Recently, freestanding lms have attracted much attention because they are highly useful in the fabrication of various nanodevices. Freestanding lms can be used on any substrate without deterioration of their own unique properties. Layerby-layer (LBL) deposition has been used widely in the synthesis of freestanding lms, especially of polymer lms with specic physical and mechanical propertie...

The paper proposes a new adaptive VS LMS algorithm, obtained by combining LMS algorithms with different step sizes without calculating their weighting coefficients. As a criterion for choosing the VS LMS algorithm step size, we take the ratio between the weighting coefficients' bias and variance. Identification of an unknown system in nonstationary noisy environment is performed and simulations...

There has been recent trend towards the adoption of cloud-based Learning Management Systems (LMS). The benefits of cloud-based LMS systems include reduced costs and increased productivity resulting from sophisticated course development features, online course delivery, and anytime and anywhere availability of courses. Following the evaluation of a range of commercially available LMS platforms a...

| Based on the least mean squares (LMS) algorithm , the LMS spectrum analyzer can be used to re-cursively calculate the discrete Fourier transform (DFT) of a sliding window of data. In this paper, we compare the LMS spectrum analyzer with the straightforward non-adaptive implementation of the recursive DFT. In particular , we demonstrate the robustness of the LMS spectrum analyzer to the propag...

In this paper, e cient pipelined architectures for the implementation of the Transform Domain LMS algorithm, are presented. Pipelining of the TD-LMS algorithm is achieved by introducing an amount of time delay into the original adaptive scheme. The adaptation delay introduced to the TD-LMS algorithm allows for the development of pipelined architectures. By retiming the delays existing in the er...

The least mean squares (LMS) algorithm is one of the most popular recursive parameter estimation methods. In its standard form it does not take into account any special characteristics that the parameterized model may have. Assuming that such model is sparse in some domain (for example, it has sparse impulse or frequency response), we aim at developing such LMS algorithms that can adapt to the ...

The hardness and stress of amorphous carbon lms prepared by glow discharge and by ion beam assisting deposition are investigated. Relatively hard and almost stress free amorphous carbon lms were deposited by the glow discharge technique. On the other hand, by using the ion beam assisting deposition, hard lms were also obtained with a stress of the same order of those found in tetrahedral amorph...

In this paper we report results on the synthesis and magnetic properties of L10 FePt nanocomposite fi lms. Three fabrication methods have been developed to produce high-anisptropy FePt fi lms: non-epitaxial growth of (0 0 1)-oriented FePt:X (X=Ag, C) composite fi lms that might be used for perpendicular media; monodispersed FePt(CFx) core–shell nanocluster-assembled fi lms grown with a gas-aggr...

An adaptive filter is defined as a digital filter that has the capability of self adjusting its transfer function under the control of some optimizing algorithms. Most common optimizing algorithms are Least Mean Square (LMS) and Recursive Least Square (RLS). Although RLS algorithm perform superior to LMS algorithm, it has very high computational complexity so not useful in most of the practical...

LMS (Lernmanagement-Systeme) beinhalten bei flächendeckendem Einsatz kursspezifische Informationen, die bei der Erstellung und der Verwaltung von Vorlesungsaufzeichnungen umfangreiche Automatisierungspotenziale bieten. Durch Ansteuerung der Vorlesungsaufzeichnung aus dem LMS können Metadaten automatisch in die Aufzeichnung einfließen. Auch die Ansteuerung der zur Aufzeichnung benötigten Hörsaal...