Large-area, freestanding, two-dimensionally ordered macroporous (2DOM) Ag thin fi lms with adjustable periodic spacings and good mechanical robustness were fabricated via nanosphere lithography at the solution surface (NSLSS) combined with interfacial reactions. The obtained 2DOM Ag thin fi lms exhibited typical properties of plasmonic crystals with wellresolved refl ectivity dips and vivid col...

As one of the recently proposed algorithms for sparse system identification, l0 norm constraint Least Mean Square (l0-LMS) algorithm modifies the cost function of the traditional method with a penalty of tap-weight sparsity. The performance of l0-LMS is quite attractive compared with its various precursors. However, there has been no detailed study of its performance. This paper presents compre...

Abstract Beidou-3 (BD3) uses the pseudo range transmission method to calculate clock difference through range. However, due influence of electromagnetic interference, measurement error is too large, which affects timing accuracy power system. This paper first introduces principle Beidou service; Secondly, it calculation method; Finally, combined with method, this presents an anti-interference c...

Objective: This study aims to explore research trends related the use of Massive Open Online Courses in Learning Management Systems (MOOCs LMS) university environments and conduct bibliometric analysis understand developments this topic. learning is increasingly popular with MOOCs LMS, which allows students learn flexibly independently through digital platforms. Method: The data retrieved from ...

In this paper, we propose two novel p-norm penalty least mean square (lp-LMS) algorithms as supplements of the conventional lp-LMS algorithm established for sparse adaptive filtering recently. A gradient comparator is employed to selectively apply the zero attractor of p-norm constraint for only those taps that have the same polarity as that of the gradient of the squared instantaneous error, w...

In a distributed network environment, the diffusion-least mean squares (LMS) algorithm gives faster convergence than the original LMS algorithm. It has also been observed that, the diffusion-LMS generally outperforms other distributed LMS algorithms like spatial LMS and incremental LMS. However, both the original LMS and diffusion-LMS are not applicable in non-linear environments where data may...

In this paper, we consider the steady state mean square error (MSE) analysis for 2-D LMS adaptive filtering algorithm in which the filter’s weights are updated along both vertical and horizontal directions as a doubly-indexed dynamical system. The MSE analysis is conducted using the well-known independence assumption. First we show that computation of the weight-error covariance matrix for doub...

This paper presents a new approach to single-channel speech enhancement involving both noise and channel distortion (i.e., convolutional noise). The approach is based on finding longest matching segments (LMS) from a corpus of clean, wideband speech. The approach adds three novel developments to our previous LMS research. First, we address the problem of channel distortion as well as additive n...

The effectiveness of single-epoch integer ambiguity resolution, which provides centimeter-level relative positioning in real-time, is a function of the number, quality and type of carrier phase measurements available. We apply the Local-Minima Search (LMS) method epoch-by-epoch to GPS-GLONASS dual frequency carrier phase measurements taken over 2, 9 and 18 km baselines. While the application of...

Standardized learning management systems and contents are becoming prevalent over time with the growing adoption of Web-based learning technologies. The complexity adherent in the SCORM run-time environment APIs and data model, however, makes it difficult for instructional designers, content developers and LMS vendors to tailor their contents and LMSs for the SCORM model. In this paper, our own...