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A NOVEL METHOD FOR FEATURE selection WITH RANDOM SAMPLING HDMR AND ITS APPLICATION TO HYPERSPECTRAL IMAGE CLASSIFICATION

A NOVEL METHOD FOR FEATURE SELECTION WITH RANDOM SAMPLING HD...

引用

IEEE International Geoscience and Remote Sensing Symposium

作者： G. Taskin H. Kaya L. Bruzzone Istanbul Technical Univ Institute of Earthquake Engineering and Disaster Management Istanbul Technical Univ Informatics Institute Department of Information Engineering and Computer Science University of Trento

ISBN: (纸本)9781479979301

In hyperspectral image analysis, the classification task has generally been discussed with dimensionality reduction due to high correlation and noise between the spectral features, which might cause significantly low classification performance. In supervised classification, limited training samples in proportion to the number of spectral features have also negative impacts on the classification accuracy, which has known as Hughes effects or curse of dimensionality in the literature. In this paper, we focus on dimensionality reduction problem, and proposed a novel feature selection algorithm by using the method called random sampling high dimensional model representation (RS-HDMR), and the proposed algorithm were tested on a toy and hyperspectral dataset in comparison to conventional feature selection algorithms with regards to both computational time and classification accuracy.

关键词： Sensitivity analysis Feature selection High dimensional model representation Hyperspectral image classification Feature extraction Random sampling Image classification spectral feature dimensionality reduction Sensitivity analysis Curse of Dimensionality images Playthings selection algorithm computational time

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Antenna selection for Large-Scale Mimo Systems with Low-Resolution Adcs

Antenna Selection for Large-Scale Mimo Systems with Low-Reso...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Jinseok Chai Junmo Sung Brian L. Evans Alan Gatherer Wireless Networking and Communications Group The University of Texas at Austin Systems and Design for Wireless Communications Huawei Plano Texas USA

ISBN: (纸本)9781538646595

One way to reduce the power consumption in large-scale multiple-input multiple-output (MIMO) systems is to employ low-resolution analog-to-digital converters (ADCs). In this paper, we investigate antenna selection for large-scale MIMO receivers with low-resolution ADCs, thereby providing more flexibility in resolution and number of ADCs. To incorporate quantization effects, we generalize an existing objective function for a greedy capacity-maximization antenna selection approach. The derived objective function offers an opportunity to select an antenna with the best tradeoff between the additional channel gain and increase in quantization error. Using the generalized objective function, we propose an antenna selection algorithm based on a conventional antenna selection algorithm without an increase in overall complexity. Simulation results show that the proposed algorithm outperforms the conventional algorithm in achievable capacity for the same number of antennas.

关键词： Antenna selection large-scale MIMO low-resolution ADCs capacity-maximization algorithm ANTENNA selection algorithm Objective function Quantization multiple input multiple output systems antennae numerical invariant Power consumption

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ADAPTIVE SEARCH RANGE selection IN MOTION ESTIMATION

ADAPTIVE SEARCH RANGE SELECTION IN MOTION ESTIMATION

引用

IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Chung-Cheng Lou Szu-Wei Lee C.-C. Jay Kuo Ming Hsieh Department of Electrical Engineering and Signal and Image Processing Institute University of Southern California Los Angeles CA 90089-2564 USA

ISBN: (纸本)9781424442959

An adaptive search range (SR) selection algorithm in motion estimation for video encoding is proposed in this work with an objective to achieve excellent coding performance with reduced memory access bandwidth. In modern fast motion search algorithms, a motion vector predictor (MVP) is obtained from the motion vectors (MVs) of spatially and temporally neighboring blocks, which is called the predictive MV set. By exploiting the relationship between the variance of the predictive MV set and the SR, we develop an adaptive SR selection algorithm. That is, a larger variance implies lower accuracy of the MVP and, thus, a larger SR. The superior performance of the proposed SR selection algorithm is demonstrated by experimental results.

关键词： Motion estimation motion vector predictor adaptive search range selection motion estimation motion vector SAVANNAH RIVER OPERATIONS OFFICE Strontium selection algorithm cisplatin/mitomycin/vindesine Variance

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Efficient and exact mesh deformation using multiscale RBF interpolation 55

Efficient and exact mesh deformation using multiscale RBF in...

引用

55th AIAA Aerospace Sciences Meeting

作者： Kedward, L. Allen, C.B. Rendall, T.C.S. Department of Aerospace Engineering University of Bristol BristolBS8 1TR United Kingdom

ISBN: (数字)9781624104473

ISBN: (纸本)9781624104473

Mesh deformation schemes are vital in many areas of numerical simulation, and radial basis function(RBF)-based interpolation schemes are popular due to their excellent quality preservation properties. However, the system solution cost scales with moving surface points as N3surface, and so there have been numerous works investigating efficient methods of reducing the data set. However, reduced data methods require the addition of a secondary ‘correction vector field’ to ensure surface points not included in the primary deformation are moved to the correct location, and the volume mesh moved accordingly. A new method is presented here, which captures global and local motions at multiple scales using all the surface points, and so there is no need for a correction stage. The multiscale formulation developed means that although all surface points are used and a single interpolation built, the cost and conditioning issues associated with RBF methods are eliminated while still retaining exact recovery of the surface. Moreover, the sparsity introduced can be exploited, using an existing wall distance function, to further reduce the cost. The method is com- pared with a conventional greedy method on two- and three-dimensional meshes with large deformations. It is shown that mesh quality is always comparable with or better than with the greedy method, and cost and complexity is also comparable or cheaper for all stages. The most expensive stage of reduced point methods is surface mesh preprocessing, and the cost is reduced significantly here;a three or four orders of magnitude reduction in cost is demonstrated compared to greedy-type methods. © 2017 by C.B. Allen.

关键词： Computational Fluid Dynamics Fluid Structure Interaction Greedy algorithm Cost Reduction NACA 0012 Aerodynamic Shape Optimization Multivariate Interpolation Structural Element selection algorithm Mesh Free Methods

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selection of the Coordination Strategy in the Network MIMO Downlink

Selection of the Coordination Strategy in the Network MIMO D...

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WSA 2015;19th International ITG Workshop on Smart Antennas

作者： Sebastian Stern Robert F. H. Fischer Institut fur Nachrichtentechnik Universitat Ulm

Network MIMO or distributed MIMO is one promising strategy to increase the data rates in future cellular communication systems. However, well-known schemes like linear preequalization or Tomlinson-Harashima precoding for handling the multiuser interference assume full coordination (via some centralized processing) between the base stations. This approach causes significant traffic in the (wired) backhaul. In this paper, decentralized strategies with partial coordination are considered. A selection algorithm is presented, which, given the actual MIMO channel, automatically chooses the amount of coordination which is necessary to achieve a predefined performance. The trade-off between the achievable reduction in backhaul signaling and the required signal-to-noise ratio to not exceed a tolerated bit error rate is discussed. The proposed strategies are covered by means of numerical simulations.

关键词： multiple input multiple output systems Data transfer rates signal to noise ratios Multi-user Interference selection algorithm Bit error rate return stroke Downlink pre-equalization

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COMPARING MESSAGE PASSING INTERFACE AND MAPREDUCE FOR LARGE-SCALE PARALLEL RANKING AND selection 15

COMPARING MESSAGE PASSING INTERFACE AND MAPREDUCE FOR LARGE-...

引用

Simulation Conference

作者： Eric C. Ni Shane G. Henderson Dragos F. Ciocan Susan R. Hunter Cornell University Ithaca NY Technology and Operations Management INSEAD Fontainebleau France Purdue University West Lafayette IN

ISBN: (纸本)9781467397414

We compare two methods for implementing ranking and selection algorithms in large-scale parallel computing environments. The Message Passing Interface (MPI) provides the programmer with complete control over sending and receiving messages between cores, and is fragile with regard to core failures or messages going awry. In contrast, MapReduce handles all communication and is quite robust, but is more rigid in terms of how algorithms can be coded. As expected in a high-performance computing context, we find that MPI is the more efficient of the two environments, although MapReduce is a reasonable choice. Accordingly, MapReduce may be attractive in environments where cores can stall or fail, such as is possible in low-budget cloud computing.

关键词： message passing core mannose phosphate isomerase remote procedure calls Messages Environments High Performance Computing Computer personnel Cloud Computing Fragility Core samples Communication Research selection algorithm Interface Interfaces

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Robust EEG Channel selection across Sessions in Brain-Computer Interface Involving Stroke Patients

Robust EEG Channel Selection across Sessions in Brain-Comput...

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International Joint Conference on Neural Networks

作者： Mahnaz Arvaneh Cuntai Guan Kai Keng Ang Chai Quek Institute for Infocomm Research - Agency for Science Technology And Research School of Computer Engineering Nanyang Technological University

ISBN: (纸本)9781467314886

Brain-computer interface (BCI) technology has shown the capability of improving the quality of life for people with severe motor disabilities. To improve the portability and practicability of BCI systems, it is crucial to reduce the number of EEG channels as well as to have a good reliability. However, a relatively neglected issue in the EEG channel selection studies is the robustness of selected channels across sessions. This paper investigates whether the selected channels from first session is also useful for subsequent sessions on other days for a stroke patient. For this purpose, a new robust sparse common spatial pattern (RSCSP) algorithm is proposed for optimal EEG channel selection. Thereafter, the robustness of the proposed algorithm as well as 5 existing channel selection algorithms is investigated across 12 sessions data from 11 stroke patients who performed motor imagery based-BCI rehabilitation. The experimental results show that the proposed RSCSP channel selection algorithm significantly outperforms the other channel selection algorithms, when the 8 channels selected from the first session are evaluated on the 11 subsequent sessions. Moreover, there is no significant difference between the classification results of 8 channels selected by the proposed RSCSP algorithm from the first session and the classification results of 8 optimal channels selected from the same session as the test session.

关键词： stroke patient channel selection Brain-Computer Interfaces Electroencephalography selection algorithm Computer interfaces

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Optimal Resource Allocation and Mode selection for D2D Communication Underlaying Cellular Networks

Optimal Resource Allocation and Mode Selection for D2D Commu...

引用

IEEE Global Communications Conference

作者： Xue Chen Rose Qingyang Hu Jeongho Jeon Geng Wu Department of Electrical and Computer Engineering Utah State University Communication and Devices Group Intel Corporation

ISBN: (纸本)9781479959532

In this work, we consider the device-to-device (D2D) communications underlaying cellular networks to support local communication needs. In particular, we focus our attention on the design of an optimal resource allocation and mode selection algorithm for both cellular and D2D users. In the design, communication mode selection for D2D users is also taken into account so that a D2D source-destination pair has an option to either directly communicate or indirectly communicate through the base station (BS). On the other hand, it is necessary and important to provide a certain level of Quality of Service (QoS) to users. The users can be further differentiated by assigning different weighting factors and QoS requirements. To this end, we formulate a problem of maximizing the weighed sum rate of all the users constrained by their power and QoS requirements. The tool that we use to handle this problem is the primal-dual technique which transforms the original problem into the equivalent problem showing lower computational complexity. The simulation results verify that our proposed scheme outperforms the previous heuristic scheme by jointly optimizing the power and resource allocation along with the communication mode selection for the D2D communication pairs.

关键词： Resource utilization Cellular networks Consumers management of resources Quality of service Communication Research communication modes selection algorithm Energy sources original problem

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Recursive Path selection For Delay Fault Testing

Recursive Path Selection For Delay Fault Testing

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IEEE VLSI Test Symposium (VTS)

作者： Jaeyong Chung Jacob A. Abraham Computer Engineering Research Center The University of Texas at Austin

ISBN: (纸本)9781424437696

This paper presents a new path selection algorithm for delay fault testing in a statistical timing framework. Existing algorithms which consider correlation between paths use an iterative process for each path or defect and require a Monte Carlo simulation for each iteration to calculate the conditional fault probability. The proposed algorithm does not require the iteration process and selects a requested number of paths simultaneously once it performs a statistical timing analysis at the beginning. If selection of k paths is required in a set of paths, it partitions the set into two path sets and determines how many paths should be selected in each path set out of the k paths. It recursively continues this process and ends up with k paths. The partitioning is easily performed during the recursive traversal of a circuit, which produces an imaginary path tree, where paths are already grouped based on their prefix. Experimental results show the proposed algorithm can effectively use structural correlation and spatial correlation to generate high quality path sets.

关键词： Byways Iterative Process Paths fault latency time series analysis fault probability selection algorithm Monte Carlo technique Recursive

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Relay selection with Limited and Noisy Feedback

Relay Selection with Limited and Noisy Feedback

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IEEE Vehicular Technology Conference

作者： Mohammed E. Eltayeb Khalil Elkhalil Abdullahi Abubakar Mas'ud Tareq Y. Al-Naffouri The University of Texas at Austin Texas USA King Abdullah University of Science and Technology Thuwal Saudi Arabia Jubail Industrial College Saudi Arabia

ISBN: (纸本)9781479980925

Relay selection is a simple technique that achieves spatial diversity in cooperative relay networks. Nonetheless, relay selection algorithms generally require error-free channel state information (CSI) from all cooperating relays. Practically, CSI acquisition generates a great deal of feedback overhead that could result in significant transmission delays. In addition to this, the fed back channel information is usually corrupted by additive noise. This could lead to transmission outages if the central node selects the set of cooperating relays based on inaccurate feedback information. In this paper, we propose a relay selection algorithm that tackles the above challenges. Instead of allocating each relay a dedicated channel for feedback, all relays share a pool of feedback channels. Following that, each relay feeds back its identity only if its effective channel (source-relay-destination) exceeds a threshold. After deriving closed-form expressions for the feedback load and the achievable rate, we show that the proposed algorithm drastically reduces the feedback overhead and achieves a rate close to that obtained by selection algorithms with dedicated error-free feedback from all relays.

关键词： Relay selection Limited Noisy Feedback relay Feedback selection algorithm cooperating feedback channel Set of central axillary lymph nodes Error-free operations

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