131 results about "Frequency vector" patented technology

The invention discloses a calculating method of text similarity degree and vocabulary meaning similarity degree and system and application system, which comprises the following steps: basing on vocabulary data bank; proceeding initialize; calculating; getting initial vocabulary meaning similarity degree among vocabulary in the vocabulary data bank; basing on the initial vocabulary meaning similarity degree; calculating initial semantic similarity degree among text; iterating semantic similarity degree among each text and vocabulary meaning similarity degree among vocabulary till constriction; constructuring final vocabulary meaning similar matrix with final vocabulary similarity degree; transforming the text vocabulary frequency vector of the initial text to the new text vocabulary text vocabulary frequency vector; calculating text similarity degree in the text collection. This invention can improve related property of current text especially about short text.

In a data processing system, a method of recommending articles and products to a user is disclosed. The method creates a frequency vector in relation to the content of an article, frequency vectors in relation each of one or more products from intermediate data. The method compares the vectors to determine a content similarity measure, and provides as output a list of one or more products having the highest content similarity measures. The method may also determine a correlation measure. An electronic data processing system for recommending articles and products to a user is also disclosed. The system includes modules to receive article information and product information, a correlation module to determine a content similarity measure between the article and each of the products and, a multiplexer module for providing a list comprising the article and the products associated having the highest content similarity measure.

The invention relates to a multi-document auto-abstracting method facing to inquiry, which comprises the following steps: performing preprocessing on the inquiry and documents; performing topic segmentation and semantic paragraph clustering on the preprocessed documents to obtain subtopics; expressing the inquiry and the sentences in each of the subtopics in the form of a word frequency vector, and calculating the correlation measurement of the inquiry and the subtopics; screening the subtopics according to the correlation measurement of the inquiry and the subtopics, sequencing the subtopics according to the importance of the subtopics, and selecting the front T important subtopics to obtain an ordered sequence of the subtopics correlative with the inquiry; and circularly obtaining representative sentences from the subtopic sequence in turn, and connecting the representative sentences together to generate an abstract. The method uses the topic segmentation technique so that the abstract is in a limited length range and comprises the important information in a document set as much as possible, provides more targeted services, can adjust the content of the abstract according to a user inquiry topic, and can achieve the interactions with users.

The invention discloses an automatic webpage classification method and a system. The method comprises the following steps: S1: searching website webpages related to a client webpage, and capturing titles and variable data information of the webpages therefrom to form a webpage list set; S2: processing characters in the webpage list set to form a classification keyword list set; S3: statistically gathering the frequency of occurrence of classification keywords in the classification keyword list set on the webpage to enable each webpage to correspond to one classification keyword frequency vector; and S4: establishing a statistical model, calculating the classification keyword frequency vector distance between each target webpage and the client webpage to obtain the correlation degree between each target webpage and the client webpage, and automatically classifying the target webpage on the basis of the correlation degree. The invention can automatically find the optimum webpage based on unbiased estimation and thereby a great amount of high-quality potential webpage can be recommended to clients for link exchange.

A displacement measurement method for achieving, at each position of interest, high accuracy measurement of a displacement, a velocity and a strain in an actually generated beam direction by measuring the beam direction angle from ultrasound echo data. The method includes the steps of: generating an ultrasound echo data frame through scanning an object in a lateral direction with an ultrasound steered beam having one steering angle; calculating both a beam direction and a frequency in the beam direction based on an azimuth angle φ=tan−1(fy / fx), a polar angle θ=cos−1[fz / (fx2+fy2+fz2)1 / 2], and a frequency (fx2+fy2+fz2)1 / 2 in the case where first spectral moments calculated from local ultrasound echo data at plural different temporal phases are expressed by a three-dimensional frequency vector (fx, fy, fz); and calculating a displacement component in the beam direction at each position of interest generated between plural different temporal phases.

The invention discloses a method and a system for orthogonal modulation of power signals. The method comprises the following steps: acquiring an initial sequence length and an initial sequence according to a frequency lower limit, a preset sampling frequency and an initially set integer signal cycle number of a power signal; acquiring a reference frequency according to the initial sequence, and further acquiring a unit cycle sequence length and a preset sequence length; acquiring first forward and reverse sequences according to a preset sequence starting point and the preset sequence length; generating first real-frequency and imaginary-frequency vector sequences and second real-frequency and imaginary-frequency vector sequences according to the first forward and reverse sequences; converting obtained first and second phases into a first forward sequence average initial phase; obtaining a new preset sequence starting point according to the average initial phase; and obtaining a cosine function modulation sequence and a sine function modulation sequence according to second forward and reverse sequences obtained from the initial sequence. By adopting the method and the system of the invention, an orthogonal modulation sequence with consistent amplitude height can be obtained, and the accuracy and anti-jamming performance of sinusoidal parameter calculation are improved.

A streaming text data comparator performs real-time text data mining on streaming text data. The comparator receives a streaming text data document and generates a vector representation of the term frequencies relating to an existing document collection. The comparator then transforms the term frequency vector into a projection in a precomputed multidimensional subspace that represents the original document collection. The comparator further calculates a relationship value representing the similarities or differences between the vector representation and the subspace, and compares the relationship value to a predetermined threshold to determine whether the streaming text data document is related to the original document collection. If the streaming text data document is related, the streaming text data comparator intercalates the new document into the document collection. If the new document is not related, the comparator may store or delete the unrelated document.

The invention provides a method of automatically discovering a hot news theme (or a hot event) on the internet, which can automatically discover various news events on the internet and automatically and briefly explain the events. The method comprises the following steps: downloading webpages of recent news, blogs, microblogs and the like from the internet; extracting titles and texts from the news, blogs, microblogs and the like; carrying out word segmentation for the extracted titles and texts to acquire a word frequency vector, and combining all the texts to acquire a word frequency matrix; carrying out cluster analysis for the word frequency matrix with clustering algorithm so that texts with the same theme are gathered and clusters of various themes are acquired; and extracting a title of a central text and keywords from each cluster to explain the cluster, i.e., to explain the news theme.

Moiré free color halftoning is achieved through the use of two dot screens and one or two line screens. The line screens may be, for example hybrid line screens. Frequency vectors associated with the screens combine to produce moiré frequency vectors representing moiré frequencies above or below the visual range. In one embodiment lines screens are used to halftone yellow and black separations and dot screens are used to halftone cyan and magenta separations. The dot screens are oriented at 15 and 75 degrees. The line screens are oriented at 45 and 135 degrees. Selected screens and screen orientations minimize screen interaction with mechanical or optical artifacts of a rendering device, thereby minimizing mechanical and optical moiré.

Disclosed herein is a method and apparatus for moiré-free enhanced color halftone printing of color image separations for an arbitrary number of colorants. The method and apparatus utilizes a plurality of halftone screens, >4, to produce outputs that are moiré free and form hexagonal periodic rosettes. The relatively large number of screens can be used for enhanced printing applications, such as printing with high-fidelity colorants, light colorants, or special colorants, such as white, metallics and fluorescents. The method and apparatus provide for defining rosette fundamental frequency vectors VR1, VR2 that satisfy a length and sum requirement to meet visual acceptability standards according to |VR1|>fmin, |VR2|>fmin, and |VR1±VR2|>fmin; defining N halftone screens for colorants i=1, N, respectively possessing first and second frequency vectors (Vi1, Vi2), where no two screens possess identical fundamental frequency vector pairs; and selecting fundamental frequency vectors for the N halftone screens according to (Vi1, Vi2)=(mi1VR1+mi2VR2, ni1VR1+ni2VR2) for integer m's and n's, where at least one fundamental frequency vector or its conjugate must also satisfy one of the following: Vik=VR1, Vik=VR2, and |Vik>2 max [|VR1|, |VR2|].

The invention relates to a method for detecting Android malicious software in batch, comprising the following steps: A, respectively extracting and calculating a system permissions characteristic, a process control flow chart characteristic of an application program and frequency vectors of a system call characteristic, and combining and splicing the frequency vectors to form comprehensive characteristic vectors; B, using sorting algorithms in the data mining to classify the comprehensive characteristic vectors; C, calculating contribution values of electric quantity record to malicious software detection and intent record to malicious software detection; D, carrying out weighting calculation to the numerical value of classification result and contribution values of electric quantity record and intent record to malicious software detection, judging as the malicious software if the calculating result exceeds a set threshold value, otherwise judging as normal software. The invention has the following advantages: the method and device of the invention can be used for mixing system permissions, a system call and a program control flow chart to form a new feature vector, and detecting the malicious software by using the sorting algorithms with high accuracy and little omission.

The embodiment of the invention discloses a channel estimation method and device, relates to the technical field of communication, and helps to reduce indication overhead. The method can comprise thesteps that indication information is generated and sent, the indication information is used for indicating M N-dimensional precoding vectors, each precoding vector is applied to one frequency band inthe M frequency bands, the M N-dimensional precoding vectors form a space frequency matrix, and the space frequency matrix is generated by weighting and combining a plurality of space frequency component matrixes, the space-frequency matrix is an M * N-dimensional space-frequency vector or an X * Y space-frequency matrix, X and Y are respectively one and the other of M and N, the M is greater thanor equal to 1, the N is greater than or equal to 2, and the M and N are integers.

A method and system for estimating color separation misregistration of a printing system. The method may include marking a substrate to form a misregistration estimation patch. The misregistration estimation patch being formed by first and second color separations. The first color separation marking the substrate with a first halftone pattern. The first halftone pattern has a first halftone-frequency vector in a first direction and a second halftone-frequency vector in a second direction. The second color separation marking the substrate with a second halftone pattern. The second halftone pattern has a first halftone-frequency vector in a first direction and a second halftone-frequency vector in a second direction. The first and second halftone patterns form a moiré pattern. A deviation in at least one the halftone frequency vectors and / or the moiré pattern can be indicative of a color separation misregistration. The method also includes estimating the color separation misregistration of the printing system using the misregistration estimation patch.

The invention discloses a method for identifying a place image on the basis of an improved probabilistic topic model, belonging to the technical field of image identification. The method provided by the invention can be used for well solving the problems that the image identification is uncertain due to different angles, illumination, and height dynamic changes of figures and objects. The method comprises the following steps: an image acquiring step, an image preprocessing step, a feature extraction step, a feature clustering step, a feature distribution step and a potential topic modeling step, wherein in the image acquiring step, the features of the image are extracted by adopting a SIFI (scale invariant feature transform) algorithm; in the feature clustering step, all the features are clustered so as to obtain a plurality of clustering centers; in the feature distribution step, the feature of each image is voted in the clustering center so as to obtain a frequency vector corresponding to each clustering center; in the potential topic modeling step, the potential topic distribution of the image is learned by adopting the improved probabilistic topic model; and a classifier is adopted to identify the images at unknown places. According to the invention, a quantization function is added in an LDA (latent dirichlet allocation) model, and the potential topic of the image is learned through the improved probabilistic topic model, so that the identification performance is effectively improved on the premise of guaranteeing instantaneity.

Disclosed are a method and system for video compression, wherein the video encoder has low computational complexity and high compression efficiency. The disclosed system comprises a video encoder and a video decoder, wherein the method for encoding includes the steps of converting a source frame into a space-frequency representation; estimating conditional statistics of at least one vector of space-frequency coefficients; estimating encoding rates based on the said conditional statistics; and applying Slepian-Wolf codes with the said computed encoding rates. The preferred method for decoding includes the steps of; generating a side-information vector of frequency coefficients based on previously decoded source data, encoder statistics, and previous reconstructions of the source frequency vector; and performing Slepian-Wolf decoding of at least one source frequency vector based on the generated side-information, the Slepian-Wolf code bits and the encoder statistics.

The invention proposes a target motion parameter estimation method for a random frequency hopping radar, and solves the problem that the existing speed measurement scheme has a long accumulation time,a large calculation amount and a poor anti-noise performance. The method comprises the main steps of: designing a waveform parameter for transmitting a random frequency hopping signal and receiving atarget echo; preprocessing digital signals; preprocessing the slow time sampling vector; constructing a difference frequency vector group; constructing a Doppler domain generalized Fourier transformmatrix group; carrying out the generalized Doppler transform and non-coherent processing; carrying out motion compensation processing; and carrying out the coherent integration of distance dimensionsand de-redundance processing to obtain a one-dimensional range profile with the correct target in the plurality of range gates. According to the target motion parameter estimation method for the random frequency hopping radar, a set of dimension decreasing difference frequency vectors are constructed from the target echoes, generalized Doppler processing is performed on each difference frequency vector, and an estimated value of the target radial velocity can be read in the generalized Doppler spectrum after non-coherent integration. The method is short in accumulation time, small in calculation amount and good in anti-noise performance, and is used for target detection and pulse accumulation of the random frequency hopping radar.

A method and system for quantizing LSF vectors in a speech coder, wherein predicted LSF values based on previously decoded output values are used to estimate spectral distortion, along with the residual codebook vectors and the LSF coefficients. The method comprises the steps of obtaining a plurality of quantized LSF coefficients from the respective predicted LSF values and the residual codebook vectors; rearranging the quantized LSF coefficients in the frequency domain in an orderly fashion; obtaining the spectral distortion from the rearranged quantized LSF coefficients and the respective LSF coefficients; and an optimal code vector is selected based on the spectral distortion.

The invention discloses a data model dual-drive GFDM receiver and method. The method comprises the steps: respectively obtaining a channel estimation and a signal detection neural network; taking thereal-number result of a matrix comprising transmitted pilot frequency information and a received time domain pilot frequency vector as the input of a channel estimation neural network, and outputtingan estimation of the frequency domain channel state information; obtaining an equivalent channel matrix, taking the real-number result of the equivalent channel matrix and the received time domain signal vector as the input of a signal detection neural network, and outputting the result as the estimation of a GFDM symbol; establishing a demapping neural network, taking an estimation of the GFDM symbol outputted by the signal detection neural network as the input, and outputting the estimation as the estimation of the original bit information; determining the output of the demapping network andthe size of a set threshold, and outputting a detection result of the original bit information according to a determination result. The method has the advantages that the training parameters do not change with the data dimension, the training speed is fast, and the adaptability to different channel environments is strong.

The invention discloses a method for ordering significance of keywords in a text. The method comprises the steps of performing a word segmentation operation in a text firstly, and then removing stop words to obtain a keyword set of the text; then counting word frequencies of the keywords to obtain word frequency vectors corresponding to the keywords; setting punctuation marks with pausing functions as boundary endpoints of a co-occurrence window, counting co-occurrence information between word items to obtain co-occurrence arrays, and obtaining vectors of distribution conditions of co-occurrence of the keywords from the co-occurrence arrays of the keywords; processing the co-occurrence arrays of the keywords to obtain a keyword significance vector which is judged by a keyword co-occurrence relationship; then integrating the vectors of the distribution conditions of co-occurrence of the keywords from the co-occurrence arrays of the keywords with the word frequency vectors of the keywords by the keyword significance vector which is judged by the co-occurrence of the keywords to obtain a comprehensive significance of the keywords in the test; and finally, ordering the keywords according to the significance degree of the keywords obtained by calculating. According to the method, the significance of the keywords in the text is judged by using various types of information; and accuracy and reliability for judging the significance of the keywords in the text can be improved.

The embodiment of the invention provides a webpage tampering detection method and device for improving the webpage tampering detection accuracy and efficiency. The method comprises the steps of obtaining a target malicious word of a text to which a to-be-detected station belongs; retrieving whether the text to which the to-be-detected station belongs is the target malicious word exists or not; if the target malicious word exists, constructing a word frequency vector of the context where the target malicious word is located; inputting the word frequency vector of the context into a preset classifier model to judge whether the context is tampered or not, wherein the classifier model is an original classifier model which is generated according experiment text training.

Disclosed herein is a method and apparatus for moiré-free color halftone printing with up to four color image separations. The method and apparatus utilize a plurality of non-orthogonal halftone screens to produce outputs that are moiré free and form uniform periodic rosettes. The method and apparatus provide for defining a first and a second color halftone screen fundamental frequency vector for each of three halftone screens such that the halftone screen set output forms uniform hexagonal rosettes; then defining a fourth color halftone screen where a first fundamental vector of the fourth screen shares a fundamental frequency vector with one of said three halftone screens and a second fundamental frequency vector of the fourth screen shares a fundamental frequency vector with a different one of said three color halftone screens.

The invention discloses a distributed type in-memory database indexing method oriented to structural data. The method includes the steps of receiving a database operation request; indexing a to-be-operated key value in the database according to the data operation request. Indexes include distributed type indexes and bottom-layer single-machine indexes, the distributed type indexes include data distribution indexes and row distribution indexes, the data distribution indexes are responsible for cross-machine positioning of data and row tables, the bottom-layer single-machine indexes are fine-grained data-level indexes, the single-machine indexes include line compression indexes and row table indexes, the line compression indexes are composed of three vectors including the dictionary, the frequency vector and the row number index, and the row tables are responsible for keeping the mapping of row numbers of all record items to dictionary subscripts where the record items are located. The method has the technical advantages that high-efficiency storage indexing can be achieved, data can be rapidly inquired about through the indexes, the indexes are compressed, and the memory requirement is lowered.

The invention relates to a method for transforming physiological data from the time domain to the frequency domain. The method includes the steps of: providing a plurality of digital data in the time domain; providing a microcomputer programmed to run a recursive Fourier transform estimation algorithm; calculating, for each newly received digital data in the time domain, an integer index using modulo(N) arithmetic based on a time the each newly received data was received; selecting a frequency vector from a plurality of N frequency vectors using the integer index; and updating the plurality of frequency coefficients according to a recursive equation including the selected frequency vector as an input variable. The invention also relates to an apparatus that performs a recursive Fourier transform estimation algorithm to convert data in the time domain to data in the frequency domain.

The invention discloses a knowledge recommendation method and equipment based on similarity. The method comprises the following steps: obtaining one piece of knowledge which comprises a title part and a content part; independently carrying out word segmentation processing on the content part and the title part, determining the weight of each segmented word, and independently determining the characteristic words of the content part and the title part according to the weight; according to the characteristic words of the two parts, determining a characteristic word set of the obtained knowledge; forming a new characteristic word set with the obtained characteristic word set and a characteristic word set of another piece of knowledge stored in a repository, independently determining the frequency of each characteristic word in the two pieces of knowledge in the formed characteristic word set to obtain the word frequency vectors of the two pieces of knowledge; on the basis of the word frequency vectors of the two pieces of knowledge, determining the similarity between the two pieces of knowledge; and under a situation that the similarity is greater than or equal to a threshold value, recommending the other piece of knowledge to the user. Therefore, the accuracy and the authenticity of the similarity can be improved, and the knowledge with the highest similarity is recommended to the user.

The invention discloses a speech coding and decoding method using high-order linear prediction coefficient grouping vector quantization. The method can be applied to a low-bit-rate and high-quality speech codec and can be used to reduce the codebook size and computation load required for high-order line spectrum frequency vector quantization

The invention relates to a video multi-target long-range tracking method. The method comprises the following steps of: step 1, target features of a large number of sample pictures to be tracked are extracted, at first, a M- tree is adopted to represent a feature set of word frequency vectors of feature words of a target sample, and then, video retrieval is adopted to perform M- tree retrieval on targets to be matched, and finally, an affine transformation relationship is adopted to verify retrieval results, and therefore, initial targets can be matched; step 2, a short-range tracker of optical flow tracking is adopted to track and detect the initial targets; step 3, a three-dimensional target model of online learning is adopted to update the targets so as to construct a multi-form multi-perspective target model; and step 4, and short-range tracking and target redetection are combined so as to realize long-range tracking. According to the video multi-target long-range tracking method of the invention, the three-dimensional target model of online learning is adopted, and therefore, problems caused by constantly changing target objects in network video tracking can be solved, and problems existing in detection of targets of which image features change constantly can be solved; and a tracking framework of the short-range tracking and target redetection is adopted, such that long-range racking of targets can be realized. The video multi-target long-range tracking method can be widely used in fields such as network information security and multi-target detection and video multi-target tracking.

The invention discloses a method and device for configuring a full-phase filter bank through the frequency response characteristic. The method comprises the steps of convolving an input signal x(n) through a convolution window, adding every two multiplied data with the interval of N-1 to form N data, rapidly configuring the frequency response characteristic to Q subchannel filter coefficient vectors, obtaining the configured Q subchannel filter coefficient vectors, and carrying out multiply-accumulate on the data to obtain Q filtering output results. The device is characterized in that signals to be filtered are sampled through an analog-to-digital converter to obtain a sample sequence, the sample sequence enters a DSP device in a parallel data input mode, the filter order N, the number p of 0 and the number m of 1 in a frequency vector H are set, and Q filtering output results are obtained through processing of the DSP device. According to the method and device for configuring the full-phase filter bank through the frequency response characteristic, rapid configuration of the locations of sub-bands and the widths of the sub-bands of a filter, a filter coefficient and a frequency response function is achieved, and signal characteristics can be accurately extracted.

A method of estimating an aggregate of a join over data-streams in real-time using skimmed sketches, that only examines each data element once and has a worst case space requirement of O(n2 / J), where J is the size of the join and n is the number of data elements. The skimmed sketch is an atomic sketch, formed as the inner product of the data-stream frequency vector and a random binary variable, from which the frequency values that exceed a predetermined threshold have been skimmed off and placed in a dense frequency vector. The join size is estimated as the sum of the sub-joins of skimmed sketches and dense frequency vectors. The atomic sketches may be arranged in a hash structure so that processing a data element only requires updating a single sketch per hash table. This keeps the per-element overhead logarithmic in the domain and stream sizes.

The invention discloses a method and a device for detecting an answer signal. The method comprises the following steps of: converting an answer signal vector received by an antenna into an equivalent pilot frequency vector; computing noise power and signal power according to the equivalent pilot frequency vector so as to obtain a signal-to-noise ratio; multiplying the signal-to-noise ratio by thesignal power and converting an obtained result into a numeric value represented by a logarithmic format; and judging whether the numeric value is more than or equal to a preset threshold value or notand determining that the answer signal is valid if the numeric value is more than or equal to the preset threshold value. According to the invention, the validness of an acknowledgment (ACK) / negativeacknowledgement (NACK) signal is determined by combining the signal-to-noise ratio of the signal with absolute power. Compared with the conventional detection method, the method of the invention has lower false-alarm probability, so that the stability and throughput of the system can be improved effectively.