41 results about "Non negativity" patented technology

Methods are provided for iteratively reconstructing an image signal to generate a reconstructed image signal. In one embodiment, sub-iterations of each iteration are performed on pixel or voxel subsets. The subsets may be composed of neighboring or spatially separated pixel or voxels and may extend in the z-direction. In one embodiment, an update step of the iterative reconstruction involves the direct inversion of an approximation of a Hessian matrix associated with the respective subsets. In further embodiments, non-negativity or other limitations or constraints on update values may be enforced.

A method for determining interior coordinates is disclosed. The method includes receiving information specifying an object having a plurality of sites and a boundary. Interior coordinates associated with each of the plurality of sites are determined based on the boundary. The interior coordinate associated with each of the plurality of sites represent a system of coordinates that satisfy several properties, including non-negativity and interior locality. At least one value associated with the plurality of sites is then interpolated using the interior coordinates.

The invention relates to a low-field nuclear magnetic resonance (NMR) two-dimensional spectrum inversion algorithm which extends a PDCO (a primitive dual interior point method for convex objectives) to two-dimensional space for solving a two-dimensional inversion problem. Compared with other low-field NMR inversion algorithms reported in domestic and foreign literatures, the inversion algorithm of the invention uses L1 regularization and L2 regularization instead of just the L2 regularization, thereby getting closer to the sparseness of an original signal and acquiring spectral distribution that may more reflect a reality. The PDCO can ensure the non-negativity of a solution, and does not need additional nonnegative constraint calculation, which simplifies an inversion process. The inversion algorithm of the invention can also distinguish closely adjacent peaks and achieves high computational accuracy. The inversion algorithm of the invention has good robustness and may obtain stable inversion results under different SNR data.

The disclosed apparatus, systems and methods relate to a framelet-based iterative algorithm for polychromatic CT which can reconstruct two components using a single scan. The algorithm can have various steps including a scaled-gradient descent step of constant or variant step sizes; a non-negativity step; a soft thresholding step; and a color reconstruction step.

The invention discloses a method and a device for configuring the water resource. The method comprises the steps of A, establishing an optimized model by taking land utilization maximization and water consumption minimization as a goal and taking surface water capacity constraint, available water capacity constraint of underground water, surface water irrigation proportion constraint, irrigation water requirement constraint, land utilization constraint, water reservoir capacity constraint and irrigation water capacity non-negativity constraint as constraint conditions; B, disassembling the optimized model into an upper bound sub model and a lower bound sub model according to a region interactive algorithm, introducing penalty coefficients through a type-2 fuzzy type reduction method, converting the upper bound sub model and the lower bound sub model into corresponding linear programming models, and solving the linear programming models; C, selecting different underground water use proportions, bringing the different underground water use proportions into the optimized model to compute, and obtaining a relationship between the underground water use proportions and a crop planting structure. By utilizing the method and the device, disclosed by the invention, the plan on water resource utilization under multiple uncertain conditions can be carried out, and a reasonable agricultural irrigation method can be provided.

Systems and methods for managing components of physical systems, including decomposing raw time series by extracting an aging trend and a fluctuation term from the time series using an objective function of an optimization problem, the objective function minimizing reconstruction error and ensuring flatness of the fluctuation term over time. The optimization problem is transformed into a Quadratic Programming (QP) formulation including a monotonicity constraint and a non-negativity constraint, the constraints being merged together to reduce computational costs. An aging score and a confidence score are generated for the extracted aging trend to determine a severeness of aging for one or more components of the physical system, and the aging score and confidence score are fused to provide a fused ranking for the extracted aging trend for predicting future failures of the components.