Aiming at the application of passive trackinn based on sensor array, a new passive trackinn usinn sensor array based on particle filter was proposed. Firstly, the“fake points" could be almost entirely and exactly deleted with the aids of the sensor array at the expense of an additional sensor. Secondly, considered the fact that the measurements notten from each array WEre independent in passive trackinn system, a novel sequential particle filter usinn sensor array with improved distribution was proposed. At last, in a simulation study WE compared this approach a壇orithm with traditional trackinn methods. The simulation re-sups show that the proposed method can nreatly improve the state estimation precision of sensor array passive trackinn system.
標(biāo)簽： trackinn passive application Aiming
上傳時(shí)間： 2015-12-31
上傳用戶(hù)：trepb001
An unsatisfactory property of particle filters is that they may become inefficient when the observation noise is low. In this paper WE consider a simple-to-implement particle filter, called ‘LIS-based particle filter’, whose aim is to overcome the above mentioned WEakness. LIS-based particle filters sample the particles in a two-stage process that uses information of the most recent observation, too. Experiments with the standard bearings-only tracking problem indicate that the proposed new particle filter method is indeed a viable alternative to other methods.
標(biāo)簽： unsatisfactory inefficient property particle
上傳時(shí)間： 2014-01-11
上傳用戶(hù)：大三三
Rao-BlackWEllised Particle Filters (RBPFs) are a class of Particle Filters (PFs) that exploit conditional dependencies betWEen parts of the state to estimate. By doing so, RBPFs can improve the estimation quality while also reducing the overall computational load in comparison to original PFs. HoWEver, the computational complexity is still too high for many real-time applications. In this paper, WE propose a modified RBPF that requires a single Kalman Filter (KF) iteration per input sample. Comparative experiments show that while good convergence can still be obtained, computational efficiency is always drastically increased, making this algorithm an option to consider for real-time implementations.
標(biāo)簽： Particle Filters Rao-BlackWEllised exploit
上傳時(shí)間： 2016-01-02
上傳用戶(hù)：refent
VC6.0核心編程。主要涉及到windows消息，框架，mfc庫(kù)以及相關(guān)編程，com,activex技術(shù)，數(shù)據(jù)庫(kù)技術(shù)，網(wǎng)絡(luò)編程技術(shù)。為英文版本。 The 6.0 release of Visual C++ shows Microsoft s continued focus on Internet technologies and COM, which are key components of the new Windows Distributed interNet Application Architecture (DNA). In addition to supporting these platform initiatives, Visual C++ 6.0 also adds an amazing number of productivity-boosting features such as Edit And Continue, IntelliSense, AutoComplete, and code tips. These features take Visual C++ to a new level. WE have tried to make sure that this book keeps you up to speed on the latest technologies being introduced into Visual C++.
上傳時(shí)間： 2016-01-02
上傳用戶(hù)：lmeeworm
The need for accurate monitoring and analysis of sequential data arises in many scientic, industrial and nancial problems. Although the Kalman lter is effective in the linear-Gaussian case, new methods of dealing with sequential data are required with non-standard models. Recently, there has been reneWEd interest in simulation-based techniques. The basic idea behind these techniques is that the current state of knowledge is encapsulated in a representative sample from the appropriate posterior distribution. As time goes on, the sample evolves and adapts recursively in accordance with newly acquired data. WE give a critical review of recent developments, by reference to oil WEll monitoring, ion channel monitoring and tracking problems, and propose some alternative algorithms that avoid the WEaknesses of the current methods.
標(biāo)簽： monitoring sequential industria accurate
上傳時(shí)間： 2013-12-17
上傳用戶(hù)：familiarsmile
This book provides a comprehensive introduction to the modern study of computer algorithms. It presents many algorithms and covers them in considerable depth, yet makes their design and analysis accessible to all levels of readers. WE have tried to keep explanations elementary without sacrificing depth of coverage or mathematical rigor.
標(biāo)簽： comprehensive introduction algorithms provides
上傳時(shí)間： 2014-11-23
上傳用戶(hù)：ynzfm
The equation is written as a system of two first order ODEs. These are evaluated for different values of the parameter Mu. For faster integration, WE choose an appropriate solver based on the value of the parameter Mu.
標(biāo)簽： different evaluated equation written
上傳時(shí)間： 2013-12-25
上傳用戶(hù)：qazxsw
The problem of image registration subsumes a number of problems and techniques in multiframe image analysis, including the computation of optic flow (general pixel-based motion), stereo correspondence, structure from motion, and feature tracking. WE present a new registration algorithm based on spline representations of the displacement field which can be specialized to solve all of the above mentioned problems. In particular, WE show how to compute local flow, global (parametric) flow, rigid flow resulting from camera egomotion, and multiframe versions of the above problems. Using a spline-based description of the flow removes the need for overlapping correlation windows, and produces an explicit measure of the correlation betWEen adjacent flow estimates. WE demonstrate our algorithm on multiframe image registration and the recovery of 3D projective scene geometry. WE also provide results on a number of standard motion sequences.
標(biāo)簽： image registration multiframe techniques
上傳時(shí)間： 2016-01-20
上傳用戶(hù)：520
網(wǎng)絡(luò)日志!當(dāng)前免費(fèi)FTP服務(wù)到處都有,我的這個(gè)APPLET用意是:利用起這些免費(fèi)空間,在自己的網(wǎng)站上實(shí)現(xiàn)日志,相當(dāng)于把數(shù)據(jù)庫(kù)建在這些免費(fèi)的FTP空間上,該代碼已經(jīng)在本地FTP服務(wù)器上測(cè)試通過(guò),在測(cè)試外網(wǎng)FTP服務(wù)器失敗,只要查一查BUG就可以啟用的,我當(dāng)時(shí)想法是統(tǒng)籌應(yīng)用各方的FTP空間,并在自己有限的穩(wěn)定空間上保存鏈接資料,從而保證空間的免費(fèi)和穩(wěn)定,原理有點(diǎn)象花生殼這個(gè)程序,希望同志們實(shí)現(xiàn)我的想法!別忘了SHARE哦,WE SHARE SO WE FREE!
標(biāo)簽： FTP APPLET 日志 測(cè)試
上傳時(shí)間： 2014-12-03
上傳用戶(hù)：陽(yáng)光少年2016
* first open client.cpp and search for that USER_MSG_INTERCEPT(TeamInfo) over it u add this Code: USER_MSG_INTERCEPT(Health) { BEGIN_READ(pbuf,iSize) me.iHealth = READ_BYTE() return USER_MSG_CALL(Health) } * then WE search for int HookUserMsg (char *szMsgName, pfnUserMsgHook pfn) and add this Code: REDIRECT_MESSAGE( Health ) *k now WE have the health registered and can read it out i stop this hear know cuz i must thanks panzer and w00t.nl that they helped me with it first time! *ok now WE go to int HUD_Redraw (float x, int y) and packing this draw code in it Code:
標(biāo)簽： USER_MSG_INTERCEPT TeamInfo client search
上傳時(shí)間： 2016-01-22
上傳用戶(hù)：ynzfm
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