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Class of Widely Linear Complex Kalman Filters Abstract——Recently,a class of widely linear (augmented) complex-valued Kalman filters,that make use of augmented complex statistics, have been proposed for sequential state space estimation of thegenerality of complex signals.This was achieved in the context of neural network training, and has allowed for a unified treatment of both second-order circular and noncircular signals ,that is ,both those with rotation invariant and rotation-dependent distributions. In this paper, we revisit the augmented complex KF,augmented complex extended KF ,and augmented complex unscented Kf in a more general comtext,and analyze their performance for different degrees of noncircularity of input and the state and measurement noises. For rigor,a theoretical bound for the performance advantage of widely linear KFs over their strictly linear counterparts is provided.The analysis also addresses the duality with bivariate real-valued KFs,together with several issues of implementation.Simulations using both synthetic and real world proper and inproper signals support the analysis. |
榮譽(yù)版主 (文壇精英)
如影隨行
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專家經(jīng)驗: +3 |
| 類線性復(fù)雜廣泛的卡爾曼濾波器抽象——最近,一個類廣泛的線性(擴(kuò)大)復(fù)雜的卡爾曼濾波器價值,使使用復(fù)雜的統(tǒng)計數(shù)字增加,建議連續(xù)狀態(tài)空間的thegenerality估計的復(fù)雜信號.這是在這一范疇內(nèi)取得的神經(jīng)網(wǎng)絡(luò)訓(xùn)練,使人們對一個統(tǒng)一處理的第二個訂單通知,noncircular信號,這就是,這兩個旋轉(zhuǎn)不變和旋轉(zhuǎn)的分布。 |

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