to conduct information transferring, naming pseudo-code sequences which control carrier frequency hopping as frequency hopping sequences, adopting an evolution DES grouping encryption algorithm by the frequency hopping sequences, serving address codes of a user as encryption secret keys, conducting encrypting on TOD information of the user to obtain a ciphertext, selecting n codes from the encrypted ciphertext to serve as frequency hopping codes, and therefore, constructing the frequency hopping sequences. The frequency hopping sequences constructed by the method are superior to those of the existing technical scheme in uniformity, correlation and linear complexity. In the method, an evolution data encryption algorithm is introduced to conduct encryption operation to construct the frequency hopping sequences, so that the frequency hopping sequences are high in safety and hardly intercepted by an aggressor.

The invention relates to a stock index prediction method based on adaptive feature extraction, and the method comprises the steps: S1, obtaining stock index data, and obtaining the daily opening price, lowest price, highest price, closing price and transaction volume; s2, calculating an artificial index value proposed by a financial and economic expert; s3, constructing sample features and samplelabels, and dividing all samples into a training set, a verification set and a test set; s4, performing adaptive feature extraction on the sample; and S5, inputting self-adaptive extraction features and the artificial indexes calculated in the S2 into a neural network prediction model based on a factor machine, and outputting a prediction result. According to the method, the characteristics of thestock indexes are extracted in a self-adaptive manner, and the extraction method is simple and high in interpretability; the neural network based on the factor machine is used as a prediction model,interaction between features can be learned, the nonlinear expression capability is achieved, and the linear complexity is achieved; the accuracy of the stock index prediction technology can be effectively improved.

The invention discloses a complexity analysis method of non-linear EEG signals. Permutation entropy and sample entropy algorithms are greatly applied to the non-linear complexity analysis, but certain defects exist. The sample entropy is good in robustness and accuracy, but the calculation efficiency is not satisfactory; and the permutation entropy is rapid in calculation, but the calculation is not as accurate as that of the sample entropy. Aiming at the above problem, the method for the non-linear complexity analysis of the EEG signals includes: firstly performing filtering processing on the EEG signals, extracting effective frequency bands, ranking the frequency bands, performing equal-dividing symbolization assignment according to two rules, and finally respectively performing m dimensional and m+1 dimensional phase space construction for entropy calculation. According to the method, compared with the previous non-linear method, the accuracy of the permutation entropy is improved, and the calculation efficiency is improved for the sample entropy method.

The invention relates to a spreading code cross-correlation optimization method of a satellite navigation system based on a greedy algorithm, and belongs to the technical field of satellite navigation. According to the method, the maximum value of odd and even cross-correlation function absolute values of two code words serves as the performance measure, and a cross-correlation measure matrix and a spreading code word index array are built; then the greedy algorithm is adopted to delete one spreading code word in a candidate code word set, and an obtained new matrix is utilized for updating the cross-correlation measure matrix. Code words in the candidate code word set are deleted by iteration until the optimal number of the code words is reached, a final spreading code word index array is obtained, and spreading codes of the corresponding serial numbers are extracted from the candidate code word set and serve as optimization results to be output. Compared with a conventional traversal search method, the spreading code cross-correlation optimization method has the advantages that the calculation complexity is decreased from the index complexity to the linear complexity, cross-correlation optimization of the spreading codes can be achieved rapidly, and meanwhile optimization of the spreading codes can be carried out on a greater candidate set.

The invention discloses a linear-complexity Massive MIMO target space orientation estimation method and device. The method comprises that a reception signal of a target is collected by an antenna array; an autocorrelation covariance matrix is generated according to the reception signal; a skeleton is extracted from the autocorrelation covariance matrix to generate a low-rank characteristic matrix;low-rank symmetric approximate decomposition is carried out on the autocorrelation covariance matrix based on the low-rank characteristic matrix to generate a low-rank symmetric approximate decomposition matrix; a singular value of the low-rank symmetric approximate decomposition matrix is decomposed, signal sub-space approximate estimation of the reception signal is obtained according to a decomposition result, and a MUSIC spectrum is calculated according to the signal sub-space approximate estimation; and the space orientation of the target is calculated according to a peak value position of the MUSIC spectrum. The random matrix sampling and low-rank approximate decomposition methods are used to avoid direct SVD of the high-dimensional autocorrelation matrix, the computing complexity inthe method is reduced greatly, and the problem of limitation in radar target detection and signal processing in the large-scale antenna scene is solved.

The invention relates to an ALD device scanning algorithm under the unreliable communication environment. An identical scanning frame is sent repeatedly according to the algorithm so that the possibility of scanning missing can be reduced to an acceptable degree. The algorithm comprises the following step of causing a system to send the scanning frame; detecting a conflict response; determining the matching conditions of an electrically-controlled antenna device in a network and a scanning frame matching code according to the result of detecting the conflict response; and performing corresponding process according to the matching conditions. The algorithm has linear complexity, can effectively improve scanning recognition rate, basically can solve the problem of scanning missing, is good in applicability and can quickly accurately scan ALD devices such as a RCU and a TMA produced by different factories.

The invention discloses a generating method for chaotic cipher in limited precise. The steps are: (1) initialization: generates in random or sets the initial value x1[i] (i=0; l=1, 2... n,) of the chaotic system, and sets with K kinds of variable carrying rules, k is equal or less than n; (2) the chaotic system output x j[i] (j=1, 2... n) correspondent to the carrying rule can be acquired with the K kinds of variable carrying rules according to the input xl [i]; (3) the outputs of different carrying rule x j [i] are converted into value with the same carrying rule x' j [i]; (4) the x' j[i] is coded according to the set coding rule and acquires x'' j[i]; (5) the n chaotic coding series x'' j [i] are arranged into M xi= M xi (I, j)=x'' j[i], xi=1, 2, ...; (6) xl [i+1]=x j[i] according to the set rule; (7) I=i+1, returns to the step (2), till the task is completed. The invention can reduce the correlation of series, increases the linear complexity, thus the chaotic series may has excellent performance.

The invention discloses a channel state information quantification method. The method includes the following steps that: a 3D channel is decomposed into two sub channels; CSI (channel state information) quantification is carried out on the two sub channels respectively based on a Kronecker product codebook according to the equivalence of incoherent sequence receiving and CSI quantification; and code words obtained after the quantification of the two sub channels are multiplied, so that a final CSI quantification result can be obtained. According to the quantification method of the invention, FD-MIMO channel information quantification is converted into the receiving problem of two incoherent sequences with parallel linear complexity according to the equivalence relation of incoherent sequence receiving and channel information quantification and the decomposability feature of the Kronecker product codebook, and therefore, quantification complexity can be greatly decreased.

The invention provides an information extraction method based on transmission and distribution statistics and validity evaluation on the basis of intrinsic characteristics of a social network. The method includes the steps of carrying out initial qualitative evaluation on information distribution according to information source tools and establishing valid quadratic characteristics based on user information in the process of validity processing to carry out quantitative evaluation. In the process of calculation, a linear complexity algorithm is used for carrying out analysis, the demand for computing resources is low, and time cost and space cost are low. In the process of association, comparison processing is carried out, and MicroBlog information which is really high in exposure rate is output at last. The information extraction method has higher practical value in reality, effectively achieves analysis on influence and exposure rates of public opinion information of the social network and can filter out low-quality data and reserve true and valid information for use in follow-up manual analysis.

The invention provides a training sequence based OFDM integer-multiple frequency offset quick estimation method and system. The training sequence based OFDM integer-multiple frequency offset quick estimation method comprises a transmitting-end signal processing method and a receiving-end signal processing method, wherein the receiving-end signal processing method comprises the steps of conducting FFT transformation on input signals, performing grouped summation operation and then sequentially performing integral-multiple frequency offset estimation and integral-multiple frequency offset compensation. On the basis of OFDM system receiving end timing estimation and a frequency offset estimation algorithm and starting with a whole OFDM receiving access demodulation algorithm, the integer-multiple frequency offset estimation algorithm is optimized, and the shortcomings of long capture time and high resource consumption of a traditional serial correlator are overcome. The capture time and the resource consumption are remarkably reduced, and meanwhile the requirements for quick capture and low resource consumption are met. The training sequence based OFDM integer-multiple frequency offset quick estimation method has linear complexity O(N) and is easily achieved through FPGA hardware.