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122 results about "Global distribution" patented technology

Enhanced CPLD macrocell module having selectable bypass of steering-based resource allocation

Structures and techniques are provided for allowing one or more of the following actions to occur within a Complex Programmable Logic Device (CPLD): (1) Elective use of a fast, allocator-bypassing path (e.g., a fast 5-PT path) in combination with in-block simple or super-allocation; (2) Elective use of an OSM-bypassing path for signals that do not need pin-consistency; (3) Automatic re-routing of output enable signals that corresponding to output signals which are re-routed for pin-consistency purposes; (4) Global distribution of globally-usable output enable signals; (5) Elective use of two-stage steering to develop complex sum-of-clusters terms where fast path or simple allocation will not be sufficient; and (6) Use of unidirectional super-allocation with stage-2 wrap-around in designs having about 24 or less macrocell units per logic block. Techniques are provided for concentrating the development of complex function signals (e.g., ≦80PTs) within singular logic blocks so that the development of such complex function signals does not consume inter-block interconnect resources. One CPLD configuring method includes the machine-implemented steps of first identifying middle-complexity functions that are achievable by combined simple or super-allocation based development in one logic block and fast-path completion in the same or a second logic block; and configuring the CPLD to realize one or more of the functions identified in the first identification step by simple or super-allocation based development in one logic block and fast-path completion in the same or a second logic block.
Owner:LATTICE SEMICON CORP

Clustering-based typical daily load curve selecting method and device

The invention provides clustering typical daily load curve selecting method and device. The method comprises the following steps: reading a curve within a time span, determining the number k of typical daily load curves, and selecting k curves as a set center; classifying the curves into a set (S3) nearest to the set center; and calculating a new set center, determining whether the new set center is the same as the previous set center or not, determining whether the difference with the previous target function is within a preset range or not if the new set center is not the same as the previous set center, returning to the S3 if the difference is not within the preset range, and defining the curves in each set nearest to the set center as the typical daily load curves if the new set center is the same as the previous set center or the difference of the previous target function is within the preset range. The method ensures that all the daily load curves are grasped on the basis of a clustering thought; the generated samples inside the set are similar, while the samples in different sets are different, so that the discovery of a global distribution mode is facilitated, single index calculation or averaging processing is avoided, the influence of random and subjective factors can be reduced, and the sensitivity of directly extracting a single curve on bad data is reduced, therefore, the method is more suitable for discovering potential regulation of large-scale data, and can be used for characterizing the whole regulation better.
Owner:CHINA ENERGY ENG GRP GUANGDONG ELECTRIC POWER DESIGN INST CO LTD

Multi-source remote sensing image classification method based on robust deep semantic segmentation network

The invention discloses a multi-source remote sensing image classification method based on a robust deep semantic segmentation network (Robust Loss Function of Remote Sensing Imagery, RSRLF). The method is formed by recombining a fault tolerance loss function and an adaptive category weight. Remote sensing semantic segmentation is carried out based on the open source land cover classification dataset so that sample annotation work can be greatly reduced, but the open source land cover classification data set contains a certain annotation error sample. The method is advantaged in that the fault tolerance loss function can inhibit the model from learning the noise label, and avoids the over-fitting of the noise label by the model; and a category equalization constraint module can solve problems of large scale difference of globally distributed samples of ground object categories and inconsistent confusion degree among the categories; combination of the two can effectively solve a problem that noise labels and category samples are unbalanced when remote sensing semantic segmentation is carried out by using an open source land cover classification data set, and ground object classification precision based on an open source land cover classification data set is improved.
Owner:WUHAN UNIV

Identity authentication method and device based on a finger vein and equipment

The invention discloses an identity authentication method based on a finger vein, which comprises the following steps: pre-processing the received finger vein image to be identified to obtain a pre-processed image; Convolution calculation is carried out on the preprocessed image, and characteristic point map and vein pattern map are generated according to the obtained convolution value. Accordingto the eigenvalue size and coordinate information of the feature points in the feature point map, the feature points in the feature point map are selected globally according to the preset conditions,and the feature points with high eigenvalue in the global distribution are taken as the feature points to be matched. The vein pattern and template image are matched and compared according to the feature points to be matched, and the identity authentication result is generated according to the matched result. This method extracts feature points from global and local features to obtain globally distributed feature points with high eigenvalues, which can improve the accuracy of vein texture recognition and generate high-precision recognition results. The invention also discloses an identity authentication device e based on a finger vein and equipment, which have the beneficial effects mentioned above.
Owner:GRG BAKING EQUIP CO LTD

A discriminant sparse preserving embedding method for unconstrained face recognition

ActiveCN109241813ARefactoring Relationship EnhancementWeakened relationshipsCharacter and pattern recognitionPattern recognitionHat matrix
The invention provides a discriminant sparse preserving embedding method for unconstrained face recognition, 1) calculating a sample reconstruction relation matrix W, when calculating the sparse reconstructed relation of samples, the class label is introduced to construct the intra-class reconstructed relation matrix and inter-class reconstructed relation matrix respectively, and the intra-class and inter-class compactness constraint is added in the sparse reconstructed stage, which effectively increases the reconstructed relation between the samples to be tested and the same kind of samples,and weakens the reconstructed relation between the samples to be tested and the heterogeneous samples. 2) When calculating the low-dimensional projection matrix P and the low-dimensional projection matrix, the global constraint factor is added, which not only considers the local sparse relation of the sample, but also considers the global distribution characteristic, further weakens the disturbance of the heterogeneous pseudo-nearest neighbor sample to the low-dimensional projection, and more accurately excavates the essential structure of the low-dimensional manifold hidden in the complex redundant data; 3) The low-dimensional linear mapping of high-dimensional sample data is realized, which greatly improves the accuracy of face recognition in unconstrained environment.
Owner:NANJING INST OF TECH
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