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熟悉A/D轉(zhuǎn)換 軟件思路：選擇RAO做為模擬輸入通道； 連續(xù)轉(zhuǎn)換4次再求平均值做為轉(zhuǎn)換結(jié)果 最后結(jié)構(gòu)只取低8位 結(jié)果送數(shù)碼管的低3位顯示
標(biāo)簽： 轉(zhuǎn)換 RAO 8位 模擬輸入
上傳時(shí)間： 2014-01-21
上傳用戶：eclipse
軟件思路：選擇RAO做為模擬輸入通道 連續(xù)轉(zhuǎn)換4次再求平均值做為轉(zhuǎn)換結(jié)果最后結(jié)構(gòu)只取低8位結(jié)果送數(shù)碼管的低3位顯示 硬件要求：撥碼開關(guān)S14第2位置ON，第1位置OFF撥碼開關(guān)S6全部置ON，S5第4-6位置ON，第1-3位置OFF為不影響結(jié)果，其他撥碼開關(guān)置OFF。
標(biāo)簽： RAO S14 轉(zhuǎn)換 軟件
上傳時(shí)間： 2017-08-04
上傳用戶：zhouli
基于RBMCDA (Rao-Blackwellized Monte Carlo Data Association)方法的多目標(biāo)追蹤程序
標(biāo)簽： Rao-Blackwellized Association RBMCDA Monte
上傳時(shí)間： 2017-08-29
上傳用戶：tb_6877751
This paper examines the asymptotic (large sample) performance of a family of non-data aided feedforward (NDA FF) nonlinear least-squares (NLS) type carrier frequency estimators for burst-mode phase shift keying (PSK) modulations transmitted through AWGN and flat Ricean-fading channels. The asymptotic performance of these estimators is established in closed-form expression and compared with the modified Cram`er-Rao bound (MCRB). A best linear unbiased estimator (BLUE), which exhibits the lowest asymptotic variance within the family of NDA FF NLS-type estimators, is also proposed.
標(biāo)簽： performance asymptotic examines non-data
上傳時(shí)間： 2015-12-30
上傳用戶：225588
In this article, we present an overview of methods for sequential simulation from posterior distributions. These methods are of particular interest in Bayesian filtering for discrete time dynamic models that are typically nonlinear and non-Gaussian. A general importance sampling framework is developed that unifies many of the methods which have been proposed over the last few decades in several different scientific disciplines. Novel extensions to the existing methods are also proposed.We showin particular how to incorporate local linearisation methods similar to those which have previously been employed in the deterministic filtering literature these lead to very effective importance distributions. Furthermore we describe a method which uses Rao-Blackwellisation in order to take advantage of the analytic structure present in some important classes of state-space models. In a final section we develop algorithms for prediction, smoothing and evaluation of the likelihood in dynamic models.
標(biāo)簽： sequential simulation posterior overview
上傳時(shí)間： 2015-12-31
上傳用戶：225588
We present a particle filter construction for a system that exhibits time-scale separation. The separation of time-scales allows two simplifications that we exploit: i) The use of the averaging principle for the dimensional reduction of the system needed to solve for each particle and ii) the factorization of the transition probability which allows the Rao-Blackwellization of the filtering step. Both simplifications can be implemented using the coarse projective integration framework. The resulting particle filter is faster and has smaller variance than the particle filter based on the original system. The convergence of the new particle filter to the analytical filter for the original system is proved and some numerical results are provided.
標(biāo)簽： construction separation time-scale particle
上傳時(shí)間： 2016-01-02
上傳用戶：fhzm5658
％ PURPOSE : Demonstrate the differences between the following ％ filters on a simple DBN. ％ ％ 3) Particle Filter (PF) ％ 4) PF with Rao Blackwellisation (RBPF)
標(biāo)簽： Demonstrate differences the following
上傳時(shí)間： 2016-01-07
上傳用戶：cjf0304
跳變馬爾可夫模型狀態(tài)估計(jì)的粒子濾波算法研究，本文在系統(tǒng)分析傳統(tǒng)粒子濾波理論與應(yīng)用問題的基礎(chǔ)上，重點(diǎn)研究了基于跳變馬爾可夫狀態(tài)空間模型的粒子濾波算法。針對(duì)混合系統(tǒng)在二維離散狀態(tài)情形下的混合狀態(tài)估計(jì)問題，給出了基于Rao-Blackwellised粒子濾波的二維離散狀態(tài)與連續(xù)狀態(tài)的同步估計(jì)算法，一定程度上緩解了傳統(tǒng)粒子濾波算法在高維狀態(tài)空間估計(jì)中的失效問題，有效提高了狀態(tài)估計(jì)的精度。應(yīng)用數(shù)值仿真計(jì)算，對(duì)相關(guān)粒子濾波算法的性能進(jìn)行了比較分析。結(jié)果表明，本文研究的算法能夠有效完成二維離散狀態(tài)與連續(xù)狀態(tài)的同步估計(jì)，其中，二維離散狀態(tài)的估計(jì)準(zhǔn)確率達(dá)到了 96％。
標(biāo)簽： 馬爾可夫模型 狀態(tài) 粒子濾波 算法研究
上傳時(shí)間： 2013-12-12
上傳用戶：qb1993225
This paper studies the problem of tracking a ballistic object in the reentry phase by processing radar measurements. A suitable (highly nonlinear) model of target motion is developed and the theoretical Cramer—Rao lower bounds (CRLB) of estimation error are derived. The estimation performance (error mean and
標(biāo)簽： processing ballistic the tracking
上傳時(shí)間： 2014-10-31
上傳用戶：yyyyyyyyyy
This paper studies the problem of tracking a ballistic object in the reentry phase by processing radar measurements. A suitable (highly nonlinear) model of target motion is developed and the theoretical Cramer—Rao lower bounds (CRLB) of estimation error are derived. The estimation performance (error mean and
標(biāo)簽： processing ballistic the tracking
上傳時(shí)間： 2014-01-14
上傳用戶：奇奇奔奔
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