estimation problem造句
例句與造句
- So far , there is no method can solve these software cost estimation problems perfectly
目前還沒(méi)有一種單純的方法可以較好地解決軟件成本估算中的問(wèn)題。 - In order to solve the estimation problem of pn sequences itself , a code recovery algorithm based on subspace tracking is proposed
該算法通過(guò)應(yīng)用past技術(shù),求出兩個(gè)主特征向量,實(shí)現(xiàn)擴(kuò)頻碼序列的恢復(fù)。 - In addition , a novel hnn method is put forward to deal with the estimation problem of the state - space expressions of general linear dynamic systems
此外,本文還提出了一種基于輸入輸出數(shù)據(jù)的線(xiàn)性系統(tǒng)狀態(tài)空間表達(dá)式的hnn參數(shù)估計(jì)方法。 - Computation . earn a hall of fame trophy while correctly solving addition , subtraction , multiplication , division as well as equivalencies and estimation problems
計(jì)算：在正確解決加減乘除，等值及估算類(lèi)型的問(wèn)題的同時(shí)，獲得各式各樣的獎(jiǎng)杯。 - Simulation results and real - life data are used to show the feasibility of the proposed method . ls - ar spectrum method and ga - mpsv are presented to solve the estimation problems in chaotic noise
基于混沌噪聲的預(yù)測(cè)值，提出了混沌噪聲中的信號(hào)檢測(cè)方案，并進(jìn)行了相應(yīng)的仿真試驗(yàn)。 - It's difficult to find estimation problem in a sentence. 用estimation problem造句挺難的
- The optimal solu tion of real control can be obtained by means of iteratively solving the op timiz ation problem based on bilinear model and parameter estimation problem
在模型與實(shí)際存在差異的情況下，通過(guò)求解修正的基于雙線(xiàn)性模型的優(yōu)化問(wèn)題和參數(shù)估計(jì)問(wèn)題，給出了實(shí)際問(wèn)題的最優(yōu)解。 - Recent researches have showed that sea clutter can be modeled as chaotic dynamic . local prediction technique is used for detection and estimation problem in chaotic environment for radar signal processing
提出了一種基于神經(jīng)網(wǎng)絡(luò)的信號(hào)檢測(cè)方案；信號(hào)檢測(cè)解決了信號(hào)的有無(wú)判斷問(wèn)題，而參數(shù)估計(jì)則是要解決信號(hào)參量的確定問(wèn)題。 - By applying generalized svm and least square svm of classification to regression estimation problem , fuzzy generalized weighted svm and fuzzy multiplayer least square generalized svm are proposed . 3
把針對(duì)分類(lèi)問(wèn)題的廣義svm及最小二乘廣義svm用來(lái)處理回歸估計(jì)問(wèn)題，并和模糊svm結(jié)合起來(lái)形成了基于模糊加權(quán)的廣義svm和基于模糊的多層最小二乘廣義svm 。 - 6 . we discuss a new popular approach , which is called particle filter , to state estimation problem for non - linear , non - gaussian system . in addition , some potential problems of the particle filter have been presented
分析了目前廣泛應(yīng)用于非線(xiàn)性非高斯系統(tǒng)狀態(tài)估計(jì)的“粒子”濾波( particlefilter )算法的基本思想，指出其存在的問(wèn)題和可能的研究方向。 - On the basis of the perturbed karush - kuhn - tucker ( kkt ) conditions of the primal problem , this paper presents a new interior point algorithm to solve power system weighted nonlinear l ( norm ( ipwnl1 ) state and parameter estimation problem
基于原問(wèn)題的擾動(dòng)karush - kuhn - tucker ( kkt )條件，本文提出了一種新的電力系統(tǒng)加權(quán)非線(xiàn)性l1范數(shù)狀態(tài)及參數(shù)估計(jì)內(nèi)點(diǎn)算法。 - And then , the esprit bearing estimation problem . is reformulated using fourth - order cumulant matrices instead of auto - correlation matrices . by doing so , the fourth - order cumulant matrices of additive colored gaussian noises can be suppressed
在此基礎(chǔ)之上，將esprit方法擴(kuò)展到四階方法，用四階累積量矩陣代替自相關(guān)矩陣，實(shí)現(xiàn)對(duì)加性有色高斯噪聲的抑制，提高算法的估計(jì)精度。 - Later , the corresponding matching algorithm is also proposed , which provides an excellent way to motion estimation problems concerning on the dominant points detection . in the multi - target motion states analysis systems , most papers only deal with the tracking problems
多目標(biāo)運(yùn)動(dòng)分析系統(tǒng)不僅應(yīng)具有對(duì)處于正常運(yùn)動(dòng)狀態(tài)的可跟蹤能力，更應(yīng)具有對(duì)各種運(yùn)動(dòng)狀態(tài)的辨識(shí)性及跟蹤策略自適應(yīng)性。 - The main contents of this dissertation consist of the following parts : an improved unscented kalman filter using spherical simplex unscented transformation ( sukf ) is derived in an attempt to solve the attitude estimation problem with the biased gyro or not from the vector observations
主要完成了以下幾方面的工作:針對(duì)有陀螺和無(wú)陀螺兩種模式,提出了一種基于簡(jiǎn)化球形分布sigma點(diǎn)ut變換的改進(jìn)型ukf濾波( sukf )的衛(wèi)星姿態(tài)估計(jì)算法。 - Compared with classical recursive extended least squares , their accuracy obviously is improved . applying these new algorithms to the parameter estimation problem for systems with measurement noises , some new approaches and algorithms of parameter estimation for system with measurement noises , are presented , for example , two - stage rels - gevers - wouters algorithm and three - stage rls - pi - gevers - wouters algorithm , which solve the biased parameter estimation problem by classical least squares method
并將這些算法推廣到帶觀測(cè)噪聲系統(tǒng)參數(shù)估計(jì)的問(wèn)題，給出了帶觀測(cè)噪聲系統(tǒng)參數(shù)估計(jì)的一些新方法和新算法，其中包括兩段rels - gevers - wouters算法和三段rls - pi - gevers - wouters算法，解決了用普通最小二乘法估計(jì)帶觀測(cè)噪聲系統(tǒng)未知參數(shù)的有偏問(wèn)題。 - Particle filter can deal those nonlinear and nongaussian estimation problems , and what ' s more , it does n ' t need the measurement equation which is hard to build in face tracking . experiments results demonstrate the algorithm is effective under complex situation such as changing background and partial occlusion
考慮到遮擋以及人運(yùn)動(dòng)的不確定性和非線(xiàn)性等因素，基于粒子濾波的跟蹤算法無(wú)需給出量測(cè)方程，且當(dāng)目標(biāo)發(fā)生遮擋時(shí)能夠自適應(yīng)的改變搜索空間，實(shí)驗(yàn)分析證明了該算法的有效性。
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