11 results about "Band spectrum" patented technology

The present application relates to a kind of spectrum occupation degree calculation method based on full-band spectrum data, belong to radio signal spectrum analysis field.The present application is based on the full-band spectrum data of same sampling time, and the full-band signal is divided into several sub-bands;Based on the full-band spectrum data of once sampling time, the level threshold of all sub-bands is calculated;Based on the spectrum data of different sampling time in measurement time, the occupation degree is estimated.The present application obtains multiple interval threshold values in each sub-band by histogram, interclass variance and other means, which can be used in abnormal electromagnetic signal monitoring scene, further reduces the false alarm rate of abnormal signal alarm, and improves electromagnetic space safety supervision ability.

A method for performing in-band spectrum sharing in a mixed TN-NTN system is provided. The method is performed by a user equipment (UE). The UE receives reference signal (RS) configuration information from a satellite or TN base station and obtains measurement results indicative of coupling loss or interference based on the RS configuration. The UE transmits a measurement report to the satellite or an uplink RS to the TN base station for resource allocation decisions. The UE operates according to resource allocation results indicating a partition of shared radio resources across frequency, time, or polarization domains to mitigate interference. Finally, the UE communicates using the allocated resource portion of the shared radio resources.

This invention discloses a rapeseed quality detection method based on feature wavelength optimization and multi-model fusion. The method involves collecting full-band near-infrared diffuse reflectance spectral data of rapeseed samples and simultaneously measuring the true values ​​of physicochemical indicators to construct an original dataset. Based on the data distribution characteristics of each physicochemical indicator, the original dataset is divided into a training set and a test set. Preprocessing algorithms are selected for each physicochemical indicator to process the full-band near-infrared diffuse reflectance spectral data. Dimensionality reduction algorithms are selected for each physicochemical indicator to extract feature wavelengths from the preprocessed spectral data. Predictive models for each physicochemical indicator are established based on the training set, and the performance of the predictive models is verified using the test set to determine the optimal algorithm combination for each physicochemical indicator. The variable importance projection algorithm is used to calculate the comprehensive contribution score of each wavelength point in the full-band spectrum to the four physicochemical indicators. A multi-indicator comprehensive threshold is set, and the core light source wavelength of the portable device is determined from the high-score region.

The present application relates to a kind of wide frequency power grid harmonic fast extraction method based on multiscale collaborative measurement, belong to the field of power system harmonic analysis, including: construct multi-window parallel data buffer, utilize smooth transition function dynamically calculate the confidence weight of each window;Adopt adaptive window function strategy to load rectangular window and Blackman window respectively, and preliminary obtain full-band spectrum parameter in combination with zero padding FFT, introduce phase alignment algorithm based on time zero point to eliminate the phase drift caused by non-synchronous sampling;For random interference, use stability filtering mechanism to carry out effectiveness check.The present application realizes the unity of wide frequency harmonic transient fast locking and steady-state high-precision measurement by organically combining multi-window parallel processing with S-shaped smooth transition mechanism, significantly improves the dynamic adaptability and anti-noise reliability of measurement, and provides reliable technical foundation for new type power system wide frequency oscillation monitoring and control.

The present application relates to the technical field of mineral resources exploration, and particularly relates to a bauxite lithium-rich ore rapid optimization method and system based on imaging hyperspectrum. The method comprises the following steps: collecting standard hyperspectrum data according to a bauxite sample; constructing a multi-dimensional fusion spectrum data set by using the standard hyperspectrum data; screening optimal characteristic band spectrum data from the multi-dimensional fusion spectrum data set; constructing a lithium ore rapid optimization model based on the optimal characteristic band spectrum data, and generating a lithium content spatial distribution thermal map through the lithium ore rapid optimization model. Through multi-dimensional spectrum transformation, characteristic band screening and integrated estimation model construction, the present application realizes efficient and accurate identification of lithium-rich ores in bauxite, and solves the problems of high cost, low efficiency and insufficient optimization precision of traditional methods.

The described technology is generally directed towards multi-band spectrum allocation for cellular networks. A first radio frequency band can be allocated for dedicated use at a first cellular communication network, while a second radio frequency band can be allocated for shared use via the first cellular communication network and a second cellular communication network. The first cellular communication network can comprise a private network, while the second cellular communication network can comprise a public network. In order to select the first and second radio frequency bands, multiple radio frequency bands can be evaluated for carrier characteristics such as quality of service and coverage area.

The application discloses a hyperspectral image efficient splicing system based on grid guidance and manual registration, relates to computer vision technology, and is proposed in view of problems such as complicated operation in the prior art. The following steps are performed during running: a hyperspectral data folder is loaded and a false color image is generated; initial image splicing is performed; a coordinate mapping file is generated and saved; a global false color image is reconstructed based on the coordinate mapping file; and a single-band gray image is generated and interactive spectrum extraction is performed. The application has the advantages that an ordered splicing mechanism of grid arrangement guidance is provided, an accurate registration strategy of manual feature point selection is combined, and independent storage and on-demand reuse of a position mapping file are deeply integrated, so that decoupling scheduling of original hyperspectral data, a false color image and a pixel mapping relationship after initial splicing is realized, splicing accuracy and operation efficiency in a complex scene are significantly improved, memory occupation of secondary reconstruction and single-band spectrum analysis is reduced, and data reuse and interactive analysis capability are improved.

The application relates to a narrow-band frequency selection monitoring method, device, equipment, medium and program product. The method comprises the following steps: performing spectrum analysis and candidate frequency point evaluation processing on a narrow-band spectrum scanning signal of a target region, dynamically screening and determining a target frequency point; acquiring spectrum identification information of the target frequency point, narrow-band time sequence monitoring data of the target frequency point and type identification information corresponding to multiple signal types; calculating a confidence degree corresponding to each signal type of the target frequency point according to frequency point description characteristics, spectrum quality characteristics and type identification information characteristics; determining a target frequency point type of the target frequency point according to the confidence degree; and performing a corresponding monitoring treatment strategy according to the target frequency point type and / or the spectrum quality characteristics. The method can adapt to the communication stability requirement in a complex electromagnetic environment.

The application discloses a kiwi fruit quality deterioration detection method based on hyperspectrum and deep learning, relates to the field of fruit and vegetable quality nondestructive detection technology, collects hyperspectrum images and extracts full-band spectrum data, carries out deterioration grade labeling and division on the data after smoothing pretreatment, trains and optimizes a one-dimensional convolutional neural network model embedding spectrum original features and deep convolutional feature fusion grading determination operation, finally inputs sample spectrum data to be detected into the model, and outputs deterioration grade results; the application collects hyperspectrum images and constructs a standardized spectrum data set, combines the one-dimensional convolutional neural network model embedding spectrum original features and deep convolutional feature fusion grading determination operation, realizes classification and quantitative determination of fruit deterioration grades, effectively solves the problems of strong subjectivity and low efficiency of traditional detection, improves detection precision and robustness, and provides standardized technical support for postharvest quality grading and commercialization of kiwi fruits.