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IEEE Global Communications Conference

作者： Masato Taniguchi Hidekazu Murata Susumu Yoshida Koji Yamamoto Daisuke Umehara Satoshi Denno Masahiro Morikura Graduate School of Informatics Kyoto University Graduate School of Science and Technology Kyoto Institute of Technology Matsugasaki Graduate School of Natural Science and Technology Okayama University

ISBN: (纸本)9781479913510

A transmission experiment of a multi-user MIMO system with user selection and linear spatial precoding is conducted and the results are reported. As a low-complexity user selection algorithm, the chordal distance-based user selection (CDUS) algorithm is employed. The testbed used in the experiment is implemented by taking full advantage of the software-defined radio. An amplify-and-forward-based simple channel estimation method is adopted. As a result of the experiment in a conference room, the CDUS algorithm improved both the power efficiency and the interference suppression accuracy compared to the round-robin user selection.

关键词： MIMO experiment round-robin user selection multiple input multiple output systems selection algorithm Chord dynamic efficiency multi-user

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An user selection algorithm for the heterogeneous network

An user selection algorithm for the heterogeneous network

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Third International Conference on Cyberspace Technology (CCT 2015)

作者： Dongsheng Han Conghui Hao Hairui Zhang Linlin Che School of Electrical and Electronic Engineering North China Electric Power University Baoding 071003 China The 54th Research Institute of China Electronics Technology Group Corporation Shijiazhuang 050081 China

The cross-tier inter-cell interference between macrocell and microcell is the bottleneck against performance improvement of the heterogeneous network. To overcome this bottleneck, we propose a user selection algorithm that takes effect of chordal distance-channel norm balance on the system into account and predetermines the available user set. Simulation results demonstrated that the proposed algorithm could achieve user diversity gain while lowering cross-tier interference.

关键词： channel norm chordal distance cross-tier interference heterogeneous network user selection Heterogeneous networks selection algorithm Traffic Bottlenecks Microcells Diversity methods macrocells

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AMOS: An automated model order selection algorithm for spectral graph clustering

AMOS: An automated model order selection algorithm for spect...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Pin-Yu Chen Thibaut Gensollen Alfred O. Hero Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor USA

ISBN: (纸本)9781509041183

One of the longstanding problems in spectral graph clustering (SGC) is the so-called model order selection problem: automated selection of the correct number of clusters. This is equivalent to the problem of finding the number of connected components or communities in an undirected graph. In this paper, we propose AMOS, an automated model order selection algorithm for SGC. Based on a recent analysis of clustering reliability for SGC under the random interconnection model, AMOS works by incrementally increasing the number of clusters, estimating the quality of identified clusters, and providing a series of clustering reliability tests. Consequently, AMOS outputs clusters of minimal model order with statistical clustering reliability guarantees. Comparing to three other automated graph clustering methods on real-world datasets, AMOS shows superior performance in terms of multiple external and internal clustering metrics.

关键词： selection algorithm Automation Cluster Analysis Clustering methods Line graph undirected graph connected component

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A Novel Feature selection algorithm Based on Artificial Bee Colony algorithm and Genetic algorithm

A Novel Feature Selection Algorithm Based on Artificial Bee ...

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IEEE International Conference on Power, Intelligent Computing and Systems

作者： Junqi Ge Xutao Zhang Gongyou Liu Yu Sun College of Computer Science and Technology Jilin University

ISBN: (纸本)9781728137216

The classification of microarray data has positive significance for the judgment of cancer and the determination of clinical programs. However, the high dimensionality and small sample characteristics of the microarray data has brought classification a difficult problem. Aiming at the feature selection problem in microarray data classification, a feature selection algorithm based on artificial bee colony algorithm and genetic algorithm is proposed to solve the dimensionality disaster problem in microarray data classification. Finally, the feature subsets obtained by the algorithm are combined with the SVM (Support Vector Machine) classifier to apply to the six published microarray datasets. The experimental results show that the feature subsets obtained based on the proposed scheme can significantly improve the classification performance.

关键词： Feature selection Artificial bee colony algorithm genetic algorithm Microarray data Feature extraction artificial bee colony algorithm data classification Genetic algorithm (GA) Microarray selection algorithm Taxonomy algorithms

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A Biologically Inspired Action selection algorithm Based on Principles of Neuromodulation

A Biologically Inspired Action Selection Algorithm Based on ...

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International Joint Conference on Neural Networks

作者： Jeffrey L. Krichmar Department of Cognitive Sciences Department of Computer Science University of California

ISBN: (纸本)9781467314886

The brain's neuromodulatory systems play a key role in regulating decision-making and responding to environmental challenges. Attending to the appropriate sensory signal, filtering out noise, changing moods, and selecting behavior are all influenced by these systems. We introduce a neural network for action selection that is based on principles of neuromodulatory systems. The algorithm, which was tested on an autonomous robot, demonstrates valuable features such as fluid switching of behavior, gating in important sensory events, and separating signal from noise.

关键词： Adaptive behavior Computational neuroscience Neuromodulation Neurorobots neuroregulation Autonomous robots selection algorithm Principle-Based Ethics Noise Respiratory Inspiration Neural network signal filtering Emotional States Fluid Sensation

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A Computationally Efficient Multimode Antenna selection algorithm for MIMO V-BLAST Systems

A Computationally Efficient Multimode Antenna Selection Algo...

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications

作者： Chiao-En Chen Shin-Hua Huang Department of Electrical/Communications Engineering National Chung Cheng University Chiayi Taiwan

ISBN: (纸本)9781457713460

Multimode antenna selection (MAS), the technique of jointly selecting both the number of spatial streams and antenna subsets at the transmitter, is a promising scheme for improving the performance of spatial multiplexing MIMO systems. In this paper, we investigate the problem of multimode antenna selection for the Vertical Bell Laboratories Layered Space-Time (V-BLAST) system with a goal to minimize the system's error rate. As the error rate of a communications system varies dramatically with the transceiver architecture, the optimal MAS algorithm for V-BLAST should explicitly take the ordered-successive interference cancellation (OSIC) detection structure into account. A computationally efficient MAS algorithm is there-fore proposed to exploit the recursive structure of mean-square-error matrices between consecutive OSIC detection stages and achieve near optimal error rate performance with significantly lower complexity as verified by the computer simulations.

关键词： V-BLAST COMMUNICATION SYSTEMS multiple input multiple output systems bit error rate performance selection algorithm blast system

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Removal-Cost Method: An Efficient Voltage selection algorithm for Multi-Core Platforms under PVT

Removal-Cost Method: An Efficient Voltage Selection Algorith...

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IEEE International SOC Conference

作者： Sohaib Majzoub Resve Saleh Steven J. E. Wilton Rabab Ward Department of Electrical and Computer Engineering University of British Columbia Vancouver

ISBN: (纸本)9781424449408

In this paper, we present a novel solution to the Voltage selection Problem for large multi-core architectures. Compared to previous algorithms, ours provides similar results, but is more than 10x faster. This run-time improvement is important, especially for large multi-core platforms with hundreds of cores. We evaluate our algorithm in the context of a process, voltage, and temperature (PVT) variation-aware energy optimization framework.

关键词： selection algorithm VOLTAGE Platform core Runtime

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Butterfly Traffic Pattern in selection algorithm on Hierarchical Torus Network

Butterfly Traffic Pattern in Selection Algorithm on Hierarch...

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International Conference on Electrical Engineering and Information Communication Technology

作者： M.M. Hafizur Rahman M. A. H. Akhand Pintu Chandra Shill Yasushi Inoguchi Dept. of Computer Science KICT IIUM Jalan Gombak PO Box. 10 50728 Kuala Lumpur Malaysia Dept. of Computer Science and Engineering KUET Khulna - 9203 Bangladesh Research Center for Advanced Computing Infrastructure JAIST Nomi-Shi Ishikawa 923-1292 Japan

ISBN: (纸本)9781467366779

A Hierarchical Torus Network (HTN) is a 2D-torus network of multiple basic modules, in which the basic modules are 3D-torus networks that are hierarchically interconnected for higher-level networks. The combination of link selection and channel selection (LS+CS) algorithm improves the dynamic communication performance of the HTN by efficient use of physical links and virtual channels. In this paper, we have evaluated the dynamic communication performances of an HTN is evaluated by using dimension-order routing and LS+CS algorithm under butterfly traffic pattern. It is found that the dynamic communication performance of an HTN using the LS+CS algorithm is better than when the dimension-order routing is used.

关键词： HTN selection algorithm butterfly traffic pattern and dynamic communication performance

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An improved, randomized algorithm for parallel selection with an experimental study

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JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING 2004年第9期64卷 1051-1059页

作者： Bader, DA Univ New Mexico Dept Elect & Comp Engn Albuquerque NM 87131 USA

A common statistical problem is that of finding the median element in a set of data. This paper presents an efficient randomized high-level parallel algorithm for finding the median given a set of elements distributed across a parallel machine. In fact, our algorithm solves the general selection problem that requires the determination of the element of rank k, for an arbitrarily given integer k. Our general framework is an SPMD distributed-memory programming model that is enhanced by a set of communication primitives. We use efficient techniques for distributing and coalescing data as well as efficient combinations of task and data parallelism. The algorithms have been coded in the message-passing standard MPI, and our experimental results from the IBM SP-2 illustrate the scalability and efficiency of our algorithm and improve upon all the related experimental results known to the author. The main contributions of this paper are (1) New techniques for speeding the performance of certain randomized algorithms, such as selection, which are efficient with likely probability. (2) A new, practical randomized selection algorithm (UltraFast) with significantly improved convergence. (C) 2004 Elsevier Inc. All rights reserved.

关键词： selection algorithm randomized algorithms parallel algorithms experimental parallel algorithmics

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Reduced feedback load using user selection algorithms for the multiuser multi-input single-output systems

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TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES 2013年第7-8期24卷 809-819页

作者： Khanfir, Hajer Le Ruyet, Didier Ozbek, Berna Conservatoire Natl Arts & Metiers Elect & Commun Lab F-75141 Paris France Izmir Inst Technol Dept Elect & Elect Engn TR-35430 Izmir Turkey

For wireless multiuser multi-input single-output communication systems with adaptive scheduling and precoding, the users have to feed back their channel state information. However, the amount of feedback data increases with the number of users and the number of transmit antennas. In this paper, we propose a criterion based on the orthogonality between the users' channels to reduce this uplink load. Without cooperation between the users, we only allow users that are semi-orthogonal to feed back their quantized channel information to the base station. We propose a lower bound on the sum rate for the proposed criterion. We show that the performance is almost independent of the number of quantized channel quality information and only channel direction information is important at the transmitter. Then, we consider a noisy feedback channel and propose an algorithm to reduce the noise effect on the analogue *** (c) 2012 John Wiley & Sons, Ltd.

关键词： Channel state information Feedback transmitting antennas orthogonality adaptive scheduling COMMUNICATION SYSTEMS multi-input Quality Information output system algorithms information channels semi-orthogonal selection algorithm Noise effects LOAD

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