Abstract: The present disclosure provides a virtual machine management method and apparatus. The method includes: acquiring virtual machine information of each virtual machine in a virtualization platform, receiving a first onboarding operation instruction for a target virtual machine in the virtualization platform, configuring a network and a virtual network console VNC of the target virtual machine, and when the configuration succeeds, storing in an already-onboarded virtual machine list in a database table virtual machine information of the target virtual machine. With the application of examples of the present disclosure, a unified management and control of virtual machines in the virtualization platform by a cloud management platform can be realized.

Abstract: The present invention provides a MIMO transmission method for discrete modulated signals. The method is mainly characterized in maximizing the mutual information of symbol vectors of a transmitter and a receiver by joint optimization of a source distribution and a precoding matrix. When the current precoding matrix G is determined, the distribution of source multi-dimensional vectors x is maximized by a Lagrange multiplier method to maximize a source entropy; and when the distribution of the current source multi-dimensional vectors x is determined, the precoding matrix G is optimized by a gradient descent method to maximize the mutual information of the transmitted and received vectors. The transmission rate approximates the Shannon limit under a MIMO scenario by joint optimization of the source distribution and the precoding matrix. After the transmitter determines a marginal distribution of symbols of each channel, a non-uniform modulation is performed by using a probabilistic amplitude shaping technology.

Abstract: The present invention provides a MIMO transmission method for discrete modulated signals. The method is mainly characterized in maximizing the mutual information of symbol vectors of a transmitter and a receiver by joint optimization of a source distribution and a precoding matrix. When the current precoding matrix G is determined, the distribution of source multi-dimensional vectors x is maximized by a Lagrange multiplier method to maximize a source entropy; and when the distribution of the current source multi-dimensional vectors x is determined, the precoding matrix G is optimized by a gradient descent method to maximize the mutual information of the transmitted and received vectors. The transmission rate approximates the Shannon limit under a MIMO scenario by joint optimization of the source distribution and the precoding matrix.

Abstract: The invention discloses a method for three-dimensional human pose estimation, which can realize the real-time and high-precision 3D human pose estimation without high configuration hardware support and precise human body model. In this method for three-dimensional human pose estimation, including the following steps: (1) establishing a three-dimensional human body model matching the object, which is a cloud point human body model of visible spherical distribution constraint. (2) Matching and optimizing between human body model for human body pose tracking and depth point cloud. (3) Recovering for pose tracking error based on dynamic database retrieval.

Abstract: The invention discloses a method for three-dimensional human pose estimation, which can realize the real-time and high-precision 3D human pose estimation without high configuration hardware support and precise human body model. In this method for three-dimensional human pose estimation, including the following steps: (1) establishing a three-dimensional human body model matching the object, which is a cloud point human body model of visible spherical distribution constraint. (2) Matching and optimizing between human body model for human body pose tracking and depth point cloud. (3) Recovering for pose tracking error based on dynamic database retrieval.

Abstract: The present disclosure provides a virtual machine management method and apparatus. The method includes: acquiring virtual machine information of each virtual machine in a virtualization platform, receiving a first onboarding operation instruction for a target virtual machine in the virtualization platform, configuring a network and a virtual network console VNC of the target virtual machine, and when the configuration succeeds, storing in an already-onboarded virtual machine list in a database table virtual machine information of the target virtual machine. With the application of examples of the present disclosure, a unified management and control of virtual machines in the virtualization platform by a cloud management platform can be realized.