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检索条件"主题词=selection algorithm"

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An Improved LMDS algorithm

An Improved LMDS Algorithm

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7th International Conference on Swarm Intelligence (ICSI)

作者： Qu, Taiguo Cai, Zixing Cent S Univ Sch Informat Sci & Engn Changsha 410083 Hunan Peoples R China

ISBN: (纸本)9783319410098;9783319410081

Classical multidimensional scaling (CMDS) is a widely used method for dimensionality reduction and data visualization, but it's very slow. Landmark MDS (LMDS) is a fast algorithm of CMDS. In LMDS, some data points are designated as landmark points. When the intrinsic dimension of the landmark points is less than the intrinsic dimension of the data set, the embedding recovered by LMDS is not consistent with that of classical multidimensional scaling. A selection algorithm of landmark points is put forward in this paper to ensure the intrinsic dimension of the landmarks to be equal to that of the data set, so as to ensure that the embedding recovered by LMDS is the same as that of CMDS. By introducing the selection algorithm into the original LMDS, an improved LMDS algorithm called iLMDS is presented in this paper. The experimental results verify the consistency of iLMDS and CMDS.

关键词： Classical multidimensional scaling Landmark points Intrinsic dimension selection algorithm

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Recursive Path selection For Delay Fault Testing

Recursive Path Selection For Delay Fault Testing

引用

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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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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Model selection in Stochastic Chemical Reaction Networks Using Flow Cytometry Data

Model Selection in Stochastic Chemical Reaction Networks Usi...

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IEEE Conference on Decision and Control

作者： Gabriele Lillacci Mustafa Khammash Center for Control Dynamical Systems and Computation University of California at Santa Barbara Santa Barbara CA USA

ISBN: (纸本)9781612848006

The model selection problem, that is picking the model that best explains an experimental data set from a list of candidates, arises frequently when studying unknown biological processes. Here, we propose a new method for model selection in stochastic chemical reaction networks using measurements from flow cytometry. A distinctive feature of our approach is its ability to perform statistically significant selection using a very small number of Monte Carlo simulations of the candidate stochastic models. After a comprehensive review of the theory associated with our procedure, we describe the model selection algorithm and we demonstrate it on an example drawn from molecular biology.

关键词： model selection Monte Carlo technique Flow Cytometry selection algorithm Stochastic molecular biology

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Efficient Antenna selection and User Scheduling in 5G Massive MIMO-NOMA System

Efficient Antenna Selection and User Scheduling in 5G Massiv...

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IEEE Vehicular Technology Conference

作者： Xin Liu Xianbin Wang Department of Electrical and Computer Engineering The University of Western Ontario

ISBN: (纸本)9781509016990

To achieve extremely high spectral efficiency in the 5-th generation (5G) communication network, the combination of massive multiple input multiple output (MIMO) and non-orthogonal multiple access (NOMA) technologies becomes a promising solution. However, due to limited radio frequency (RF) chains and channel condition variation, it is important to develop efficient antenna selection and user scheduling algorithms in complex MIMO-NOMA system. In this paper, efficient antenna selection and user scheduling algorithms are investigated to maximize the sum rate in two MIMO-NOMA scenarios. In the first simple single-band two-user scenario, the proposed antenna selection algorithm achieves higher search efficiency by limiting the candidate antennas to those are beneficial to the relevant users. In the multi-band multi-user scenario, the proposed joint antenna and user (AU) contribution algorithm considers the contribution of each antenna's and user's channel gain to total channel gain jointly. Numerical results show that proposed antenna selection algorithm achieves near-optimal performance, and joint AU contribution algorithm achieves similar performance to existing methods with reduced complexity.

关键词： ANTENNA Scheduling algorithms selection algorithm antennae multiple input multiple output systems Consumers Gold African Union ASTRONOMICAL UNIT Gain radiofrequency

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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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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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A STABLE GENE selection METHOD BASED ON SAMPLE WEIGHTING 26th

A STABLE GENE SELECTION METHOD BASED ON SAMPLE WEIGHTING

引用

IEEE Canadian Conference on Electrical and Computer Engineering

作者： Guoyin Wang Juan Gao Feng Hu Chongqing Key Laboratory of Computational Intelligence Chongqing University of Posts and Telecommunications

ISBN: (纸本)9781479900312

In microarray analysis, the selection of informative gene is an essential issue for tissue classification and successful treatment because of its ability to improve the accuracy and decrease computational complexity. However, the gene subsets selected by the same method often vary significantly with some variations of the samples in the same data set. Thus, the stability of the selected genes is an aspect as important as the predictive ability to quantify a feature selection algorithm. This work is an attempt to improve the stability of feature selection methods from the point of view of sample importance. We propose an efficient mean deviation-based sample weighting algorithm to improve the stability of feature selection methods by assigning a weight to each sample according to the mean deviation of its local value in giving samples. We perform a series of experiments with four frequently studied public data sets, and the experimental results validate that the proposed method improves the stability of common feature selection algorithms such as ReliefF without sacrificing the classification performance. Furthermore, more stable gene feature sets obtained by the proposed method than the state-of-the-art ensemble method and margin-based sample weighting algorithm.

关键词： Feature selection Stability Gene expression microarray Classification performance Feature extraction Gene Feature Genes algorithms Mean deviation Dataset selection algorithm Microarray Analysis selection methods point of view

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IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)

作者： Badar Almarri Sanguthevar Rajasekaran Chun-Hsi Huang Univ. of Connecticut - King Faisal Univ. Storrs Alhasa USA Saudi Arabia

ISBN: (纸本)9781728138862

With the evolution of sensor-empowered systems in fields ranging from smart cities (e.g., green energy) and industry (e.g., machines condition monitoring) to personal and social health and wellness (e.g., wearable devices and electroencephalography, EEG), it is vital to consider constraints related to these sensors, including power consumption and noise. Consequently, empowering intelligence (e.g. prediction of states or outcomes) in such systems becomes of high importance in order to better deal with such constraints and to reduce the effects of dimensionality and volume of sensed data. Here, we propose a sensor selection algorithm that minimizes the sensor space relying on the similarities in how sensors sense a given environment. This algorithm resulted in a significant reduction in the sensor space without notable loss of accuracy when compared against the complete set of the sensing space. We applied the proposed algorithm to two sensor-based time-series datasets of different fields of application.

关键词： Sensor selection Time-series Feature Extraction Big Data Sensor Space Reduction big data Feature extraction Sensors time series data selection algorithm health green energy Time series Electroencephalography

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Detection of timing loop and clock selection in a synchronous ethernet network based on hop count

Detection of timing loop and clock selection in a synchronou...

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3rd International Conference on Electrical, Electronics, Engineering Trends, Communication, Optimization and Sciences (EEECOS 2016)

作者： Satheesh Kumar S. Abhinav Pandit Juniper Networks India Juniper Networks USA

ISBN: (纸本)9781510863279

A Synchronous Ethernet Network consists of network element (NE) which recover clock from the underlying Ethernet PHY and the quality of clock is conveyed using Ethernet Synchronous Messaging Channel with QL information embedded in QL-TLV. This enables clock selection for the downstream node. This paper describes a method to detect Timing Loop in synchronous network by modifying the current clock selection algorithm by adding another TLV to ESMC. A new parameter `hop count' define this new TLV which is incremented by `1' on each hop as the ESMC messages propagate on a synchronous ethernet network. This paper also shows the modified clock selection algorithm which each NEs uses to select the best available clock from a set of clocks. Also this paper captures the MTIE/TDEV graph for the frequency error/noise respectively with the proposed solution.

关键词： Synchronous Ethernet Ethernet Synchronization Messaging Channel Timing Loop Hop count hop counts Timing devices Ethernet networks Humulus Loops Threshold Limit Values selection algorithm

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