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Dong H, He K, Shen X, Ma S, Wang H, Qiao C. Adaptive Intrawell Matched Stochastic Resonance with a Potential Constraint Aided Line Enhancer for Passive Sonars. Sensors (Basel) 2020; 20:s20113269. [PMID: 32521791 PMCID: PMC7309095 DOI: 10.3390/s20113269] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 05/28/2020] [Accepted: 06/01/2020] [Indexed: 11/26/2022]
Abstract
Remote passive sonar detection and classification are challenging problems that require the user to extract signatures under low signal-to-noise (SNR) ratio conditions. Adaptive line enhancers (ALEs) have been widely utilized in passive sonars for enhancing narrowband discrete components, but the performance is limited. In this paper, we propose an adaptive intrawell matched stochastic resonance (AIMSR) method, aiming to break through the limitation of the conventional ALE by nonlinear filtering effects. To make it practically applicable, we addressed two problems: (1) the parameterized implementation of stochastic resonance (SR) under the low sampling rate condition and (2) the feasibility of realization in an embedded system with low computational complexity. For the first problem, the framework of intrawell matched stochastic resonance with potential constraint is implemented with three distinct merits: (a) it can ease the insufficient time-scale matching constraint so as to weaken the uncertain affect on potential parameter tuning; (b) the inaccurate noise intensity estimation can be eased; (c) it can release the limitation on system response which allows a higher input frequency in breaking through the large sampling rate limitation. For the second problem, we assumed a particular case to ease the potential parameter aopt=1. As a result, the computation complexity is greatly reduced, and the extremely large parameter limitation is relaxed simultaneously. Simulation analyses are conducted with a discrete line signature and harmonic related line signature that reflect the superior filtering performance with limited sampling rate conditions; without loss of generality of detection, we considered two circumstances corresponding to H1 (periodic signal with noise) and H0 (pure noise) hypotheses, respectively, which indicates the detection performance fairly well. Application verification was experimentally conducted in a reservoir with an autonomous underwater vehicle (AUV) to validate the feasibility and efficiency of the proposed method. The results indicate that the proposed method surpasses the conventional ALE method in lower frequency contexts, where there is about 10 dB improvement for the fundamental frequency in the sense of power spectrum density (PSD).
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Affiliation(s)
- Haitao Dong
- School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, China; (H.D.); (K.H.); (X.S.); (S.M.)
- Key Laboratory of Ocean Acoustics and Sensing (Northwestern Polytechnical University), Ministry of Industry and Information Technology, Xi’an 710072, China
| | - Ke He
- School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, China; (H.D.); (K.H.); (X.S.); (S.M.)
- Key Laboratory of Ocean Acoustics and Sensing (Northwestern Polytechnical University), Ministry of Industry and Information Technology, Xi’an 710072, China
| | - Xiaohong Shen
- School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, China; (H.D.); (K.H.); (X.S.); (S.M.)
- Key Laboratory of Ocean Acoustics and Sensing (Northwestern Polytechnical University), Ministry of Industry and Information Technology, Xi’an 710072, China
| | - Shilei Ma
- School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, China; (H.D.); (K.H.); (X.S.); (S.M.)
- Key Laboratory of Ocean Acoustics and Sensing (Northwestern Polytechnical University), Ministry of Industry and Information Technology, Xi’an 710072, China
| | - Haiyan Wang
- School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, China; (H.D.); (K.H.); (X.S.); (S.M.)
- School of Electronic Information and Artificial Intelligence, Shaanxi University of Science and Technology, Xi’an 710021, China
- Correspondence:
| | - Changcheng Qiao
- The 27th Research Institude of China Electronic Technology Group Corporation, Zhengzhou 450047, China;
- Zhengzhou Key Laboratory of Underwater Information System Technology, Zhengzhou 450000, China
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Zeng GL. A fast method to emulate an iterative POCS image reconstruction algorithm. Med Phys 2018; 44:e353-e359. [PMID: 29027236 DOI: 10.1002/mp.12169] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2016] [Revised: 01/10/2017] [Accepted: 02/10/2017] [Indexed: 11/10/2022] Open
Abstract
PURPOSE Iterative image reconstruction algorithms are commonly used to optimize an objective function, especially when the objective function is nonquadratic. Generally speaking, the iterative algorithms are computationally inefficient. This paper presents a fast algorithm that has one backprojection and no forward projection. METHODS This paper derives a new method to solve an optimization problem. The nonquadratic constraint, for example, an edge-preserving denoising constraint is implemented as a nonlinear filter. The algorithm is derived based on the POCS (projections onto projections onto convex sets) approach. A windowed FBP (filtered backprojection) algorithm enforces the data fidelity. An iterative procedure, divided into segments, enforces edge-enhancement denoising. Each segment performs nonlinear filtering. RESULTS The derived iterative algorithm is computationally efficient. It contains only one backprojection and no forward projection. Low-dose CT data are used for algorithm feasibility studies. The nonlinearity is implemented as an edge-enhancing noise-smoothing filter. CONCLUSIONS The patient studies results demonstrate its effectiveness in processing low-dose x ray CT data. This fast algorithm can be used to replace many iterative algorithms.
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Affiliation(s)
- Gengsheng L Zeng
- Department of Engineering, Weber State University, Ogden, UT, 84408, USA.,Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, 84108, USA
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Wang X, Pan Q, Ding Z, Ma Z. Simultaneous Mean and Covariance Correction Filter for Orbit Estimation. Sensors (Basel) 2018; 18:s18051444. [PMID: 29734764 PMCID: PMC5982120 DOI: 10.3390/s18051444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/30/2018] [Revised: 04/28/2018] [Accepted: 05/01/2018] [Indexed: 06/08/2023]
Abstract
This paper proposes a novel filtering design, from a viewpoint of identification instead of the conventional nonlinear estimation schemes (NESs), to improve the performance of orbit state estimation for a space target. First, a nonlinear perturbation is viewed or modeled as an unknown input (UI) coupled with the orbit state, to avoid the intractable nonlinear perturbation integral (INPI) required by NESs. Then, a simultaneous mean and covariance correction filter (SMCCF), based on a two-stage expectation maximization (EM) framework, is proposed to simply and analytically fit or identify the first two moments (FTM) of the perturbation (viewed as UI), instead of directly computing such the INPI in NESs. Orbit estimation performance is greatly improved by utilizing the fit UI-FTM to simultaneously correct the state estimation and its covariance. Third, depending on whether enough information is mined, SMCCF should outperform existing NESs or the standard identification algorithms (which view the UI as a constant independent of the state and only utilize the identified UI-mean to correct the state estimation, regardless of its covariance), since it further incorporates the useful covariance information in addition to the mean of the UI. Finally, our simulations demonstrate the superior performance of SMCCF via an orbit estimation example.
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Affiliation(s)
- Xiaoxu Wang
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China.
| | - Quan Pan
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China.
| | - Zhengtao Ding
- School of Electrical and Electronic Engineering, The University of Manchester, Manchester M13 9PL, UK.
| | - Zhengya Ma
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China.
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Wang X, Li T, Sun S, Corchado JM. A Survey of Recent Advances in Particle Filters and Remaining Challenges for Multitarget Tracking. Sensors (Basel) 2017; 17:E2707. [PMID: 29168772 DOI: 10.3390/s17122707] [Citation(s) in RCA: 80] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/12/2017] [Revised: 11/19/2017] [Accepted: 11/20/2017] [Indexed: 11/30/2022]
Abstract
We review some advances of the particle filtering (PF) algorithm that have been achieved in the last decade in the context of target tracking, with regard to either a single target or multiple targets in the presence of false or missing data. The first part of our review is on remarkable achievements that have been made for the single-target PF from several aspects including importance proposal, computing efficiency, particle degeneracy/impoverishment and constrained/multi-modal systems. The second part of our review is on analyzing the intractable challenges raised within the general multitarget (multi-sensor) tracking due to random target birth and termination, false alarm, misdetection, measurement-to-track (M2T) uncertainty and track uncertainty. The mainstream multitarget PF approaches consist of two main classes, one based on M2T association approaches and the other not such as the finite set statistics-based PF. In either case, significant challenges remain due to unknown tracking scenarios and integrated tracking management.
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Fan J, Mohamed MG, Qian C, Fan X, Zhang G, Pecht M. Color Shift Failure Prediction for Phosphor-Converted White LEDs by Modeling Features of Spectral Power Distribution with a Nonlinear Filter Approach. Materials (Basel) 2017; 10:ma10070819. [PMID: 28773176 PMCID: PMC5551862 DOI: 10.3390/ma10070819] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/28/2017] [Revised: 06/27/2017] [Accepted: 07/07/2017] [Indexed: 11/16/2022]
Abstract
With the expanding application of light-emitting diodes (LEDs), the color quality of white LEDs has attracted much attention in several color-sensitive application fields, such as museum lighting, healthcare lighting and displays. Reliability concerns for white LEDs are changing from the luminous efficiency to color quality. However, most of the current available research on the reliability of LEDs is still focused on luminous flux depreciation rather than color shift failure. The spectral power distribution (SPD), defined as the radiant power distribution emitted by a light source at a range of visible wavelength, contains the most fundamental luminescence mechanisms of a light source. SPD is used as the quantitative inference of an LED's optical characteristics, including color coordinates that are widely used to represent the color shift process. Thus, to model the color shift failure of white LEDs during aging, this paper first extracts the features of an SPD, representing the characteristics of blue LED chips and phosphors, by multi-peak curve-fitting and modeling them with statistical functions. Then, because the shift processes of extracted features in aged LEDs are always nonlinear, a nonlinear state-space model is then developed to predict the color shift failure time within a self-adaptive particle filter framework. The results show that: (1) the failure mechanisms of LEDs can be identified by analyzing the extracted features of SPD with statistical curve-fitting and (2) the developed method can dynamically and accurately predict the color coordinates, correlated color temperatures (CCTs), and color rendering indexes (CRIs) of phosphor-converted (pc)-white LEDs, and also can estimate the residual color life.
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Affiliation(s)
- Jiajie Fan
- College of Mechanical and Electrical Engineering, Hohai University, Changzhou 213022, China.
- Changzhou Institute of Technology Research for Solid State Lighting, Changzhou 213161, China.
- Beijing Research Center, Delft University of Technology, Delft 2628, The Netherlands.
| | - Moumouni Guero Mohamed
- College of Mechanical and Electrical Engineering, Hohai University, Changzhou 213022, China.
| | - Cheng Qian
- Changzhou Institute of Technology Research for Solid State Lighting, Changzhou 213161, China.
| | - Xuejun Fan
- Changzhou Institute of Technology Research for Solid State Lighting, Changzhou 213161, China.
- Department of Mechanical Engineering, Lamar University, Beaumont, TX 77710, USA.
| | - Guoqi Zhang
- Changzhou Institute of Technology Research for Solid State Lighting, Changzhou 213161, China.
- Beijing Research Center, Delft University of Technology, Delft 2628, The Netherlands.
- EEMCS Faculty, Delft University of Technology, Delft 2628, The Netherlands.
| | - Michael Pecht
- Center for Advanced Life Cycle Engineering, University of Maryland, College Park, MD 20742, USA.
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Zhang H, He Q, Kong F. Stochastic Resonance in an Underdamped System with Pinning Potential for Weak Signal Detection. Sensors (Basel) 2015; 15:21169-95. [PMID: 26343662 DOI: 10.3390/s150921169] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/07/2015] [Revised: 08/19/2015] [Accepted: 08/24/2015] [Indexed: 11/27/2022]
Abstract
Stochastic resonance (SR) has been proved to be an effective approach for weak sensor signal detection. This study presents a new weak signal detection method based on a SR in an underdamped system, which consists of a pinning potential model. The model was firstly discovered from magnetic domain wall (DW) in ferromagnetic strips. We analyze the principle of the proposed underdamped pinning SR (UPSR) system, the detailed numerical simulation and system performance. We also propose the strategy of selecting the proper damping factor and other system parameters to match a weak signal, input noise and to generate the highest output signal-to-noise ratio (SNR). Finally, we have verified its effectiveness with both simulated and experimental input signals. Results indicate that the UPSR performs better in weak signal detection than the conventional SR (CSR) with merits of higher output SNR, better anti-noise and frequency response capability. Besides, the system can be designed accurately and efficiently owing to the sensibility of parameters and potential diversity. The features also weaken the limitation of small parameters on SR system.
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Vahabi Z, Kermani S. Desired Accuracy Estimation of Noise Function from ECG Signal by Fuzzy Approach. J Med Signals Sens 2012; 2:176-83. [PMID: 23717810 PMCID: PMC3660714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2012] [Accepted: 07/30/2012] [Indexed: 11/02/2022]
Abstract
Unknown noise and artifacts present in medical signals with non-linear fuzzy filter will be estimated and then removed. An adaptive neuro-fuzzy interference system which has a non-linear structure presented for the noise function prediction by before Samples. This paper is about a neuro-fuzzy method to estimate unknown noise of Electrocardiogram signal. Adaptive neural combined with Fuzzy System to construct a fuzzy Predictor. For this system setting parameters such as the number of Membership Functions for each input and output, training epochs, type of MFs for each input and output, learning algorithm and etc. is determined by learning data. At the end simulated experimental results are presented for proper validation.
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Affiliation(s)
- Zahra Vahabi
- Department of Electrical and Computer Engineering, Digital Signal Processing Lab, Isfahan University of Technology, Isfahan, 84156-83111, Iran,Address for correspondence: Mrs. Zahra Vahabi, Digital Signal Processing Research Lab, Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, 84156-83111, Iran. E-mail:
| | - Saeed Kermani
- Medical Image and Signal Processing Research Center, Department of Physics and Biomedical Engineering, Isfahan University of Medical Sciences, Isfahan, Iran
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