Search - set of complex number

Search - set of complex number - List

[Other] makefile DL : 0: makefile关系到了整个工程的编译规则。一个工程中的源文件不计数，其按类型、功能、模块分别放在若干个目录中，makefile定义了一系列的规则来指定，哪些文件需要先编译，哪些文件需要后编译，哪些文件需要重新编译，甚至于进行更复杂的功能操作。-related to the makefile to compile the whole project and the rules. A project in the source file does not count, its by type, function, modules were placed in a number of directory, makefile defines a set of rules to specify which files need to compile, after which files need to compile, which files need to re- compilation, and even more complex functions.
Date : 2025-12-29 Size : 416kb User :
[Other] ANEWDATAASSOCIAT-SISDENSITYFILTER DL : 0: 为了避免引入复杂的随机有限集 (Random finite set, RFS) 理论, 本文根据 PHD 的物理空间 (Physical space) 描述法推导得到了 MM-PHD 平滑器的后向更新公式. 由于 MM-PHD 前向–后向平滑器的递推公式中包含有多个积分, 因此它在非线性非高斯条件下没有解析的表达形式. 故本文又给出了它的序贯蒙特卡洛 (Sequential Monte Carlo, SMC) 实现. 100 次蒙特卡洛 (Monte Carlo, MC) 仿真实验表明, 与 MM-PHD 滤波器相比, MM-PHD 平滑器能够更加精确地估计多个机动目标的个数和状态, 但 MM-PHD 平滑器存在一定的时间滞后, 并且需要耗费更大的计算代价-To avoid use of complex random finite set (RFS) theory, the backward updated equation of the MM-PHD smoother can be derived according to the physical-space explanation of the PHD. Since the MM-PHD forward-backward smoother involves multiple integrals, this renders its recursion analytically intractable in the nonlinear and non-Gaussian conditions. Thus, the sequential Monte Carlo (SMC) method is used to implement the smoother. 100 Monte Carlo (MC) simulation results show that the proposed MM-PHD smoother significantly outperforms the MM-PHD filter in estimating the number and states of the multiple maneuvering targets, although the MM-PHD smoother will have time lag and more expansive computation requirement
Date : 2025-12-29 Size : 522kb User : 正东