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Recursive myriad-mean filters: adaptive algorithms and applications

SIGNAL PROCESSING 2017年 139卷 12-24页

作者： Marcos Ramirez, Juan Luis Paredes, Jose Univ Los Andes Dept Elect Engn Merida 5101 Venezuela

In this paper, a new class of recursive hybrid filtering structures is proposed for impulsive noise removal;the so-called recursive myriad-mean (RMyM) filters. More precisely, the output of the RMyM filter can be thought of as the sum of two independent weighted M-filters: the nonlinear weighted myriad acting on a subset of input samples and the linear weighted mean acting on a subset of filter's previous outputs. The uncoupled structure of the proposed filters takes into account the benefits of both weighted M-estimators: the robustness against impulsive noise of the myriad operator and the desired spectral response induced by the linear feedback. Least mean absolute (LMA) based adaptive algorithms are developed for designing these filtering structures under the equation error formulation framework. The results of extensive simulations are shown to evaluate both the behavior of the adaptive algorithms as well as the performance of the proposed recursive filters against impulsive noise. Additionally, taking into account the uncoupled structure of the proposed recursive filters, a decision feedback equalizer (DFE) based on the RMyM filter is proposed, where its performance is compared to those yielded by various conventional DFE structures, under different conditions of impulsive noise. (C) 2017 Elsevier B.V. All rights reserved.

关键词： adaptive algorithm Decision feedback equalizer Equation error formulation Hybrid nonlinear filters Recursive filters

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adaptive decoding algorithm based on multiplicity order of candidate sequences for TPC

Adaptive decoding algorithm based on multiplicity order of c...

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2014 International Conference on Information and Communications Technologies (ICT 2014)

作者： Min Tan Jing Tao Xiaoyu Dang Xiangbin Yu College of Electronic Information Engineering Nanjing University of Aeronautics and Astronautics China 210016

ISBN: (纸本)9781634392785

It is known that Turbo Product Codes (TPC) can be nearly optimally decoded by Chase-II algorithm, in which the Least Reliable Bits (LRBs) are chosen empirically to keep the size of the test patterns (sequences) relatively small and to reduce the decoding complexity. While there are also other adaptive techniques, where the decoder's LRBs adapt to the external parameter of the decoder like signal SNR level, a novel adaptive algorithm for TPC based on the statistics of an internal variable of the decoder itself is proposed in this paper. Different from the previous reported results, it collects the statistics of multiplicity order of the candidate sequences, i.e., the number of the same candidate sequences with the same minimum squared Euclidean distance returned from the decoding of test sequences. It is shown by Monte Carlo simulations that the proposed adaptive algorithm has only about 0.03dB coding loss but the average complexity of the proposed algorithm is about 45% less compared with Pyndiah's iterative decoding algorithm using the fixed LRBs parameter.

关键词： adaptive algorithm BER Complexity Least Reliable Bits Turbo Product Code

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A Block Parallel l_0-Norm Penalized Shrinkage and Widely Linear Affine Projection algorithm for adaptive Filter

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China Communications 2017年第1期14卷 86-97页

作者： Youwen Zhang Shuang Xiao Lu Liu Dajun Sun Acoustic Science and Technology Laboratory Harbin Engineering University Harbin 150001 China College of Underwater Acoustic Engineering Harbin Engineering University Harbin 150001 China

To improve the identification capability of AP algorithm in time-varying sparse system, we propose a block parallel l_0-SWL-DCD-AP algorithm in this paper. In the proposed algorithm, we first introduce the l_0-norm constraint to promote its application for sparse system. Second, we use the shrinkage denoising method to improve its track ability. Third, we adopt the widely linear processing to take advantage of the non-circular properties of communication signals. Last, to reduce the high computational complexity and make it easy to implemented, we utilize the dichotomous coordinate descent(DCD) iterations and the parallel processing to deal with the tapweight update in the proposed algorithm. To verify the convergence condition of the proposed algorithm, we also analyze its steadystate behavior. Several simulation are done and results show that the proposed algorithm can achieve a faster convergence speed and a lower steady-state misalignment than similar APA-type algorithm. When apply the proposed algorithm in the decision feedback equalizer(DFE), the bite error rate(BER) decreases obviously.

关键词： signal processing adaptive algorithm LMS l0-norm shrinkage linear DCD

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An adaptive artificial bee colony algorithm based on objective function value information

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APPLIED SOFT COMPUTING 2017年 55卷 384-401页

作者： Song, Xiaoyu Yan, Qifeng Zhao, Ming Shenyang Jianzhu Univ Sch Informat & Control Engn Shenyang 110168 Liaoning Provin Peoples R China

Artificial bee colony (ABC) algorithm is a novel biological-inspired optimization algorithm, which has many advantages compared with other optimization algorithm, such as less control parameters, great global optimization ability and easy to carry out. It has proven to be more effective than some evolutionary algorithms (EAs), particle swarm optimization (PSO) and differential evolution (DE) when testing on both benchmark functions and real issues. ABC, however, its solution search equation is poor at exploitation. For overcoming this insufficiency, two new solution search equations are proposed in this paper. They apply random solutions to take the place of the current solution as base vector in order to get more useful information. Exploitation is further improved on the basis of enhancing exploration by utilizing the information of the current best solution. In addition, the information of objective function value is introduced, which makes it possible to adjust the step-size adaptively. Owing to their respective characteristics, the new solution search equations are combined to construct an adaptive algorithm called MTABC. The methods our proposed balance the exploration and exploitation of ABC without forcing severe extra overhead in respect of function evaluations. The performance of the MTABC algorithm is extensively judged on a set of 20 basic functions and a set of 10 shifted or rotated functions, and is compared favorably with other improved ABCs and several state-of-the-art algorithms. The experimental results show that the proposed algorithm has a higher convergence speed and better search ability for almost all functions. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Optimization algorithm Artificial bee colony (ABC) algorithm Adjust dynamically adaptive algorithm Search equations

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Learning a hidden uniform hypergraph

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OPTIMIZATION LETTERS 2018年第1期12卷 55-62页

作者： Chang, Huilan Fu, Hung-Lin Shih, Chih-Huai Natl Univ Kaohsiung Dept Appl Math Kaohsiung 811 Taiwan Natl Chiao Tung Univ Dept Appl Math Hsinchu 30010 Taiwan

Motivated by applications in genome sequencing, Grebinski andKucherov (Discret Appl Math 88: 147-165, 1998) studied the graph learning problem which is to identify a hidden graph drawn from a given class of graphs with vertex set {1, 2,..., n} by edge-detecting queries. Each query tells whether a set of vertices induces any edge of the hidden graph or not. For the class of all hypergraphs whose edges have size at most r, Chodoriwsky and Moura (Theor Comput Sci 592: 1-8, 2015) provided an adaptive algorithm that learns the class in O(m(r) log n) queries if the hidden graph has m edges. In this paper, we provide an adaptive algorithm that learns the class of all r-uniform hypergraphs in mr log n + (6e)(r)m(r+1/2) queries if the hidden graph has m edges.

关键词： Graph learning Group testing Complex model adaptive algorithm

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Conformal Beam-Steering Antenna Controlled by a Raspberry Pi for Sustained High-Throughput Applications

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IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION 2018年第2期66卷 918-926页

作者： Pal, Arpan Mehta, Amit Goonesinghe, Hasanga Mirshekar-Syahkal, Dariush Nakano, Hisamatsu Swansea Univ Coll Engn Swansea SA2 8PP W Glam Wales Essex Univ Dept Comp Sci & Elect Engn Colchester CO4 3SQ Essex England Hosei Univ Sci & Engn Dept Tokyo 1848584 Japan

A complete autonomous system consisting of a beam-steerable hemispherical square-loop antenna (HSLA) controlled by a Raspberry Pi is presented for optimizing the throughput in a scattered and a poor signal-to-noise ratio environment. Four different indoor communication configurations at various distances were analyzed in the presence of interferences. In three configurations, HSLA performance was also compared to that of a standard monopole antenna link. It was found that HSLA can offer up to 1450% higher throughput and can withstand much higher interference levels before the system breaks. In terms of quality, this means sustaining compressed high-definition communications. In effect, it improves the system throughput for the test 2.4 GHz (802.11b/g/n) WiFi band. The uniqueness about the system is that it only uses single antenna for both sensing and communication. The algorithm works at application layer that controls the RF switch and antenna patterns at physical layer. Thus, the entire middle protocol layers are untouched. The system can easily be retrofitted to the existing nonadaptive communication systems.

关键词： adaptive algorithm beam steering high-definition (HD) video impedance matching Raspberry Pi received signal strength indicator square-loop antenna (SLA) throughput

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PTS-Based PAPR Reduction by Iterative p-Norm Minimization without Side Information in OFDM Systems

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IEICE TRANSACTIONS ON COMMUNICATIONS 2018年第3期E101B卷 856-864页

作者： Yoshida, Moeko Nashimoto, Hiromichi Miyajima, Teruyuki Ibaraki Univ Grad Sch Sci & Engn Hitachi Ibaraki 3168511 Japan Nippon Signal Co Ltd Kuki Saitama 3468524 Japan Ibaraki Univ Dept Elect & Elect Engn Hitachi Ibaraki 3168511 Japan JVCKENWOOD Engn Corp Yokohama Kanagawa Japan

This paper proposes a partial transmit sequences (PTS)based PAPR reduction method and a phase factor estimation method without side information for OFDM systems with QPSK and 16QAM modulation. In the transmitter, an iterative algorithm that minimizes the p-norm of a transmitted signal determines phase factors to reduce PAPR. Unlike conventional methods, the phase factors are allowed to take continuous values in a limited range. In the receiver, the phase factor is blindly estimated by evaluating the phase differences between the equalizer's output and its closest constellation points. Simulation results show that the proposed PAPR reduction method is more computationally efficient than the conventional PTS. Moreover, the combined use of the two proposed methods achieves a satisfactory tradeoff between PAPR and BER by limiting the phase factors properly.

关键词： OFDM PAPR PTS adaptive algorithm blind estimation

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AN adaptive FINITE ELEMENT METHOD FOR THE WAVE SCATTERING BY A PERIODIC CHIRAL STRUCTURE

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Journal of Computational Mathematics 2018年第6期36卷 845-865页

作者： Zhoufeng Wang Peiqi Huang School of Mathematics and Statistics Henan University of Science and Technology Henan 471023 and Department of Mathematics Nanjing University Nanjing 210093 China Department of Applied Mathematics Nanjing Forestry University Nanjing 210037 China

The electromagnetic wave propagation in the chiral medium is governed by Maxwell＇s equations together with the Drude-Born-Fedorov （constitutive） equations. The problem is simplified to a two-dimensional scattering problem, and is formulated in a bounded domain by introducing two pairs of transparent boundary conditions. An a posteriori error estimate associated with the truncation of the nonlocal boundary operators is established. Based on the a posteriori error control, a finite element adaptive strategy is presented for computing the diffraction problem. The truncation parameter is determined through sharp a posteriori error estimate. Numerical experiments are included to illustrate the robustness and effectiveness of our error estimate and the proposed adaptive algorithm.

关键词： Maxwell＇s equations A posteriori error analysis adaptive algorithm Scattering

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adaptive Control of Precision Guided Airdrop Systems with Highly Uncertain Dynamics

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2018年第5期41卷 1025-1035页

作者： Cacan, Martin R. Costello, Mark Georgia Inst Technol Woodruff Sch Mech Engn Ctr Adv Machine Mobil Atlanta GA 30322 USA Georgia Inst Technol Auton Guggenheim Sch Aerosp Engn Atlanta GA 30322 USA

The bulk of research in the field of precision guided airdrop systems has focused on improving landing accuracy in the presence of atmospheric winds that can exceed vehicle airspeed. One important challenge of parafoil systems is their highly uncertain flight dynamic behavior and control response, which can result from canopy degradation or an offnominal inflation event. This significantly impacts the ability to reach the target and can often lead to very large miss distances. This work addresses guided airdrop system model uncertainty with a novel combined direct and indirect adaptive control strategy to quickly characterize vehicle dynamics and lateral control sensitivity in flight. Extensive simulation and experimental flight testing indicate that the proposed adaptive algorithm is capable of high-accuracy landing in a large variety of degraded conditions, including unknown nonlinear changes in control sensitivity as well as control reversals. In comparison, current industry standard algorithms experience over an order of magnitude decrease in accuracy when tested under identical scenarios.

关键词： adaptive Control algorithm Parafoil Experimental Flight Test Airspeed Control Reversal adaptive algorithm Navigation algorithm GPS Multiple Input Multiple Output algorithms Ability

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An adaptive kernel regression method for 3D ultrasound reconstruction using speckle prior and parallel GPU implementation

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NEUROCOMPUTING 2018年 275卷 208-223页

作者： Wen, Tiexiang Yang, Feng Gu, Jia Chen, Shifu Wang, Lei Xie, Yaoqin Chinese Acad Sci Shenzhen Inst Adv Technol 1068 Xueyuan Ave Shenzhen 518055 Peoples R China Southern Med Univ Sch Biomed Engn Guangzhou 510515 Guangdong Peoples R China Univ Chinese Acad Sci 19A Yuquan Rd Beijing 100049 Peoples R China

Freehand three-dimensional (3D) ultrasound imaging is an attractive research area because it is capable of providing large field of view and high in-plane resolution image to allow better illustration of complex anatomy structures. However, reconstructed image is corrupted with speckle noise and artifacts in the conventional reconstructed volume data. In this paper, we propose a simple but effective adaptive kernel regression method for volume reconstruction from freehand swept B-scan images. By creating a linear model for estimating the homogeneous region of the B-scan image and learning the parameters of the model with a supervised learning method, the statistical characteristic of speckle can be well recovered. With the learned linear model of speckle, we can easily estimate the homogenous region and reconstruct image with speckle reduction and edge preservation via the adaptive turning of the smoothing parameters of the kernel regression. Our algorithm lends itself to parallel processing, and yields a 288 x speedup on a graphics processing unit (GPU). Experiments on the simulated data, ultrasonic abdominal phantom and in-vivo liver of human subject and comparisons with some classical and recent algorithms are used to demonstrate its improvements in both volume reconstruction accuracy and efficiency. (C) 2017 The Authors. Published by Elsevier B.V.

关键词： Three-dimensional ultrasound imaging Volume reconstruction Kernel regression adaptive algorithm GPU

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