We consider the problem of target localization by a network of passive sensors. When an unknown target emits an acoustic or a radio signal, its position can be localized with multiple sensors using the time difference of arrival (TDOA) information. In this paper, we consider the maximum likelihood formulation of this target localization problem and provide efficient convex relaxations for this nonconvex optimization problem.We also propose a formulation for robust target localization in the presence of sensor location errors. Two Cramer-Rao bounds are derived corresponding to situations with and without sensor node location errors. Simulation results confirm the efficiency and superior performance of the convex relaxation approach as compared to the existing least squares based approach when large sensor node location errors are present.
標(biāo)簽： 傳感器網(wǎng)絡(luò)
上傳時(shí)間： 2016-11-27
上傳用戶：xxmluo
System identification with adaptive filter using full and partial-update Least-Mean-Squares
標(biāo)簽： Least-Mean-Squares identification partial-update adaptive
上傳時(shí)間： 2014-01-02
上傳用戶：bibirnovis
System identification with adaptive filter using full and partial-update Normalised-Least-Mean-Squares
標(biāo)簽： Normalised-Least-Mean-Squar identification partial-update adaptive
上傳時(shí)間： 2017-09-13
上傳用戶：leixinzhuo
System identification with adaptive filter using full and partial-update Transform-Domain Least-Mean-Squares
標(biāo)簽： Transform-Domain identification partial-update Least-Mean
上傳時(shí)間： 2014-01-12
上傳用戶：ztj182002
recursive:數(shù)據(jù)結(jié)構(gòu)(黃國(guó)瑜 葉乃菁 編著)中的遞歸例子
標(biāo)簽： recursive 數(shù)據(jù)結(jié)構(gòu) 遞歸
上傳時(shí)間： 2013-11-26
上傳用戶：上善若水
The Linux kernel is one of the most interesting yet least understood open-source projects. It is also a basis for developing new kernel code. That is why Sams is excited to bring you the latest Linux kernel development information from a Novell insider in the second edition of Linux Kernel Development. This authoritative, practical guide will help you better understand the Linux kernel through updated coverage of all the major subsystems, new features associated with Linux 2.6 kernel and insider information on not-yet-released developments. You ll be able to take an in-depth look at Linux kernel from both a theoretical and an applied perspective as you cover a wide range of topics, including algorithms, system call interface, paging strategies and kernel synchronization. Get the top information right from the source in Linux Kernel Development.
標(biāo)簽： interesting open-source understood projects
上傳時(shí)間： 2015-06-30
上傳用戶：zyt
控制行業(yè)中重要的least square parameter solution，里面使用了一個(gè)例子，可以將輸入改變?nèi)缓笫褂?/p>
標(biāo)簽： parameter solution square least
上傳時(shí)間： 2014-02-13
上傳用戶：tb_6877751
The Linux kernel is one of the most interesting yet least understood open-source projects. It is also a basis for developing new kernel code. That is why Sams is excited to bring you the latest Linux kernel development information from a Novell insider in the second edition of Linux Kernel Development. This authoritative, practical guide will help you better understand the Linux kernel through updated coverage of all the major subsystems, new features associated with Linux 2.6 kernel and insider information on not-yet-released developments. You ll be able to take an in-depth look at Linux kernel from both a theoretical and an applied perspective as you cover a wide range of topics, including algorithms, system call interface, paging strategies and kernel synchronization. Get the top information right from the source in Linux Kernel Development.
標(biāo)簽： interesting open-source understood projects
上傳時(shí)間： 2015-07-26
上傳用戶：mpquest
Least Square - ARMA 算法的MATLAB代碼, 是頻譜分析(通常是在高級(jí)DSP這門課中會(huì)用到的)的常用算法
標(biāo)簽： Square MATLAB Least ARMA
上傳時(shí)間： 2013-12-21
上傳用戶：zhangjinzj
卡爾曼濾波C程序 卡爾曼濾波器是一個(gè)“optimal recursive data processing algorithm（最優(yōu)化自回歸數(shù)據(jù)處理算法）”。 對(duì)于解決很大部分的問(wèn)題，他是最優(yōu)，效率最高甚至是最有用的。他的廣泛應(yīng)用已經(jīng)超過(guò)30年，包括機(jī)器人導(dǎo)航，控制， 傳感器數(shù)據(jù)融合甚至在軍事方面的雷達(dá)系統(tǒng)以及導(dǎo)彈追蹤等等。近年來(lái)更被應(yīng)用于計(jì)算機(jī)圖像處理， 例如頭臉識(shí)別，圖像分割，圖像邊緣檢測(cè)等等。
標(biāo)簽： processing algorithm recursive optimal
上傳時(shí)間： 2013-12-19
上傳用戶：pinksun9
蟲(chóng)蟲(chóng)下載站版權(quán)所有 京ICP備2021023401號(hào)-1
