Relevant bibliographies by topics / Off-the-grid methods

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Academic literature on the topic 'Off-the-grid methods'

Author: Grafiati
Published: 23 February 2024

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Journal articles on the topic "Off-the-grid methods"

1

Laville, Bastien, Laure Blanc-Féraud, and Gilles Aubert. "Off-The-Grid Variational Sparse Spike Recovery: Methods and Algorithms." Journal of Imaging 7, no. 12 (2021): 266. http://dx.doi.org/10.3390/jimaging7120266.

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Gridless sparse spike reconstruction is a rather new research field with significant results for the super-resolution problem, where we want to retrieve fine-scale details from a noisy and filtered acquisition. To tackle this problem, we are interested in optimisation under some prior, typically the sparsity i.e., the source is composed of spikes. Following the seminal work on the generalised LASSO for measures called the Beurling-Lasso (BLASSO), we will give a review on the chief theoretical and numerical breakthrough of the off-the-grid inverse problem, as we illustrate its usefulness to the super-resolution problem in Single Molecule Localisation Microscopy (SMLM) through new reconstruction metrics and tests on synthetic and real SMLM data we performed for this review.
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2

Ling, Yun, Huotao Gao, Guobao Ru, Haitao Chen, Boya Li, and Ting Cao. "Grid Reconfiguration Method for Off-Grid DOA Estimation." Electronics 8, no. 11 (2019): 1209. http://dx.doi.org/10.3390/electronics8111209.

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Off-grid algorithms for direction of arrival (DOA) estimation have become attractive because of their advantages in resolution and efficiency over conventional ones. In this paper, we propose a grid reconfiguration direction of arrival (GRDOA) estimation method based on sparse Bayesian learning. Unlike other off-grid methods, the grid points of GRDOA are treated as dynamic parameters. The number and position of the grid points are varied iteratively via a root method and a fission process. Then, the grid gets reconfigured through some criteria. By iteratively updating the reconfigured grid, DOAs are estimated completely. Since GRDOA has fewer grid points, it has better computational efficiency than the previous methods. Moreover, GRDOA can achieve better resolution and relatively higher accuracy. Numerical simulation results validate the effectiveness of GRDOA.
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3

Sunday, Joshua, Chibuisi Chigozie, Ezekiel O. Omole, and John B. Gwong. "A Pair of Three-Step Hybrid Block Methods for the Solutions of Linear and Nonlinear First-Order Systems." European Journal of Mathematics and Statistics 3, no. 1 (2022): 13–23. http://dx.doi.org/10.24018/ejmath.2022.3.1.86.

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In this research paper, a pair of three-step hybrid block methods is derived for the solutions of linear and nonlinear first-order systems. The derivation is carried out with the aid of collocation and interpolation technique and the adoption of power series as basis function. The first and second three-step hybrid block methods are derived by incorporating a single and double off-grid point(s) respectively within the three-step integration interval. The methods derived were then applied on some linear and nonlinear first-order systems to test their accuracy and efficiency. The results obtained show that the three-step hybrid block method with two off-grid points performed better than the three-step hybrid block method with one off-grid point. It was also clear from the results obtained that the two methods derived performed better than the existing methods with which we compared our results. We further analyzed the basic properties of the methods derived. These properties include zero-stability, consistence, convergence and region of absolute stability.
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4

Liu, Song, Lan Tang, Yechao Bai, and Xinggan Zhang. "A Sparse Bayesian Learning-Based DOA Estimation Method With the Kalman Filter in MIMO Radar." Electronics 9, no. 2 (2020): 347. http://dx.doi.org/10.3390/electronics9020347.

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The direction of arrival (DOA) estimation problem as an essential problem in the radar system is important in radar applications. In this paper, considering a multiple-input and multiple-out (MIMO) radar system, the DOA estimation problem is investigated in the scenario with fast-moving targets. The system model is first formulated, and then by exploiting both the target sparsity in the spatial domain and the temporal correlation of the moving targets, a sparse Bayesian learning (SBL)-based DOA estimation method combined with the Kalman filter (KF) is proposed. Moreover, the performances of traditional sparse-based methods are limited by the off-grid issue, and Taylor-expansion off-grid methods also have high computational complexity and limited performance. The proposed method breaks through the off-grid limit by transforming the problem in the spatial domain to that in the time domain using the movement feature. Simulation results show that the proposed method outperforms the existing methods in the DOA estimation problem for the fast-moving targets.
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5

Atik, Md Atik-Uz-Zaman, and Abu Osman Al Mahbub. "Modeling Electricity Bill with the Reflection of CO2 Emissions and Methods of Implementing AMI for Smart Grid in Bangladesh." International Journal of Intelligent Systems and Applications 14, no. 5 (2022): 14–21. http://dx.doi.org/10.5815/ijisa.2022.05.02.

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Taking into consideration the lack of circumstantial alertness, automated fault analysis and labor-saving switches, the present-day electrical power grid system has been deteriorating day by day. The backbone technology of this grid system is too ill-fitted to the on-going demand for electricity. Despite the fact that the government of Bangladesh has set a new target of reaching the total power generation to be 40,000 MW by 2030. Hence the infrastructure and corresponding technology of the electrical power sector are required to be modernized to cope with this gigantic target within a short time. Another challenging fact is that the rapid expansion of population and power-intensive industrialization trigger off the carbon emissions that lead to global climate change. Also, the constraints of electricity generation capacity, unidirectional way of communication, failure of power equipment and dropping off conventional sources of energy impose burden on the existing electric power grid. This paper articulates the needfulness of reflection on CO2 emissions or reduction in the electricity bill of the consumer in developing countries by employing a mathematical model and by proposing some fruitful methods to implement AMI for smart grid.
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6

Zhou, Xiaoli, Hongqiang Wang, Yongqiang Cheng, Yuliang Qin, and Haowen Chen. "Radar Coincidence Imaging for Off-Grid Target Using Frequency-Hopping Waveforms." International Journal of Antennas and Propagation 2016 (2016): 1–16. http://dx.doi.org/10.1155/2016/8523143.

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Radar coincidence imaging (RCI) is a high-resolution staring imaging technique without the limitation of the target relative motion. To achieve better imaging performance, sparse reconstruction is commonly used. While its performance is based on the assumption that the scatterers are located at the prediscretized grid-cell centers, otherwise, off-grid emerges and the performance of RCI degrades significantly. In this paper, RCI using frequency-hopping (FH) waveforms is considered. The off-grid effects are analyzed, and the corresponding constrained Cramér-Rao bound (CCRB) is derived based on the mean square error (MSE) of the “oracle” estimator. For off-grid RCI, the process is composed of two stages: grid matching and off-grid error (OGE) calibration, where two-dimension (2D) band-excluded locally optimized orthogonal matching pursuit (BLOOMP) and alternating iteration minimization (AIM) algorithms are proposed, respectively. Unlike traditional sparse recovery methods, BLOOMP realizes the recovery in the refinement grids by overwhelming the shortages of coherent dictionary and is robust to noise and OGE. AIM calibration algorithm adaptively adjusts the OGE and, meanwhile, seeks the optimal target reconstruction result.
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7

Audu, Haliru, Ahmed Adamu, and OlaJide Oladipo. "A mixed-methods study on the determinants of solar home systems utilization in rural, off-grid Nigeria." Journal of Global Economics and Business 4, no. 14 (2023): 16–44. http://dx.doi.org/10.58934/jgeb.v4i14.171.

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This study employs a mixed-methods research approach to scrutinize the varied determinants influencing the willingness of off-grid rural households in Kwara State, Nigeria, to adopt Solar Home Systems (SHS). Integrating quantitative survey data from 400 households, qualitative findings derived from semi-structured interviews, and secondary data, the research provides a robust empirical framework. Through the application of Interval Regression and Tobit models, the analysis pinpoints income and education as key positive drivers towards SHS adoption, yet reveals a contrasting gender divide. Interestingly, a high level of satisfaction with the current energy provision emerges as a stumbling block to SHS acceptance. The research further identifies a distinct trend: households located further away from the grid exhibit a heightened propensity to pay for SHS, signifying a higher value attribution to SHS in these off-grid areas. The findings underscore the need for targeted interventions that encapsulate the diverse characteristics of households to ensure successful SHS promotion. The comprehensive insights garnered from this study offer indispensable guidance for policymakers and energy providers, bolstering strategic efforts to enhance SHS uptake and ultimately contributing to Nigeria's shift towards a more sustainable energy future.
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8

Ma, Jitong, Jiacheng Zhang, Zhengyan Yang, and Tianshuang Qiu. "Off-Grid DOA Estimation Using Sparse Bayesian Learning for MIMO Radar under Impulsive Noise." Sensors 22, no. 16 (2022): 6268. http://dx.doi.org/10.3390/s22166268.

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Direction of arrival (DOA) estimation is an essential and fundamental part of array signal processing, which has been widely used in radio monitoring, autonomous driving of vehicles, intelligent navigation, etc. However, it remains a challenge to accurately estimate DOA for multiple-input multiple-output (MIMO) radar in impulsive noise environments. To address this problem, an off-grid DOA estimation method for monostatic MIMO radar is proposed to deal with non-circular signals under impulsive noise. In the proposed method, firstly, based on the property of non-circular signal and array structure, a virtual array output was built and a real-valued sparse representation for the signal model was constructed. Then, an off-grid sparse Bayesian learning (SBL) framework is proposed and further applied to the virtual array to construct novel off-grid sparse model. Finally, off-grid DOA estimation was realized through the solution of the sparse reconstruction with high accuracy even in impulsive noise. Numerous simulations were performed to compare the algorithm with existing methods. Simulation results verify that the proposed off-grid DOA method enables evident performance improvement in terms of accuracy and robustness compared with other works on impulsive noise.
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9

Guo, Jia, Zhi Gang Li, Ya Ping Cheng, and Chun Yan Cui. "The Research of Two Staged Non-Isolated Photovoltaic Grid Connected Inverter Control Method." Advanced Materials Research 773 (September 2013): 139–42. http://dx.doi.org/10.4028/www.scientific.net/amr.773.139.

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Grid-connected inverter topologies and control methods are analyzed and compared on the basis of two non-isolated PV grid-connected inverter circuit topology as 3kVA grid connected PV systems. In this paper, the current control method, the DC bus voltage outer grid current inner loop of the dual closed-loop PI control method. Sampled signal through the system circuit for processing, resulting in a SPWM drive signal to control the conduction of the power devices off the grid current control.
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10

Chibuisi, C., B. O. Osu, S. O. Edeki, G. O. Akinlabi, C. Olunkwa, and O. P. Ogundile. "Implementation of Two-step Hybrid Block Adams Moulton Solution Methods for First Order Delay Differential Equations." Journal of Physics: Conference Series 2199, no. 1 (2022): 012017. http://dx.doi.org/10.1088/1742-6596/2199/1/012017.

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Abstract In this paper, Hybrid Block Adams Moulton Methods for step number k = 2 merged with two and three off-grid points were obtained and implemented in solving first order delay differential equations without the use of interpolation condition in evaluating the delay expression. The discrete schemes of these off-grid hybrid block methods were assessed through the continuous development of the linear multistep collocation method using a matrix conversion formula. The results obtained after the implementation of the proposed method in for numerical experiment of some first-order DDEs, the BHAMM2 schemes performed better and faster in satisfying the axioms for convergence and region of absolute stability than the BHAMM3 schemes at fixed step size z when examined with other existing methods.
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