14 results about "Data resampling" patented technology

The invention discloses an InSAR (Interferometric Synthetic Aperture Radar) and GNSS (Global Navigation Satellite System) robust adaptive fusion method for high-precision three-dimensional surface deformation monitoring, which belongs to the technical field of space geodetic survey and remote sensing, and comprises the following steps of: constructing a time sequence deformation field based on a small baseline set time sequence InSAR processing technology, and resampling GNSS observation data to a grid consistent with the InSAR by using Kriging spatial interpolation; a Helmert variance component estimation method is adopted to adaptively estimate variance components of InSAR and GNSS data, and reasonable weight fixing of a multi-source observation value is achieved; iterative reweighted least square estimation is introduced, outlier influences in various observation data are dynamically restrained through a Tukey double-weight function, robust optimization of a fusion model is achieved, and therefore a high-precision three-dimensional deformation field is reconstructed. The method comprises the steps of Helmert weight fixing, IRLS robust, variance component updating and a closed-loop feedback mechanism of weight matrix optimization.

The invention provides a frequency-wavenumber domain-based matrix array full-matrix capture three-dimensional ultrasonic imaging method and system, and belongs to the technical field of ultrasonic imaging. Five-dimensional time-space domain radio frequency data are collected through a two-dimensional full-sampling matrix array and are converted into a frequency-wave number domain through five-dimensional fast Fourier transform, angular frequency is mapped into axial wave number through Stolt interpolation, data resampling is achieved, then three-dimensional image frequency spectrum data are synthesized by defining spatial wave number coordinates of an image and conducting coherence stacking, and the image frequency spectrum data are obtained. And finally, reconstructing a high-quality three-dimensional ultrasonic image through three-dimensional inverse fast Fourier transform. Compared with a traditional delay summation beam forming method, the method has the advantages that the calculation efficiency is remarkably improved, the speed is increased by several times to dozens of times, the spatial resolution, the contrast noise ratio and the spot signal-to-noise ratio are remarkably improved, and the method is suitable for high-resolution real-time three-dimensional and four-dimensional ultrasonic imaging application.

The application relates to the field of meteorological data processing and satellite navigation application, and provides a multi-source meteorological data fusion method and system based on a Beidou space-time reference. The method comprises the following steps: acquiring Beidou data and multi-source meteorological data to be fused, taking the coordinated universal time timestamp output by a Beidou ground-based enhancement station as a global time reference, and setting a sliding window; taking the world geodetic coordinate system corresponding to the Beidou positioning data as a space reference, resampling the multi-source meteorological data to a preset standard grid, and combining terrain elevation data to construct a unified space coordinate system; calculating the confidence degrees of fused static terrain features and dynamic change features based on Beidou satellite orbit residual and clock difference parameters, adjusting the feature weights of the fused static terrain features and dynamic change features, and generating an enhanced fusion feature matrix.

A device includes a receiver to receive a packet over a channel at a first frequency and generate a sampled stream of data at a first sample rate corresponding to the first frequency. A data resampler circuit includes a re-timer engine to determine, using a ratio between the first sample rate and a crystal oscillator (XO)-divided sample rate, re-timer values. The data resampler circuit includes a time shifting circuit to re-sample data values of the sampled stream of data associated with locations of the plurality of re-timer values. A correlation circuit uses the re-sampled data values, and the re-timer values to match an expected data pattern to a corresponding data pattern detected in a frame of the packet.

The invention provides a domain generalization laser radar point cloud semantic segmentation method and system, and belongs to the field of laser radar semantic segmentation, and the method comprises the steps: obtaining point cloud data of a source domain, and carrying out the preprocessing; resampling the preprocessed source domain point cloud data to generate a resampling point cloud; generating a mixed point cloud through a cross-scene mixed enhancement strategy; inputting the initial point cloud data, the re-sampling point cloud data and the mixed point cloud data into a semantic segmentation network to extract point cloud features; unified alignment of point cloud features in a semantic space is realized by using a text encoder of a contrast language-image pre-training model; and carrying out model training by adopting a contrast loss function, selecting a target domain point cloud, inputting the target domain point cloud into the trained model, and outputting a point cloud semantic segmentation result. According to the method, through the synergistic effect of multi-density resampling, cross-scene mixing and unified semantic space alignment, the domain offset problem is effectively relieved, and the semantic segmentation precision and generalization ability of the model on an unknown target domain are remarkably improved.

The application relates to a touch screen resampling method and device, electronic equipment and a storage medium. The method comprises the following steps: performing scene recognition on the electronic equipment to obtain a scene recognition result; determining a corresponding target resampling time difference according to the scene recognition result; the target resampling time difference is a time difference between a sampling time point and a time point of a screen refresh event; after listening to the screen refresh event each time, determining the sampling time point according to the target resampling time difference and the time point of the screen refresh event; resampling target touch screen data reported before the screen refresh event according to the sampling time point to obtain supplementary touch screen data. The method can improve the response effect of touch.

The application provides a data synchronization method and device for multi-device cooperative collection, and belongs to the technical field of automobile testing. The synchronization method comprises the following steps: a step voltage signal is sent to all data collection devices participating in collection through a general hardware trigger module; each data collection device receives and records the step voltage signal through an analog voltage channel; the original data collected by each data collection device is subjected to time axis resetting with the moment when the step voltage signal reaches a preset voltage threshold as a time zero point; the data obtained after resetting is resampled at the same sampling frequency, and the data length is aligned, so that the multi-device data is synchronized and aligned. The step voltage signal is sent through the general hardware trigger module, and the starting moment of collection of each device is unified; meanwhile, the time deviation of data collection is solved by data resampling of software, the data collected by collection devices of different brands and models is synchronized and aligned, and high-precision and high-reliability cooperative collection is realized.

The application discloses a depth domain seismic wavelet extraction method based on a generalized seismic wavelet model. The method is characterized in that, the depth domain logging data information can be fully utilized, the depth domain seismic record is directly synthesized in the depth domain, the depth domain seismic wavelet can be efficiently and accurately extracted from the depth domain generalized seismic wavelet model only through 3 to 5 iterations, the method has high stability, and the effective information loss problem caused by domain conversion or data resampling is avoided.

This application discloses a method for reducing resource overhead during data resampling, comprising: calculating the ratio of the input and output sampling rates of the rate matching module and the absolute difference between 1 and the ratio; when the input sampling rate is less than the output sampling rate, reading data from a FIFO buffer according to a read enable signal and a read pointer, moving the read pointer forward by one position and accumulating the absolute difference after each read; when the accumulated absolute difference is greater than or equal to 1, keeping the read pointer unchanged and reading again for interpolation; when the input sampling rate is greater than or equal to the output sampling rate, writing data to a FIFO buffer according to a write enable signal and a write pointer, moving the write pointer forward by one position and accumulating the absolute difference after each write; when the accumulated absolute difference is greater than or equal to 1, pulling the write enable signal low and discarding the currently written data for sampling. This invention reduces resource overhead during data resampling without relying on a high-frequency clock and a large-depth FIFO.

The embodiment of the present application relates to a kind of time series anomaly detection method and device, the method comprises: obtaining the time series data set to be processed, each time series data in the time series data set at least includes time point and corresponding numerical value;The data in the time series data set is preprocessed, and the preprocessing includes data resampling, missing value processing, data labeling, data formatting and anomaly injection;Based on the time series data set after preprocessing, an anomaly detection model is constructed;Anomaly detection is carried out using the anomaly detection model.The technical scheme provided in the embodiment of the present application, by the reasonable data preprocessing link to time series data set, improve the data quality;By providing different sequence anomaly detection model, and more flexibly link it when monitoring in real time on line, while ensuring accuracy also makes its execution efficiency improves.

The application discloses a method and device for reducing image noise, a computer readable storage medium and a terminal, and relates to the technical field of image processing.The method comprises the following steps: performing first data processing and second data processing on a to-be-processed image respectively to obtain a first image and a second image, wherein the first data processing is increased by at least one round of data resampling processing compared with the second data processing; determining a fusion weight value of each pixel according to the first image and the second image; and performing pixel-level fusion processing on the first image and the second image by using the fusion weight value to obtain a fused image.The application can remove chroma noise while retaining the color of a real object in an image and reducing color loss.

This invention discloses a method, system, equipment, and storage medium for constructing a distribution network operation architecture, relating to the field of distribution network operation architecture. The method includes: extracting monitoring data from different equipment operations to establish a distribution network dataset with the same time-stamp; resampling all equipment data to the same timestamp sequence based on the kernel density formula; determining and performing alignment operations between the current equipment operation monitoring data and the same timestamp sequence based on the equipment's sampling frequency and timestamp; obtaining the quality assessment score and weight coefficient of the equipment operation monitoring data, and updating and optimizing it; constructing a distribution network operation architecture evaluation model and outputting the current operation status labels of the distribution network equipment; and dynamically adjusting the equipment operation parameters in the distribution network operation architecture based on fault tree analysis and expert experience rules. This achieves dynamic sampling of equipment operation data and applies the distribution network operation architecture evaluation model to solve the problem of synergistic operation of distribution network economy and reliability under multiple constraints.

Various systems and methods are provided for processing computed tomography (CT) data in a CT imaging system. The CT imaging system comprising an X-ray source configured to emit X-rays, an X-ray detector configured to generate sampled digital detector data and a digital processor configured to process the sampled digital detector data. The method comprises filtering, in the digital processor, the sampled digital detector data to generate filtered detector data and resampling, in the digital processor, the filtered detector data to generate resampled detector data. The resampling comprises a reduction in data size of the filtered detector data. The filtering is performed on at least part of the sampled digital detector data according to a filtering setting and the resampling is performed on at least part of the filtered digital detector data according to a resampling setting, wherein the filtering setting and resampling setting are decoupled.