2,301 research outputs found
Broadband VSF-OFCDM systems with hybrid MCI cancellation and MMSE detection
In this paper, an analytical study is presented on the performance of the variable spreading factor orthogonal frequency and code division multiplexing (VSF-OFCDM) system with hybrid multi-code interference (MCI) cancellation and minimum mean square error (MMSE) detection. The weights of MMSE are derived, and should be updated stage by stage of MCI cancellation. Various values of time and frequency domain spreading factors are dealt with in a QPSK-modulated VSF-OFCDM system. It is shown that the hybrid detection scheme performs much better than the conventional MMSE. For the hybrid detection, a larger value of the frequency domain spreading factor is expected. © 2004 IEEE.published_or_final_versio
Optimum sub-packet transmission for turbo-coded hybrid ARQ systems
Turbo codes are popular for their near-shannon capacity of bit-error-rate (BER) at low signal-to-noise ratio (SNR) with long packet lengths. They have been proposed in automatic-repeat-request (ARQ) systems as the forward-error correction (FEC) codes. Although sub-packet schemes were proposed in ARQ systems, optimum sub-packet transmission is more effective to maximize throughput in a dynamic channel. Sub-packet schemes can provide additional error correction capability with iterative turbo decoding algorithms. An efficient method is proposed to estimate the optimum number of sub-packets, and adaptive sub-packet schemes, i.e., schemes that enable a system to employ different optimum numbers of sub-packets under variable conditions, are suggested to achieve the maximum throughput of the system. Simulations show that the adaptive sub-packet scheme is effective at moderate SNR, e.g. from 2.6dB to 5.0dB, and can provide higher throughput than conventional packet schemes.published_or_final_versio
Investigation of the behaviour of electronic resistive switching memory based on MoSe<font size=-1><sub>2</sub></font>-doped ultralong Se microwires
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结合遗传算法的LVQ神经网络在声学底质分类中的应用
Author name used in this publication: 唐秋华Author name used in this publication: 刘保华Author name used in this publication:Author name used in this publication: 陈永奇Author name used in this publication: 周兴华Author name used in this publication: 丁继胜Title in Traditional Chinese: 結合遺傳算法的LVQ神經網絡在聲學底質分類中的應用Journal title in Traditional Chinese: 地球物理學報2006-2007 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe
基于自组织神经网络的声学底质分类研究
Author name used in this publication: 唐秋华Author name used in this publication: 刘保华Author name used in this publication: 陈永奇Author name used in this publication: 周兴华Author name used in this publication: 丁继胜Title in Traditional Chinese: 基于自組織神經網絡的聲學底質分類研究Journal title in Traditional Chinese: 聲學技術2007-2008 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe
Premonitory phenomenon of El Nino event reflected in the observations of LOD and sea level
Journal title in Traditional Chinese: 科學通報 (英文版)2000-2001 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe
Expression of the RON receptor tyrosine kinase and its association with gastric carcinoma versus normal gastric tissues
SPOT-Seq-RNA: Predicting protein-RNA complex structure and RNA-binding function by fold recognition and binding affinity prediction
RNA-binding proteins (RBPs) play key roles in RNA metabolism and post-transcriptional regulation. Computational methods have been developed separately for prediction of RBPs and RNA-binding residues by machine-learning techniques and prediction of protein-RNA complex structures by rigid or semiflexible structure-to-structure docking. Here, we describe a template-based technique called SPOT-Seq-RNA that integrates prediction of RBPs, RNA-binding residues, and protein-RNA complex structures into a single package. This integration is achieved by combining template-based structure-prediction software, SPARKS X, with binding affinity prediction software, DRNA. This tool yields reasonable sensitivity (46 %) and high precision (84 %) for an independent test set of 215 RBPs and 5,766 non-RBPs. SPOT-Seq-RNA is computationally efficient for genome-scale prediction of RBPs and protein-RNA complex structures. Its application to human genome study has revealed a similar sensitivity and ability to uncover hundreds of novel RBPs beyond simple homology. The online server and downloadable version of SPOT-Seq-RNA are available at http://sparks-lab.org/server/SPOT-Seq-RNA/
An efficient framework for estimation of muscle fiber orientation using ultrasonography
2013-2014 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe
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