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检索条件"主题词=Algorithm Design And Analysis"

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An Enhanced Mixed Norm Error Criterion Adaptive Filtering algorithm for Sparse Channel Estimation

An Enhanced Mixed Norm Error Criterion Adaptive Filtering Al...

引用

Progress in Electromagnetics Research Symposium - Spring (PIERS)

作者： Wang, Yanyan Li, Yingsong Diao, Ming Harbin Engn Univ Coll Informat & Commun Engn Harbin 150001 Heilongjiang Peoples R China

ISBN: (纸本)9781509062690

Mixed norm error (MNE) criterion has been successfully used to develop adaptive filtering algorithms. Recently, adaptive filter algorithms based on MNE has an excellent performance for system identification, including channel estimation. In this paper, an enhanced sparse mixed l(2) and l(p) norm error criterion algorithm is proposed by the use of a soft parameter function to modify the basic cost function of l(2) and l(p) algorithm to generate a desired zero attractor. The proposed sparse MNE algorithm can well explore the essential sparsity in multi-path wireless channel because of the designed zero attractor. The proposed sparse MNE algorithm is analyzed and mathematically derived in detail. Simulation examples are presented to verify its behavior via a sparse wireless multi-path channel. Additionally, we will also investigate the parameter affects on the proposed algorithm. The obtained results confirm that the excellent behavior of the proposed sparse MNE algorithm is achieved in terms of both convergence and steady-state error in comparison with the LMS/F, L2LP and their corresponding sparse algorithms.

关键词： Convergence algorithm design and analysis Channel estimation Signal processing algorithms Cost function Mathematical model Electromagnetics

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Parallel and Efficient Sensitivity analysis of Microscopy Image Segmentation Workflows in Hybrid Systems

Parallel and Efficient Sensitivity Analysis of Microscopy Im...

引用

IEEE International Conference on Cluster Computing (CLUSTER)

作者： Barreiros, Willian, Jr. Teodoro, George Kurc, Tahsin Kong, Jun Melo, Alba C. M. A. Saltz, Joel Univ Brasilia Dept Comp Sci Brasilia DF Brazil SUNY Stony Brook Dept Biomed Informat Stony Brook NY 11794 USA Oak Ridge Natl Lab Sci Data Grp Oak Ridge TN USA Emory Univ Biomed Informat Dept Atlanta GA 30322 USA

ISBN: (纸本)9781538623268

We investigate efficient sensitivity analysis (SA) of algorithms that segment and classify image features in a large dataset of high-resolution images. algorithm SA is the process of evaluating variations of methods and parameter values to quantify differences in the output. A SA can be very compute demanding because it requires re-processing the input dataset several times with different parameters to assess variations in output. In this work, we introduce strategies to efficiently speed up SA via runtime optimizations targeting distributed hybrid systems and reuse of computations from runs with different parameters. We evaluate our approach using a cancer image analysis workflow on a hybrid cluster with 256 nodes, each with an Intel Phi and a dual socket CPU. The SA attained a parallel efficiency of over 90% on 256 nodes. The cooperative execution using the CPUs and the Phi available in each node with smart task assignment strategies resulted in an additional speedup of about 2x. Finally, multi-level computation reuse lead to an additional speedup of up to 2.46x on the parallel version. The level of performance attained with the proposed optimizations will allow the use of SA in large-scale studies.

关键词： Image segmentation Sensitivity analysis Optimization algorithm design and analysis Runtime Image analysis

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A dual splitting algorithm for distributed resource allocation problems 56

A dual splitting algorithm for distributed resource allocati...

引用

56th Annual IEEE Conference on Decision and Control (CDC)

作者： Xu, Jinming Zhu, Shanying Soh, Yeng Chai Xie, Lihua Nanyang Technol Univ Sch Elect & Elect Engn 50 Nanyang Ave Singapore 639798 Singapore Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn 800 Dong Chuan Rd Shanghai 200240 Peoples R China

ISBN: (纸本)9781509028733

We deal with general composite distributed resource allocation problems over networks, which arise from many application areas such as economic dispatch, demand response and network utility maximization. Conventionally, we have to resort to centralized or parallel approaches to solve these problems. It is well known that distributed solutions are more preferable due to their robustness to component failures and great scalability to the size of the network. In this paper, we propose an efficient algorithm, termed DuSPA, to solve the above problem in a distributed way. The algorithm is developed from the dual counterpart of the above problem leveraging on certain splitting techniques. We will show that the proposed algorithm is able to find the optimal solution with a non-ergodic convergence rate of O(1/k) in terms of fixed point residual for general (potentially non-smooth) convex cost functions with a smooth constitutive term. We also apply the proposed algorithm to the well-known economic dispatch problem and compare it with the state-of-the-art to show its effectiveness.

关键词： Convergence Resource management algorithm design and analysis Economics Generators Cost function Power systems

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An Automated Formal Process for Detecting Fault Injection Vulnerabilities in Binaries 16

An Automated Formal Process for Detecting Fault Injection Vu...

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16th IEEE International Conference on Trust, Security and Privacy in Computing and Communications / The 11th IEEE International Conference on Big Data Science and Engineering / The 14th IEEE International Conference on Embedded Software and Systems

作者： Given-Wilson, Thomas Jafri, Nisrine Lanet, Jean-Louis Legay, Axel INRIA Rennes France

ISBN: (纸本)9781509049066

Recently fault injection has increasingly been used both to attack software applications, and to test system robustness. Detecting fault injection vulnerabilities has been approached with a variety of different but limited methods. This paper proposes a general process without these limitations that uses model checking to detect fault injection vulnerabilities in binaries. The efficacy of this process is demonstrated by detecting vulnerabilities in the PRESENT binary.

关键词： Model checking Software Hardware Tools Encryption algorithm design and analysis Software algorithms

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A Medium-Grained Reconfigurable Architecture Targeting High-Level Synthesis Implementation 60

A Medium-Grained Reconfigurable Architecture Targeting High-...

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60th IEEE International Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Gorski, Jason Hanna, Darrin Oakland Univ Dept Elect & Comp Engn Rochester MI 48309 USA

ISBN: (纸本)9781509063895

High-level synthesis is increasingly being used to automatically translate existing software algorithms into hardware quickly and efficiently. Typically, the circuits created by HLS are implemented on Field-Programmable Gate Arrays (FPGAs). While the fine-grained architecture of an FPGA is well suited for general circuit implementation, it can result in excessive routing resource utilization for larger dataflow circuits such as those generated by HLS. As an alternative, we present a medium-grained reconfigurable architecture tailored to implementing HLS generated circuits. The proposed architecture achieves a 5.4x reduction in critical path delay compared to a standard FPGA during initial testing.

关键词： Field programmable gate arrays Routing Computer architecture Standards Transistors algorithm design and analysis Tools

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Numerical Modeling of PCB Power/Ground Plate-Pairs by DGTD Method Taking Into Account Decoupling Capacitors

Numerical Modeling of PCB Power/Ground Plate-Pairs by DGTD M...

引用

IEEE Electrical design of Advanced Packaging and Systems Symposium (EDAPS)

作者： Li, Ping Jiang, Li Jun Bagci, Hakan Univ Hong Kong Dept Elect & Elect Engn Hong Kong Hong Kong Peoples R China King Abdullah Univ Sci & Technol Div Comp Elect & Math Sci & Engn Thuwal 239556900 Saudi Arabia

ISBN: (纸本)9781538612392;9781538612385

A discontinuous Galerkin time-domain (DGTD) method is proposed in this work to analyze printed circuit board (PCB) power/ground plate-pair having arbitrarily shaped anti pads. To apply proper excitation source over the irregular anti pad, the implemented wave port magnetic current excitation is expanded by the electric eigen-modes of the anti-pad that are calculated via either numerical approach or analytical method. Based on the orthogonality of eigen-modes, the temporal mode expansion coefficient for each mode can be conveniently extracted. Besides, considering the presence of decoupling capacitors, the whole physical system can be split into field and circuit subsystems. For the field subsystem, it is governed by the Maxwell's equations, thus it will be solved by DGTD method. For the circuit subsystem, the modified nodal analysis (MNA) is applied. In order to achieve the coupling between the field and circuit subsystems, a lumpled port is defined at the interface between the field and circuit subsystems. To verify the proposed algorithm, several representative examples are benchmarked.

关键词： Capacitors Mathematical model Ports (Computers) Couplings Circuit subsystems algorithm design and analysis Scattering parameters

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An Efficient algorithm for Fault Detection by Directional Overcurrent Relay based on Current Waveform in Distribution Systems 2

An Efficient Algorithm for Fault Detection by Directional Ov...

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International Conference on Optimization of Electrical and Electronic Equipment (OPTIM) / Intl Aegean Conference on Electrical Machines and Power Electronics (ACEMP)

作者： Faiz, Jawad Mahmoudi, Ali Univ Tehran Coll Engn Sch Elect & Comp Engn Ctr Excellence Appl Electromagnet Syst Tehran *** Iran

ISBN: (纸本)9781509044894

Considering the growth of distributed energy generation systems in distribution networks, quick and precise protection and at the same time low cost is very perceptible. This protection includes directional relays beside overcurrent relays. The directional relays in the network require voltage and current relays;therefore, the cost of using this type of protection in the distribution network is very high. This is the reason that in directional relays operation only using current sensor can be a proper choice. This paper presents a simple and quick and at the same time efficient algorithm which is used to detect the fault from rising the current slope and determining the direction of the fault current from Lissajous curves. Simulation results based on the introduced algorithm are presented.

关键词： Relays Fault currents Current measurement Current transformers Circuit faults algorithm design and analysis Distributed power generation

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designing artificial neural networks using differential evolution for classifying DNA microarrays

Designing artificial neural networks using differential evol...

引用

IEEE Congress on Evolutionary Computation (CEC)

作者： Garro, Beatriz A. Rodriguez, Katya Vazquez, Roberto A. Univ Nacl Autonoma Mexico Inst Invest Matemat Aplicadas & Sistemas Ciudad Univ Mexico City DF Mexico Univ La Salle Fac Ingn Intelligent Syst Grp Benjamin Franklin 47 Col Condesa 06140 DF Mexico

ISBN: (纸本)9781509046010

The information obtained from the analysis of DNA microarrays is relevant to identify and predict illness, improve treatments, and to determine which genes are responsible to provoke a specific disease. However, the enormous quantity of genes and the few samples to be analyzed affect the performance of any classifier. For this reason, it is necessary to develop a methodology that combines a robust feature selection technique with a classification algorithm for classifying DNA microarrays. In this paper, we combine a feature selection technique based on the Artificial Bee Colony algorithm with an Artificial Neural Network (ANN). Furthermore, this ANN is automatically designed by a Differential Evolution (DE) algorithm that optimizes the synaptic weights, the architecture, and the transfer functions at the same time. To test the accuracy of the proposed methodology, we use the Leukemia AML-ALL dataset.

关键词： algorithm design and analysis DNA Transfer functions Classification algorithms Neurons Diseases Optimization

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A Cascade Framework for Masked Face Detection 8

A Cascade Framework for Masked Face Detection

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IEEE International Conference on Cybernetics and Intelligent Systems (CIS) / IEEE Conference on Robotics, Automation and Mechatronics (RAM)

作者： Bu, Wei Xiao, Jiangjian Zhou, Chuanhong Yang, Minmin Peng, Chengbin Shanghai Univ Sch Mechatron Engn & Automat Shanghai Peoples R China Chinese Acad Sci Ningbo Inst Ind Technol Inst Adv Mfg Technol Ningbo Zhejiang Peoples R China Ningbo Univ Technol Sch Elect & Informat Engn Ningbo Zhejiang Peoples R China

ISBN: (纸本)9781538631355

Accurately and efficiently detecting masked faces is increasingly meaningful, since it can be applied on tracking and identifying criminals or terrorists. As a unique face detection task, masked face detection is much more difficult because of extreme occlusions which leads to the loss of face details. Besides, there is almost no existing large-scale accurately labeled masked face dataset, which increase the difficulty of masked face detection. The CNN-based deep learning algorithms has made great breakthroughs in many computer vision areas including face detection. In this paper, we propose a new CNN-based cascade framework, which consists of three carefully designed convolutional neural networks to detect masked faces. Besides, because of the shortage of masked face training samples, we propose a new dataset called "MASKED FACE dataset" to finetune our CNN models. We evaluate our proposed masked face detection algorithm on the MASKED FACE testing set, and it achieves satisfactory performance.

关键词： Face Face detection Training Detectors Conferences algorithm design and analysis Testing

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Optimization combining derivative-free global exploration with derivative-based local refinement 56

Optimization combining derivative-free global exploration wi...

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56th Annual IEEE Conference on Decision and Control (CDC)

作者： Alimo, Shahrouz Ryan Beyhaghi, Pooriya Bewley, Thomas R. Univ Calif San Diego Dept MAE La Jolla CA 92093 USA Univ Calif San Diego Fac Dept MAE La Jolla CA USA

ISBN: (纸本)9781509028733

This paper proposes a hybrid optimization scheme combining an efficient (and, under the appropriate assumptions, provably globally convergent) derivative-free optimization algorithm (dubbed.-DOGS), to globally explore expensive nonconvex functions, with a new derivative-based local optimization algorithm, to maximally accelerate local convergence from promising feasible points discovered in parameter space. The resulting hybrid optimization scheme proceeds iteratively, automatically shifting between (derivative-free) global exploration and (derivative-based) local refinement as appropriate. The new derivative-based local refinement method implemented uses the Voronoi partitioning of all existing datapoints at each iteration to establish a "modified trust-region" around the current best point, within which derivative-based optimization is considered. The resulting algorithm is analyzed, and its global convergence is proven under certain assumptions on the objective function. Finally, the algorithm is applied to nonconvex optimization problems with multiple local minima, and its computational cost compared with that of the original Delta-DOGS algorithm.

关键词： Optimization Convergence Uncertainty Acceleration Linear programming Search problems algorithm design and analysis

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