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131 results about "Frequency vector" patented technology

As long as time is unknown about being scalar or vector, frequency stays in waiting list too. If we look closer, it is number of waves emitted per second. It has dimensions of (per time) called as frequency. Seriously, no idea about frequency being scalar or vector quantity.

Method and system for orthogonal modulation of power signals

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.
Owner:ELECTRIC POWER RES INST OF GUANGDONG POWER GRID

Method and device for detecting Android malicious software in batch

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.
Owner:SHENZHEN GRADUATE SCHOOL TSINGHUA UNIV

Method for identifying place image on the basis of improved probabilistic topic model

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.
Owner:BEIJING UNIV OF TECH

Target motion parameter estimation method for random frequency hopping radar

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.
Owner:XIDIAN UNIV

Data model dual-drive GFDM receiver and method

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.
Owner:SOUTHEAST UNIV

Method for ordering significance of keywords in text

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.
Owner:SHANGHAI UNIV

Knowledge recommendation method and equipment based on similarity

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.
Owner:DHC SOFTWARE

Video multi-target long-range tracking method

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.
Owner:CHANGSHA UNIVERSITY OF SCIENCE AND TECHNOLOGY

Method and device for configuring full-phase filter bank through frequency response characteristic

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.
Owner:TIANJIN UNIV
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