Randomly Weighted CKF for Multisensor Integrated Systems

Information Measures for Multisensor Systems

On Weighted Randomly Trimmed Means

A class of robust location estimators called weighted randomly trimmed means are introduced and not only their consistency and asymptotic normality are proved, but their influence functions, asymptotic variances and breakdown points are also derived. They possess the same breakdown points as the median, and some of them own higher asymptotic relative efficiencies at the heavy-tailed distributio...

channel estimation for mimo-ofdm systems

تخمین دقیق مشخصات کانال در سیستم های مخابراتی یک امر مهم محسوب می گردد. این امر به ویژه در کانال های بیسیم با ‏خاصیت فرکانس گزینی و زمان گزینی شدید، چالش بزرگی است. مقالات متعدد پر از روش های مبتکرانه ای برای طراحی و آنالیز ‏الگوریتم های تخمین کانال است که بیشتر آنها از روش های خاصی استفاده می کنند که یا دارای عملکرد خوب با پیچیدگی ‏محاسباتی بالا هستند و یا با عملکرد نه چندان خوب پیچیدگی پایینی...

Implementation of microcontroller-aided PC104 platform for multisensor integrated system

The GPS-aided MEMS-based inertial navigation system is a topic of current interest by many researches. The performance of such systems relies on not only the quality of the MEMS inertial sensors, or the quality of GPS measurements and the geometry of the satellite constellation, but also implementation of time synchronisation of GPS and INS sensors on the integration platforms. The pseudolite-b...

Randomly weighted series of iid’s in L1

Let (Yk) be an integrable sequence of iid random variables defined on the probability space (Y,F , μ). We prove that there exists a subset Y ∗ ⊂ Y of full measure such that for each y ∈ Y ∗ the following holds: for every integrable iid sequence (Xk) on a probability space (X, ,m), the series lim n→∞ n ∑′ k=−n Yk(y)Xk(x) k converges for almost every x ∈ X.