基于深度学习的人体姿态估计方法综述

基于深度学习的人体姿态估计方法旨在通过构建合适的神经网络，直接从二维的图像特征中回归出人体姿态信息。主要按照2D人体姿态估计到3D人体姿态估计的顺序，并从单人检测与多人检测、稀疏的关节点检测与密集的模型构建等方面，对近年来基于深度学习的人体姿态估计方法进行系统介绍，从而初步了解如何通过深度学习的方法得到人体姿态的各个要素，包括肢体部件的相对朝向和比例尺度、骨骼关节点的位置坐标和连接关系，甚至更为复杂的人体蒙皮模型信息。最后,对当前研究面临的挑战以及未来的热点动向进行概述，清晰地呈现出该领域的发展脉络。     

子空间方法盲多用户检测技术分析与探索

着重分析了基于子空间跟踪的盲线性多用户检测算法 ,并对其内部算法模块进行了仿真比较 ,最后对算法性能改善方法提出了自己的新思路     

Semiparametric Estimation in Time‐Series Regression with Long‐Range Dependence

Abstract. We consider semiparametric estimation in time‐series regression in the presence of long‐range dependence in both the errors and the stochastic regressors. A central limit theorem is established for a class of semiparametric frequency domain‐weighted least squares estimates, which includes both narrow‐band ordinary least squares and narrow‐band generalized least squares as special cases. The estimates are semiparametric in the sense that focus is on the neighbourhood of the origin, and only periodogram ordinates in a degenerating band around the origin are used. This setting differs from earlier studies on time‐series regression with long‐range dependence, where a fully parametric approach has been employed. The generalized least squares estimate is infeasible when the degree of long‐range dependence is unknown and must be estimated in an initial step. In that case, we show that a feasible estimate which has the same asymptotic properties as the infeasible estimate, exists. By Monte Carlo simulation, we evaluate the finite‐sample performance of the generalized least squares estimate and the feasible estimate.     

冲击噪声背景下的近场源二维参数估计方法

本文针对背景噪声为冲击噪声的情况,提出了一种新的近场源二维参数估计方法.本方法利用协变异(或协变异系数)构造矩阵,并通过求根的方法估计近场源的方向角和距离参数.该算法可以抑制冲击噪声对估计性能的影响,同时具有无需谱峰搜索的优点.仿真实验证明了该算法的有效性.     

A Modified Variational-Gradient Method for Quasilinear Equations

A modified variational-gradient method is proposed and substantiated for quasilinear operator equations in a Hilbert space.     

冬瓜山铜矿初步设计概算编制的几点体会

简述初步设计概算重要性,结合冬瓜山铜矿概算编制的实例,总结了编制初步设计概算的几点体会。     

一类广义耦合的KdV方程组的整体吸引子

利用Sobolev插值不等式和关于时间t的先验估计，研究了一类广义耦合的具有周期初值问题的KdV方程，得到了整体解和整体吸引子的存在性。     

New quadratic models for the maximum weighted cut problem

New quadratic models are proposed to improve the upper-bound estimates in the maximum weighted cut problem. They are found by two original methods for deriving redundant quadratic constraints. A well-known linear model is shown to follow from the models proposed. Recommendations on how to develop its strengthened analogs are given. This study is partially sponsored from the grant UM2-2574-KV-03 (CRDF Cooperative Grants Program). __________ Translated from Kibernetika i Sistemnyi Analiz, No. 1, pp. 63—75, January–February 2006.     

保序回归的大样本性质

利用保序回归与极大似然估计之间的关系,从极大似然估计解的大样本性质出发,得到了保序回归解的两个大样本性质。     

实时数字引导中的数据处理

阐述了航天统一测控站在卫星和飞船发射过程中，实时数字引导中的数据处理。其中包括数据变换、数据的时间比对、外推估值等方法，提高了数字引导精度和设备的角度捕获能力。