4 results about "Relaxation algorithm" patented technology

The application discloses a method for designing and optimizing a VLCP system assisted by light reflection RIS under low signal-to-noise ratio, wherein the VLCP system comprises an intelligent wall adopting a smart surface RIS with mirror reflection, a transmitter and a user terminal equipped with a receiver with a liquid crystal smart surface, communication and positioning signals are integrated into the transmitter, the transmitter comprises an LED, and the method comprises the following steps: under low signal-to-noise ratio, taking asymptotic capacity as a communication metric constraint condition, taking a Cramer-Rao lower bound of positioning error as a positioning metric constraint condition, combining a positioning constraint satisfaction process based on a two-stage greedy algorithm and a communication performance maximization process based on a greedy strategy convex relaxation algorithm, optimizing elements of an RIS allocation matrix to maximize the asymptotic capacity, obtaining an optimal RIS allocation matrix, and completing the design and optimization of the VLCP system. In a low signal-to-noise ratio scene, the VLCP system of the application can significantly improve system performance by applying RIS.

A method and device for optimizing train departure path and timetable cooperatively, the method comprising: constructing a space-time state network for describing the operation of a train bottom; based on the space-time state network, constructing a train departure path and timetable cooperative optimization model; wherein the train departure path and timetable cooperative optimization model comprises a model for minimizing the space-time state path cost of the train bottom leaving a section and corresponding constraint conditions; using a Lagrange relaxation algorithm to transform the train departure path and timetable cooperative optimization model, and using a dynamic programming algorithm to solve the model to obtain an optimal train departure path and timetable. Through the method and device provided in the embodiment of the application, the train operation cost can be effectively reduced while the travel time of passengers is shortened, and the method can be used for assisting actual transportation production and improving the overall quality of train operation plans in departure time periods.

This invention relates to a multi-dimensional confidence-based point-line fusion SLAM method and system for visually degraded environments, belonging to the fields of computer vision and robot navigation technology. The invention constructs a nonlinear mapping function based on two-dimensional image entropy, dynamically adjusts the gradient threshold and Gaussian smoothing parameters of the line feature extraction algorithm, and introduces a sudden illumination safety mode to enhance adaptability to extreme environments. It performs photometric consistency verification on point features after optical flow tracking, performs region growing on line features using the aforementioned adaptive parameters, and proposes a hierarchical non-convex relaxation algorithm guided by dual weights of geometric residuals and pixel gradients for noise-resistant fitting. It establishes a linear inverse mapping mechanism between front-end feature confidence and back-end optimization information matrix, dynamically adjusting residual weights according to feature quality. In motion-blurred and illumination-changing environments, it can effectively extract high-quality features and perform tight-coupling optimization, improving the positioning accuracy and speed of the SLAM system in weak-texture and drastically changing illumination environments.

The present application relates to the technical field of power system operation control, and specifically to a parallel accelerated solution method for post-disaster restoration of a power system based on quantum computing, including: step 1: establishing a model for post-disaster restoration; step 2: according to the quantum proxy Lagrangian relaxation algorithm, decomposing an original optimization problem into node subproblems; and step 3: solving the model for post-disaster restoration, updating Lagrange multipliers and penalty factors in iteration, achieving an optimal solution under the interaction of quantum computing and classical computing, and accelerating the acquisition of a restoration plan to guide a safe operation of the power system. The present application decomposes a problem into subproblems and divides the subproblems into discrete and continuous parts for solution, reducing the difficulty. The effects of parallel computing and quantum-embedding accelerated computing are realized without complete optimization for a relaxed problem, ensuring better convergence.