56 results about "Data truncation" patented technology

Different combinations of global motion parameters are estimated for a current frame interpolated to derive local motion vectors for individual image blocks. Image blocks in a reference frame identified by the local motion vectors are compared to the image blocks in the current frame. The estimated global motion parameters that provide the best match between the image blocks in the current frame and the reference frame are selected for encoding the current frame. Selected sub regions of temporally consecutive image frame s can be used in order to release the computational burden for global motion estimation and provide more robust global motion estimation results. A data truncation method can also be used to remove bias caused by foreground moving objects.

The invention discloses a ranging method based on measurement of the laser pulse flight time. According to the ranging method based on the measurement of the laser pulse flight time, based on the synchronous clock pulse measurement method, a self-adaptive gradient adjustment slope generator and a differential amplification circuit are adopted, not only can the time duration of the part, synchronous with a system clock, in the laser pulse flight time be accurately measured, but also that the time duration of the part, not synchronous with the system clock, in the laser pulse flight time can also be measured extremely accurately, and thus accurate measurement of a target distance is achieved. The time difference ta between the moment when laser is emitted and the nest rising edge of the system clock and the time difference tb between the moment when the laser returns and the next rising edge of the system clock are linearly converted into a voltage V1 and a voltage V2 respectively, a digital value in linear proportion to ta-tb is output after differential amplification and AD conversion, calculation errors caused by data truncation can be effectively avoided, measurement errors caused by factors such as circuit nonlinearity can be effectively reduced through self-adaptive gradient adjustment conducted through the slope generator, and the ranging method is suitable for ranging occasions with the high accuracy requirement.

The invention relates to a three-dimensional digital imaging method of the large view field cone-beam X-ray tilting scanning of a biased detector, belonging to the technical field of X-ray computerized tomography (CT). In the three-dimensional digital imaging method, the area array detector is placed to be biased, and an X-ray source is used for generating cone-beam X-rays which irradiate a member imaging area with a certain angle in a penetrating and tilting way relative to the length and width surface of a member; in the scanning process, the X-ray source and the area array detector are static, the member rotates in an angle of 360 degrees in an equal angle and step length way surrounding a rotating shaft, and the area array detector acquires an X-ray signal modulated by the member under each rotation angle. A three-dimensional computerized tomography image of a scanning area can be reestablished and obtained by a data truncation smoothing preprocessing method and a filtering back projection reestablishing arithmetic according to data obtained by the area array detector under the scanning angle of 360 degrees. Compared with the traditional tilting scanning method, the three-dimensional digital imaging method can double the tilting scanning imaging view field without changing the system hardware and the scanning speed and has high reestablishment quality, simple process and high efficiency.

A rate control unit performs data truncation on a code sequence having been sorted and bit shifted as shown in FIG. 10 so that a desired noise reduction effect is achieved. The data truncation occurs in sequence from the rightmost bit. For example, in FIG. 10, data is truncated from data of bit 0 in a subband VHL4 downwardly in sequence through data of bit 0 in a subband YHH5, and so on. If the desired noise reduction effect can be achieved by truncation of up to bit data in the subband YHH1, data in those subbands in a dotted area in FIG. 10 will be truncated. If the desired noise reduction effect cannot be achieved by truncation of up to bit data in the subband YHH1, data will then be truncated from data of bit 0 in a subband VLL4 downwardly in sequence.

A rate control unit performs data truncation on a code sequence having been sorted and bit shifted as shown in FIG. 10 so that a desired noise reduction effect is achieved. The data truncation occurs in sequence from the rightmost bit. For example, in FIG. 10, data is truncated from data of bit 0 in a subband VHL4 downwardly in sequence through data of bit 0 in a subband YHH5, and so on. If the desired noise reduction effect can be achieved by truncation of up to bit data in the subband YHH1, data in those subbands in a dotted area in FIG. 10 will be truncated. If the desired noise reduction effect cannot be achieved by truncation of up to bit data in the subband YHH1, data will then be truncated from data of bit 0 in a subband VLL4 downwardly in sequence.

The invention discloses a time series data intelligent fault diagnosis method based on deep learning. The method comprises the following steps: 1) collecting one-dimensional time series health state data of electromechanical equipment, wherein fault data is the fault data arranged at a preset measuring point of the electromechanical equipment; 2) constructing a one-dimensional time series originalfault data set according to the acquired N health state data; 3) preprocessing the data, wherein the preprocessing includes normalization and data truncation; 4) constructing a two-dimensional feature map fault data set; 5) carrying out data set division; 6) constructing a deep learning fault diagnosis model; 7) training the deep learning fault diagnosis model to obtain parameters; and 8) performing fault diagnosis on the input to-be-diagnosed sample data by using the deep learning fault diagnosis model, and outputting a final fault diagnosis result. By constructing the two-dimensional feature map and improving a traditional convolutional neural network model structure, a fault diagnosis speed and fault diagnosis accuracy are improved.

The embodiment of the invention discloses a pre-estimating method and device based on missing data. The pre-estimating method comprises the steps of obtaining all historic data collected within a preset period of time; dividing all the historic data within the preset period of time into M sub-periods of time; selecting an unselected sub-period of time from all the sub-periods of time as a current sub-period of time; calculating the missing density of missing historic data in the current sub-period of time; judging whether the missing density of the missing historic data in the current sub-period of time is larger than a preset threshold value or not; if not, selecting an unselected sub-period of time in all the sub-period of time as the current sub-period of time again; if yes, determining to-be-truncated data meeting preset truncation conditions in the current sub-period of time; according to the time order, at least truncating all data before the to-be-truncated data; according to remaining historic data in all the historic data, performing pre-estimating. According to the method and device, the phenomenon of deviations of a pre-estimating result can be effectively improved.

The embodiment of the invention provides a point cloud data division method and device and an obstacle detection method and device, and belongs to the technical field of computers. The point cloud data partitioning method comprises the steps of performing three-dimensional reconstruction on a depth image of a current environment to generate a point cloud data set, wherein one piece of point clouddata in the point cloud data set corresponds to one pixel point in the depth image; obtaining histogram distribution of the depth image based on pixel point depth values; establishing a plurality of depth intervals according to the number of pixel points corresponding to each histogram dimension in the histogram distribution; and dividing the point cloud data set into a plurality of sub-point cloud data sets corresponding to a plurality of depth spaces according to the point cloud data corresponding to the pixel points included in each of the plurality of depth intervals. According to the method, a point cloud data truncation phenomenon can be avoided, and the adaptability to a scene is higher.

The invention discloses a rotary machine fault diagnosis method based on an improved convolutional neural network, and the method comprises the following steps: (1) collecting one-dimensional time sequence fault data, and obtaining an original fault data set; (2) performing preprocessing operation on the acquired data of the original fault data set, wherein the preprocessing comprises standardization, data truncation and data reconstruction; (3) dividing the preprocessed samples of each type of faults into a training set, a verification set and a test set; (4) an improved convolutional neuralnetwork fault diagnosis model is established, the model comprises an input layer, a feature extraction layer, a dimension reduction and parameter reduction layer and a softmax classification output layer, and the dimension reduction and parameter reduction layer comprises a 1 * 1 transition convolution layer and a global mean pooling layer; (5) training and testing the model; wherein the diagnosismodel can automatically extract features and diagnose the fault data without any manual feature extraction operation, so that people can diagnose the fault of the rotating machine more conveniently and quickly.

The invention discloses a power self-adaptive algorithm based on improved Prony, which is used for accurately metering the electric energy of a power grid under the condition that the frequency and the amplitude of a power system signal change along with time. The method comprises the following steps: synchronously sampling a voltage signal u(t) and a current signal i(t) of a power system with a sampling frequency fs and a sampling duration ts to obtain N-point discrete voltage signals u(n) and N-point discrete current signals i(n), performing data fitting on the sampled electric signals (u(n)and i(n)) in a time domain to obtain a fitting data sequence, performing data truncation according to a sampling interval, and constructing a reconstructed sample; estimating the frequency amplitudeof each reconstructed sample of the voltage and current signals after data fitting by using a Prony algorithm; and finally, calculating a power value changing along with time. Experimental results prove that the algorithm quickly and accurately realizes adaptive tracking of power grid electric energy.

The invention discloses a sample selection method based on Weibull distribution and right truncation data estimation reliability. The sample selection method comprises the following steps of 1) determining that a research object obeys the three-parameter Weibull distribution and the shape parameters; 2) estimating the position parameters and the scale parameters in the three-parameter Weibull distribution by using the relation between the bit rank and the sample size in the product failure probability; and 3) establishing a right truncation data truncation principle of the product life probability distribution by utilizing the shape parameters, the position parameters and the scale parameters of the three-parameter Weibull distribution according to the specific condition of the research object. According to the method, a shorter observation sample is discarded; the reliability analysis efficiency of estimating the product within the observation life time is improved to the maximum extent; the number of the practical application samples is reduced, the reliability analysis efficiency of the products based on the right truncation data is improved, and the method is especially suitable for the reliability analysis of the small-sample right truncation data products, is simple, has strong operability, has no special requirements for product types of the specific research objects, and has wide applicability.

A quantitative method for nuclear medicine heart image and an electronic device are provided. The method is adapted for multi-pinhole SPECT images or SPECT / CT images. The method includes a radionuclide physical decay correction, a scatter correction, a geometry distortion correction, a data truncation compensation, a tissue attenuation correction, an image space resolution recovery, a noise removal, a pixel value conversion, a myocardial blood flow quantitative calculation, an intra-scan patient movement correction and a blood flow condition evaluation. Accordingly, a quantitative SPECT reconstructed image of a heart is obtained, and an absolute quantization of the myocardial blood flow is calculated to measure the myocardial blood flow quantitatively according to the quantitative SPECT reconstructed image. In addition, a blood flow condition diagram according to a number of indicators is established, and a myocardial blood flow condition is evaluated according to a quantization result of myocardial blood flow and the blood flow condition diagram.

The invention discloses a multi-channel time series data fault diagnosis method based on a convolutional neural network. The method comprises the following steps: (1) collecting multi-channel one-dimensional time series fault data of a monitored object; (2) constructing a multi-channel one-dimensional time sequence original fault data set, and carrying out normalization and data truncation preprocessing; (3) constructing a multi-channel two-dimensional feature map fault data set; (4) dividing into a training set, a verification set and a test set; (5) constructing a multi-channel deep learningfault diagnosis model which comprises an input layer, a feature extraction layer, a dimension reduction and parameter reduction layer, a softmax classification layer and a support vector machine output layer, wherein the dimension reduction and parameter reduction layer comprises a transition convolution layer with a convolution kernel of 1 * 1 and a global mean pooling layer; and (6) training, verifying and testing a multi-channel deep learning fault diagnosis model, and finally automatically outputting a diagnosis result by a support vector machine, so that people can diagnose faults of theelectromechanical equipment more intelligently and conveniently.

The invention relates to a nuclear medicine heart image quantification technology, in particular to to a technological method for multi-pinhole SPECT or SPECT / CT dynamic image quantitative reestablishment and myocardial blood flow absolute quantification measurement and application of the technological method in myocardial blood flow state evaluation. The technological method includes the specific steps of nuclide physical decay correction, in-scanning patient movement correction, scattering correction, geometric warping correction, data truncation compensation, tissue attenuation correction, noise removal, pixel value conversion, myocardial blood flow quantitative calculation and blood flow state evaluation. With the technological means, a quantitative multi-pinhole SPECT dynamic heart image can be generated, myocardial blood flow absolute quantification calculation can be carried out through the quantitative multi-pinhole dynamic image, and thus quantitative measurement of the myocardial blood flow is achieved; meanwhile, a blood flow state diagram is established with the three indexes of resting blood flow, load blood flow and blood flow reserve and is put into the practical application of evaluating the myocardial blood flow state, the purpose of carrying out quantitative measurement of the myocardial blood flow with multi-pinhole SPECT and SPECT / CT dynamic development is achieved, and the technological method can be applied to evaluation of the myocardial blood flow state.

The invention provides a data synchronization method, a data synchronization apparatus, a computer device, and a storage medium. The data synchronization method comprises the following steps: receiving first data synchronization request information, wherein the first data synchronization request information comprises client data version information; comparing the latest data version information with the client data version information, and extracting corresponding service data that need to be synchronized; and compressing the service data to write the same in a file stream so as to form a service data file, and transmitting the service data file to a client corresponding to the first data synchronization request information in the form of file. By adoption of the technical scheme of the invention, on one hand, the repeated processing of multiple intermediate links is reduced, and the risk of data truncation is reduced, and on the other hand, by adoption of the file form transmission, continuous transmission can be performed even in the case of poor network quality, and the stability of synchronous data transmission is improved, furthermore, the time of data synchronization is shortened, the efficiency of data synchronization is improved, and it is conducive to improving the consistency of data synchronization.

A rate control unit performs data truncation on a code sequence having been sorted and bit shifted as shown in FIG. 10 so that a desired noise reduction effect is achieved. The data truncation occurs in sequence from the rightmost bit. For example, in FIG. 10, data is truncated from data of bit 0 in a subband VHL4 downwardly in sequence through data of bit 0 in a subband YHH5, and so on. If the desired noise reduction effect can be achieved by truncation of up to bit data in the subband YHH1, data in those subbands in a dotted area in FIG. 10 will be truncated. If the desired noise reduction effect cannot be achieved by truncation of up to bit data in the subband YHH1, data will then be truncated from data of bit 0 in a subband VLL4 downwardly in sequence.

The invention provides a method for enlarging an SFDR (spurious free dynamic range) of a signal after data truncation. A uniformly distributed random integer signal sequence in a certain amplitude range is generated through design, the bit width of the random integer signal sequence is identical with the truncated bit width, the random integer signal sequence is stacked on a signal before truncation, then bit width truncation is performed, and a random signal after truncation is obtained, so that the harmonic amplitude of the truncation error is decayed rapidly, harmonic distortion caused by direct truncation is eliminated, and the dynamic range of the random signal after truncation is enlarged.

A rate control unit performs data truncation on a code sequence having been sorted and bit shifted as shown in FIG. 10 so that a desired noise reduction effect is achieved. The data truncation occurs in sequence from the rightmost bit. For example, in FIG. 10, data is truncated from data of bit 0 in a subband VHL4 downwardly in sequence through data of bit 0 in a subband YHH5, and so on. If the desired noise reduction effect can be achieved by truncation of up to bit data in the subband YHH1, data in those subbands in a dotted area in FIG. 10 will be truncated. If the desired noise reduction effect cannot be achieved by truncation of up to bit data in the subband YHH1, data will then be truncated from data of bit 0 in a subband VLL4 downwardly in sequence.

The invention provides a BOC (n, n) modulation signal fast capture method. Multi-stage down-conversion, amplification and filtering are carried out on useful navigation signals in the band, to obtainan analog intermediate frequency BOC (n, n) signal, a low-speed clock CLK1 drives a signal preprocessing module to preprocess the intermediate frequency BOC (n, n) signal, sampling values of IF, QF and the CLoc are read by using a high-speed clock CLK2, partial matching filtering is carried out, the high-speed clock CLK2 is used for driving, a correlation value obtained in the round is subjected to P times of L-point all-phase FFT, the high-speed clock CLK2 is used for driving, and whether a signal is captured or not is judged according to the capture result and BOC (n, n) signal characteristics. According to the method, whether the signal is captured or not can be effectively judged by judging the characteristics of the relationship among the three peak values, spectrum leakage caused bysampling data truncation is reduced, and the signal processing efficiency is effectively improved.

It is disclosed a system and a method for reconstructing an image by using a straight-line trajectory scan to avoid image spatial resolution reduction due to interpolations in angular direction and detector direction during data rebinning. This system comprises: a projection data conversion section for converting projection data from straight-line trajectory scan into projection data under quasi-parallel-beam scan; a filtration section for obtaining filtered projection data by convoluting the projection data under quasi-parallel-beam scan with a predetermined convolutional kernel; and a back-projection section for reconstructing an image by back-projecting the filtered projection data with a weighting factor. By using the inventive system and method, the spatial resolution in the reconstructed image is improved, and the influence of data truncation on the reconstructed image is reduced. The present invention applies the filtration and back-projection mode, and thus has general advantages of the filtration and back projection, such as simplicity and efficiency. And it is easy to be parallelized and accelerated.

The invention discloses a frequency and amplitude adaptive algorithm for a transient electrical signal. The algorithm includes the following steps: performing cubic spline interpolation on an electrical signal of a sample at a time domain; performing data truncation according to sampling intervals after obtaining an interpolation sequence; constructing reconstructed samples; and estimating the frequency and amplitude of each reconstructed sample by adopting a Prony algorithm. Through the verification of experimental results, the algorithm can rapidly and accurately realize the synchronous adaptive tracking of the frequency and amplitude of a power grid; and the algorithm is suitable for the synchronous detection of electrical parameters under the circumstances that the frequency and amplitude of a power grid signal are simultaneously changed with time, so that the algorithm is high in accuracy and can provide reliable and effective technical support for the accurate measuring and analysis of the three elements of the power grid.

The invention discloses an urban VOCs total pollution time sequence prediction method and system, a storage medium and equipment, and the method comprises the steps: preprocessing total VOCs monitoring data, embedding the data for projection, wherein the data comprises position information including year, month and day information, and also including the setting information of holidays and festivals; performing convolution pooling on the obtained data, reducing redundant data, generating an attention probability matrix through a sparse full-self-attention mechanism in an encoder to obtain a feature map, inputting the feature map once repeatedly to obtain the feature map, and transmitting the feature map to a decoder; cutting half of the data, inputting the data, performing the same operation, splicing the feature maps obtained twice to form a finally obtained feature map, and transmitting the finally obtained feature map to the decoder; and masking the data, inputting the data into the decoder, and obtaining a prediction result by the decoder according to the masked input and the prediction result obtained in the previous step. A longer time sequence can be processed, and the information of the time sequence can be extracted more effectively.

The invention provides a data processing method and a data processing system. The data processing method comprises the steps of receiving data transmitted by a client, wherein the data comprises header information, length information and actual data, the header information comprises encapsulation identification information, and the length information comprises the preset length of each data packet sequence; carrying out de-capsulation on the actual data according to the encapsulation identification information so as to acquire original data; and segmenting the original data according to the preset length of each data packet sequence so as to acquire at least one data packet sequence. According to the invention, de-capsulation is carried out on the encapsulated actual data according to the encapsulation identification information in the header information so as to acquire the original data, and segmentation is carried out on the original data according to the preset length of each data packet sequence in the length information so as to acquire at least one data packet sequence, thereby achieving the effects of data adhesion and data truncation.

The invention discloses a data truncation method in a radar signal processor, which mainly solves the problem that data truncation modules in pulse compression processing, moving target detection processing and data mode operation in the conventional radar signal processor have low precision. The method comprises the following steps of: normalizing input data, namely taking an absolute value of the input data; performing logic OR operation on normalization results of all data in a group of pulse repetition time (PRT) or coherent parameter intervals (CPI) to obtain a logic OR value of the group of data, and determining the highest nonzero digit position of the logic OR value; and finally, selecting bits of the next group of data according to the highest nonzero digit position. By the method, effective information of the data can be fully utilized; and compared with the traditional method, the method has the advantage of high data truncation precision and can be used for the pulse compression processing, moving target detection processing and data mode operation in radar signal processing.

The invention belongs to the technical field of Internet communication and network security, and particularly relates to an IPv6 (Internet Protocol Version 6)-based encodable and traceable network transmission rule verification method. According to the method, HASH operation is carried out on a digital object, and an IPv6 address is generated by an obtained code; meanwhile, the IPv6 address is used as a routing address for accessing the data; therefore, a network with data content as the center is formed, and transmission of digital objects can be controlled and traced from a network layer. Verifying the network transmission rule of the data IPv6; the network transmission rule verification comprises a data out-of-domain rule, a pre-audited data out-of-domain rule and data truncation of cross-border platform management. The digital object can be managed, controlled and traced from a network layer according to a network transmission rule.

The invention relates to a data truncation method and device, and the method comprises the steps: detecting whether a global lock exists or not when a calculation task is received; if not, setting a global lock according to the calculation task, and performing data truncation according to the calculation task; and if so, judging whether to execute the calculation task or not according to the attribute of the global lock. According to the scheme, the global lock is adopted to guarantee the accuracy of distributed computing data truncation, generation of error data is reduced and controlled, theaccuracy of the data is guaranteed from the source, and losses caused by disorder possibly caused by data truncation are avoided. Consumption of a file system and a database is reduced, and overall operation performance of the system is improved.

The invention provides a dynamic radar echo digital down-conversion system and method based on an FPGA (field programmable gate array). The dynamic radar echo digital down-conversion system includes aband-pass filter, a dynamic truncation device, an odd-even extraction device, a frequency mixing device and a low-pass filter, wherein the dynamic truncation device comprises a first dynamic truncation module, a second dynamic truncation module and a third dynamic truncation module, and whether truncation operation is conducted or not is decided based on different input signals and the bit widthof the maximum amplitude value of the signals. The dynamic radar echo digital down-conversion system and method are based on the digital down-conversion principle, the data caching function of the FPGA and FIFO is fully used, the maximum amplitude value of each signal is calculated while data are cached, and then according to a unique data truncation method, dynamic truncation of the echo signal is completed while the useful signals are retained to the greatest extent. The digital down-conversion system can be dynamically adaptive to down-conversion processing of radar echo signals with different intensity under different environments by combining the dynamic truncation method.

The invention provides a single crystal blade impact test measurement data correction method and correction system used for correcting a to-be-corrected file generated after a reference data file is cut off, and relates to the field of data analysis. The correction method comprises the following steps: reading a to-be-corrected file, and extracting attribute information of each channel of the to-be-corrected file; determining channel codes of the to-be-corrected file according to the channel attribute information of the to-be-corrected file and the one-to-one correspondence between the channelcodes and the channel attribute information, and arranging the channel codes of the to-be-corrected file according to a preset sequence to obtain channel information of the to-be-corrected file matched with the channel information of the reference data file; and modifying and outputting the modified file according to the channel information and the preset parameters of the to-be-modified file. According to the single crystal blade impact test measurement data correction method and correction system, the channel information lost due to data truncation can be found, and the reliability of dataanalysis is ensured.

The invention relates to a system and method for predicting a truncated image, a method for preparing data, and a medium therefor. The method for preparing the data comprises a virtual simulation stepused for carrying out virtual simulation on image data so as to obtain a virtual distorted image with data truncation and a virtual fine standard image without data truncation at the same time. The method for predicting the truncated image predicts the truncated image based on the trained learning network, and the trained learning network is obtained by performing data training based on a data set composed of the virtual distorted image and the virtual fine standard image which are obtained through the method for preparing the data. Also provided are a system corresponding to the method and arecording medium in which the recorded instruction can implement the method.