The invention discloses a sparse construction and reconstruction method of array space signals. Due to the fact that the angle of received incident signals changes constantly under the high dynamic condition, enough sampling signals can not be acquired to conduct traditional beam forming. According to the method, a gain test of the array space signals is conducted through the Capon beam forming method based on feature space decomposition, and establishment of a small-snapshot-number sparseness model and OPM reconstruction of the small-snapshot-number sparseness model are conducted based on the compressed sensing theory. The result shows that the method has the advantage of processing undersampled data and achieves estimation on the angle of arrival of the array signals. The method further shows that in the space signalprocessing field, sparsity makes extraction of related information faster and more effective, so that the signal acquisition cost and the signalprocessing cost are lowered. By means of the method, expected waveform gain can be obtained in the expected direction of arrival. Compared with a direct sampling method, the method can solve the small snapshot number problem occurring under the high dynamic condition and improve the robustness of a system.
The invention discloses a blood-pressure measurement method based on video images. By adopting the method, the blood pressure is continuously measured by collecting a video image of a human face and performing space decomposition, time-domain filter and real-time processing on the face video image. The method particularly comprises the following steps: tracking a to-be-measured target region in real time to determine a ROI region; performing RGB three-channel separation on each frame of an image sequence of the obtained ROI region, summing and averaging to obtain a time sequence waveform in a period; removing the trend term from the time sequence waveform, and normalizing to obtain a time sequencesignal; denoising the normalized signal by adopting an empirical mode decomposition method to obtain a three-channel time-domain signal with relatively high signal-to-noise ratio; and finally calculating the wave crest and wave trough of the time-domain signal, and establishing the relation between the time-domain signal and blood pressure to obtain a blood pressure value. The method is applicable to the fields of health big-data collection, remote medical treatment and the like.
The invention relates to image decomposition strategies and computer-based methods for implementing them. In one method of the invention, the ordering of tetrahedral shapes that define or approximate an image is performed in such a way that neighboring tetrahedral shapes can be identified, located and efficiently used. In one aspect, a binary location code array is used to represent an image and the method for identifying the neighbor shape employs a bit manipulation step in code or pseudo-code for operating a computer. In this aspect, the invention allows one to move between adjacent tetrahedra, and any data corresponding to the tetrahedra, in constant time.
The invention relates to a method and a device of excavation of a subject of text big data based on characteristic spacedecomposition. The method comprises two associated parts: one part is a space decomposition method based on the subject characteristic, the second part is an acceleration method based on model solution of multiple sub-spaces. The key of the space decomposition method is to utilize model characteristics to decouple the data samples and the subject assemblies, and therefore segmentation and decomposition of the data space and the subject space are achieved simultaneously, a plurality of sub-model spaces smaller than a full model space are obtained, and complexity of a storage space of a calculation solution algorithm is effectively reduced. At the same time relevant independence among the sub spaces can be utilized simultaneously to reflect the sub spaces to all kinds of parallel entities, and therefore time complexity of the calculation algorithm is effectively reduced. The method of the excavation of the subject of the text big data based on the characteristic spacedecomposition is capable of sufficiently utilizing parallel processing capability of a calculation device, and achieving parallel expansion processing of large-scaled subject modeling spaces and large-scaled data assemblies.
A method for converting a software environment defined using flat name space into an equipment model is provided. The method includes decomposing the flat name space into a plurality of tokens, and assigning each token to a corresponding level of a plurality of levels included in an equipment hierarchy. The method also includes translating each token into a human-readable name, and creating an equipment model based on the human-readable name and the corresponding level assigned to each token.
The invention discloses a global energyinterconnectionpower balance optimization method based on space-time decomposition, which comprises the following steps: constructing an intercontinental powergrid partition power balance mixed integer optimization model and a global energy Internet power balance linear optimization model, and carrying out optimization calculation to obtain the operation state of a partition generator set; optimizing and calculating the intercontinental tie line transmission power and the renewable energy generation power based on a partition unit operation state optimization result; and finally, performing iterative optimization calculation between the intercontinental power grid partition power balance mixed integer optimization model and the global energy Internet power balance linear optimization model to obtain an optimal power balance optimization result. A global energy interconnection power balance optimization basic principle based on time-space decomposition iteration is determined, and modeling and optimization calculation steps realized by a computer are provided. A global energy Internet power balance optimization method suitable for distributed calculation can be provided, so that the calculation efficiency is higher, the calculation speed is higher, and the method is more suitable for large-scale data calculation.