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2005 IEEE/ACES International Conference on Wireless Communications and Applied Computational Electromagnetics

作者： Li, Tso-Wei Sun, Jwo-Shiun Institute of Computer Communication and Control National Taipei University of Technology Taipei Taiwan

ISBN: (纸本)0780390687

A dielectric resonator antenna bandwidth enhanced method by parasitic strip is investigated experimentally. Using an additional parasitic strip mounted on the dielectric resonator and shifting the displacement between dielectric resonator and microstrip feedline can increase the 10dB bandwidth in excess of 11%. By this design, the bandwidth is enhanced almost tree times more than pure microstrip fed dielectric resonator antenna by these presented materials. © 2005 ACES.

关键词： Microstrip antennas

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Performance enhancement by using switch-beam smart antenna in 802.11a WLAN system

Performance enhancement by using switch-beam smart antenna i...

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2005 IEEE/ACES International Conference on Wireless Communications and Applied Computational Electromagnetics

作者： Chu, Shao-Hua Lin, Hsin-Piao Lin, Ding-Bing Institute of Computer Communication and Control National Taipei University of Technology Taipei Taiwan

ISBN: (纸本)0780390687

An IEEE 802.l1a WLAN system physical layer use coded orthogonal frequency division multiplexing (COFDM) to combat frequency selective fading channel. The WLAN system with omni antenna suffers excess delay spread and inter-symbol interference in indoor radio propagation channel. The impact of frequency selective fading channel on WLAN performance is evaluated. Wireless communication usually utilizes smart antenna to enhance performance. This paper presents Monte Carlo simulation based on the IEEE *** physical layer specification and utilizes switch-beam smart antenna operation at the access point (AP) to enhance WLAN performance. The paper analyzes the performance of using omni and switch-beam antenna in a real office indoor environment. Compared with using omni antenna, the simulation results show that utilizing switch-beam antenna in AP the BER performance improve about 2dB in light-of-sight (LOS) case, and 6dB in non-light-of-sight (NLOS) case. © 2005 IEEE.

关键词： Local area networks

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A New Low-power Turbo Decoder Using HDA-DHDD Stopping Iteration

A New Low-power Turbo Decoder Using HDA-DHDD Stopping Iterat...

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IEEE International Symposium on Circuits and Systems 2005, ISCAS 2005

作者： Lee, Wen-Ta Lin, San-Ho Tsai, Chia-Chun Lee, Trong-Yen Hwang, Yuh-Shyan Institute of Computer Communication and Control National Taipei University of Technology Taipei Taiwan

ISBN: (纸本)9780780388345

In this paper, we present a new VLSI architecture for low-power turbo decoder. First, we develop a new soft-in-soft-out decoder architecture and change the sliding window operating flow without attaching LIFO memory. Moreover, we propose a new stopping iteration algorithm that integrates two stop criteria to avoid unnecessary iterations, especially in low SNR channel. Experiments show that our architecture gets 25.3%~39.8% memory size saving in our SISO decoder architecture and one window saving of decoding delay in comparison with traditional decoder. © 2005 IEEE.

关键词： Signal to noise ratio

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Dual-frequency dielectric resonator antenna with inverse T-shape parasitic strip

Dual-frequency dielectric resonator antenna with inverse T-s...

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2005 IEEE/ACES International Conference on Wireless Communications and Applied Computational Electromagnetics

作者： Li, Tso-Wei Sun, Jwo-Shiun Institute of Computer Communication and Control National Taipei University of Technology Taipei Taiwan

ISBN: (纸本)0780390687

A dual-band dielectric resonator antenna with inverse T-shape parasitic strip is investigated experimentally. Using an additional inverse T-shape parasitic strip mounted on the dielectric resonator can be induced a higher mode whose radiation patterns have broadside characteristics. Both the radiation patterns of low and high resonant frequencies have no nulls at main radiation directions. © 2005 ACES.

关键词： Microstrip antennas

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Multistage Naive Bayes classifier with reject option for multiresolution signal representation

Multistage Naive Bayes classifier with reject option for mul...

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2nd International Conference on Pattern Recognition Applications and Methods, ICPRAM 2013

作者： Libal, Urszula Institute of Computer Engineering Control and Robotics Wroclaw University of Technology Wroclaw Poland

ISBN: (纸本)9789898565419

In the article, two approaches to pattern recognition of signals are compared: a direct and a multistage. It is assumed that there are two generic patterns of signals, i.e. a two-class problem is considered. The direct method classifies signal in one step. The multistage method uses a multiresolution representation of signal in wavelet bases, starting from a coarse resolution at the first stage to a more detailed resolutions at the next stages. After a signal is assigned to a class, the posterior probability for this class is counted and compared with a fixed level. If the probability is higher than this level, the algorithm stops. Otherwise the signal is rejected and on the next stage the classification procedure is repeated for a higher resolution of signal. The posterior probability is calculated again. The algorithm stops when the probability is higher than a fixed level and a signal is finally assigned to a class. The wavelet filtration of signal is used for feature selection and acts as a magnifier. If the posterior probability of recognition is low on some stage, the number of features on the next stage is increased by taking a better resolution. The experiments are performed for three local decision rules: naive Bayes, linear and quadratic discriminant analysis.

关键词： Probability

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A wide U-shape slot fed broadband dielectric resonator antenna 11

A wide U-shape slot fed broadband dielectric resonator anten...

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11th International Symposium on Antenna technology and Applied Electromagnetics, ANTEM 2005

作者： Li, Tso-Wei Sun, Jwo-Shiun Institute of Computer Communication and Control National Taipei University of Technology Taipei Taiwan

ISBN: (纸本)9780973842500

A wide U-shape slot fed dielectric resonator antenna (DRA) is investigated experimentally. Using U-shape wide slot (the width of slot is about 7.5mm), a wideband DRA can be obtained. There are two adjacent modes can be induced simultaneously;then, these two modes achieve wider bandwidth than pure slot fed dielectric resonator antenna. The bandwidth of U-shape wide slot reaches about 20%. By this design, the bandwidth is enhanced almost five times pure slot fed dielectric resonator antenna. © 2005 IEEE.

关键词： Bandwidth

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Double pointer shifting Window C++ algorithm for the matrix multiplication

Double pointer shifting Window C++ algorithm for the matrix ...

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14th International Conference on Computational Science and Its Applications, ICCSA 2014

作者： Respondek, Jerzy S. Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Institute of Computer Science Poland

ISBN: (纸本)9783319091525

Inthis article we show how to utylize the pointer effectiveness in the matrix multiplication algorithm. To achieve this we proposed an advanced pointer-oriented matrix multiplication numerical recipe. We involved the double pointer matrix representation, with separate allocation of each row enabling this way convenient element acces without multiplication. Finally, we performed time tests which proved the high efficiency of the proposed pointer oriented paradigm. © 2014 Springer International Publishing.

关键词： Matrix algebra

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Slot fed broadband dielectric resonator antenna

Slot fed broadband dielectric resonator antenna

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2005 IEEE/ACES International Conference on Wireless Communications and Applied Computational Electromagnetics

作者： Li, Tso-Wei Sun, Jwo-Shiun Institute of Computer Communication and Control National Taipei University of Technology Taipei Taiwan

ISBN: (纸本)0780390687

A slot fed dielectric resonator antenna (DRA) is investigated experimentally. Using a U-shape narrow slot (the width of slot is about 1mm), a wideband DRA can be obtained. Because two adjacent modes can be induced simultaneously;then, the bandwidth can be enhanced by these two adjacent modes. The bandwidth of narrow U-shape wide slot reaches about 13%. By this design, the bandwidth is enhanced almost four times more than the pure slot fed dielectric resonator antenna with presented materials. © 2005 ACES.

关键词： Microstrip antennas

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Application of artificial neuron networks and hurst exponent to forecasting of successive values of a time series representing environmental measurements in an intelligent building

Application of artificial neuron networks and hurst exponent...

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14th International Conference on computer Aided Systems Theory, EUROCAST 2013

作者： Stachno, Andrzej Jablonski, Andrzej Institute of Computer Engineering Control and Robotics Wroclaw University of Technology Wroclaw Poland

ISBN: (纸本)9783642538551

control systems for intelligent buildings based on environmental measurements. The information contained in the measurement data in many cases are independent and chaotic. You can not interact with the control system, but only to monitor. In many cases, the use of measurement data for the purpose of building automation control, requires the use of forecasting systems. For the needs forecasting this type of measurement data apply artificial neural networks. Learning provides a mechanism to adjust its internal parameters of artificial neural network to characterize the trend of the time series reflects the measurement data. For time series with greater variability of smoothing is necessary. The intention initial classification time series smoothing and allows the use of artificial neural networks to forecast the next value of the time series irrespective of their volatility. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Forecasting

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MEET: A Million-Scale Dataset for Fine-Grained Geospatial Scene Classification with Zoom-Free Remote Sensing Imagery

arXiv

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arXiv 2025年

作者： Li, Yansheng Wu, Yuning Cheng, Gong Tao, Chao Dang, Bo Wang, Yu Zhang, Jiahao Zhang, Chuge Liu, Yiting Tang, Xu Ma, Jiayi Zhang, Yongjun Information and computing science from Shandong University Weihai China Pattern recognition and intelligent system from the Huazhong University of Science and Technology Wuhan China Computer science and technology from Wuhan University Wuhan China Xidian University Xi’an China Pattern recognition and intelligent systems from Northwestern Polytechnical University Xi’an China School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan China Institute for Pattern Recognition and Artificial Intelligence Huazhong China University of Science and Technology Remote sensing science and technology from Wuhan University Wuhan China School of Remote Sensing and Information Engineering Wuhan University Wuhan China Electronic circuit and system from Xidian University Xi’an China University of Colorado at Boulder BoulderCO United States Control science and engineering from the Huazhong University of Science and Technology Wuhan China Geodesy and photography from Wuhan University Wuhan China

Accurate fine-grained geospatial scene classification using remote sensing imagery is essential for a wide range of applications. However, existing approaches often rely on manually zooming remote sensing images at different scales to create typical scene samples. This approach fails to adequately support the fixed-resolution image interpretation requirements in real-world scenarios. To address this limitation, we introduce the Million-scale finE-grained geospatial scEne classification dataseT (MEET), which contains over 1.03 million zoom-free remote sensing scene samples, manually annotated into 80 fine-grained categories. In MEET, each scene sample follows a scene-in-scene layout, where the central scene serves as the reference, and auxiliary scenes provide crucial spatial context for fine-grained classification. Moreover, to tackle the emerging challenge of scene-in-scene classification, we present the Context-Aware Transformer (CAT), a model specifically designed for this task, which adaptively fuses spatial context to accurately classify the scene samples. CAT adaptively fuses spatial context to accurately classify the scene samples by learning attentional features that capture the relationships between the center and auxiliary scenes. Based on MEET, we establish a comprehensive benchmark for fine-grained geospatial scene classification, evaluating CAT against 11 competitive baselines. The results demonstrate that CAT significantly outperforms these baselines, achieving a 1.88% higher balanced accuracy (BA) with the Swin-Large backbone, and a notable 7.87% improvement with the Swin-Huge backbone. Further experiments validate the effectiveness of each module in CAT and show the practical applicability of CAT in the urban functional zone mapping. The source code and dataset will be publicly available at https://***/project/***. Copyright © 2025, The Authors. All rights reserved.

关键词： Image classification

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