Knowledge aided sparse

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August undefined, 2024

WebAug 1, 2001 · Integrated Computer-Aided Engineering Volume 8 Issue 3 August 2001 pp 257–281. Published: 01 August 2001 Publication History. 12 citation; 0; Downloads; Metrics. Total Citations 12. ... {38} J. Liebowitz, Knowledge management: learning from knowledge engineering, CRC Press, Boca Raton, FL, 2001. WebAug 1, 2024 · To cope with this problem, this paper proposes a knowledge-aided sparse recovery STAP algorithm with off-grid self-calibration (AO-SR-STAP). The snapshots are …

A Light-Weight CNN for Object Detection with Sparse Model and Knowledge …

WebKnowledge-Aided Normalized Iterative Hard Thresholding Algorithms for Sparse Recovery. Abstract: This paper deals with the problem of sparse recovery often found in … WebSep 25, 2024 · This paper deals with the problem of sparse recovery often found in compressive sensing applications exploiting a priori knowledge. In particular, we present … hima rathod

Publications - JunFang@uestc

WebSparse definition, thinly scattered or distributed: a sparse population. See more. WebAbstract:In this paper, novel knowledge-aided space-time adaptive processing (KA-STAP) algorithms using sparse representation/recovery (SR) techniques by exploiting the spatio … WebKnowledge-Aided Target Detection for Multistatic Passive Radar ... The challenge of unknown spectrum condition is also addressed, where block sparse Bayesian learning (BSBL) is exploited to derive the maximum-likelihood estimates (MLEs) of the unknown, temporally correlated signal. The numerical results indicate that the proposed KA … himar.benecafe.co.kr

(PDF) Prior Support Knowledge-Aided Sparse Bayesian …

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WebMar 9, 2016 · Support-Aided-Sparse-Bayesian-Learning This files implement the algorithm described in this article : "J. Fang, Y. Shen, F. Li, et al. Prior support knowledge-aided … WebNov 1, 2024 · In order to improve the performance of conformal array clutter suppression, a knowledge aided method based on semiparametric/sparse iterative covariance-based estimation STAP, named with KASPICE-STAP, is proposed here. The KASPICE-STAP method requires the knowledge of the clutter ridge spread of the testing range cell. himara elmshornWebgaps in the knowledge. inadequate knowledge. incomplete knowledge. information gaps. insufficient knowledge. knowledge deficit. knowledge gaps. lack of awareness. lack of expertise. himaraya hemp thc free bag

"WebAbstract:In this paper, novel knowledge-aided space-time adaptive processing (KA-STAP) algorithms using sparse representation/recovery (SR) techniques by exploiting the spatio-temporal sparsity are proposed to suppress the clutter for airborne pulsed Doppler radar. The proposed algorithms are not simple combinations of KA and SR techniques. " - Knowledge aided sparse

Knowledge aided sparse

Knowledge-Aided Target Detection for Multistatic Passive Radar

WebFeb 14, 2024 · Many signal processing applications require estimation of time-varying sparse signals, potentially with the knowledge of an imperfect dynamics model. In this paper, we propose an algorithm for dynamic filtering of time-varying sparse signals based on the sparse Bayesian learning (SBL) framework. ... Support knowledge-aided sparse …

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WebJun 28, 2024 · My main interests include machine learning, data mining and optimization, with special focus on the analysis, design and development of predictive models using mid to large-scale, real-world data ... WebFeb 1, 2024 · In order to obtain better performance, another SR-STAP method named knowledge aided semiparametric/sparse iterative covariance-based estimation STAP (KASPICE-STAP) [18] has been presented recently, which can accurately reconstruct the interference covariance matrix only using the CUT data.

WebSep 25, 2024 · This paper deals with the problem of sparse recovery often found in compressive sensing applications exploiting a priori knowledge. In particular, we present a knowledge-aided normalized iterative hard thresholding (KA-NIHT) algorithm that exploits information about the probabilities of nonzero entries. WebApr 11, 2024 · Aiming at the problem of sparse measurement points due to test conditions in engineering, a smoothing method based on zero-padding in the wavenumber domain is proposed to increase data density. Firstly, the principle of data extension and smoothing is introduced. The core idea of this principle is to extend the discrete data series by zero …

WebAug 20, 2024 · Since the clutter and outlier profiles are effectively estimated and distinguished by the knowledge-aided sparse recovery processing, robust clutter subspace estimation can be achieved for clutter suppression. Through the simulated and actual airborne-phased array radar data, it is verified that the proposed method can effectively … WebOct 27, 2024 · Jun Fang, Yanning Shen, Fuwei Li, and Hongbin Li, "Prior support knowledge-aided sparse Bayesian learning with partly erroneous support information", Technical report. (pdf) (Matlab codes) Journal Articles 2024

WebIn practical airborne radar, the interference signals in training snapshots usually lead to inaccurate estimation of the clutter covariance matrix (CCM) in space-time adaptive processing (STAP), which seriously degrade radar performance and even occur target self-nulling phenomenon. To solve this problem, a knowledge-aided sparse recovery (SR) …

WebApr 3, 2024 · Single shot, semantic bounding box detectors, trained in a supervised manner are popular in computer vision-aided visual inspections. These methods have several key limitations: (1) bounding boxes capture too much background, especially when images experience perspective transformation; (2) insufficient domain-specific data and cost to … hima photographyWebDec 29, 2024 · This study details the development of a lightweight and high performance model, targeting real-time object detection. Several designed features were integrated into the proposed framework to accomplish a light weight, rapid execution, and optimal performance in object detection. Foremost, a sparse and lightweight structure was … home improvement bannisterWebJun 22, 2024 · Sparse Bayesian learning has recently become successful in many compressed sensing problems. However, their performance critically relies on the … hima recoveryWebNov 1, 2024 · To improve the performance of clutter suppression in heterogeneous environments, a novel knowledge aided space-time adaptive processing method is proposed in this paper, which is based on... home improvement baby showerWebMar 28, 2016 · In this paper, novel knowledge-aided space-time adaptive processing (KA-STAP) algorithms using sparse representation/recovery (SR) techniques by exploiting the … hima renu watena chordsWebDec 21, 2024 · Aiming at the problem of low-altitude windshear wind speed estimation for airborne weather radar without independent identically distributed (IID) training samples, this paper proposes a low-altitude windshear wind speed estimation method based on knowledge-aided sparse iterative covariance-based estimation STAP (KASPICE-STAP). himareddy.com/portalWebApr 12, 2024 · Learning Transferable Spatiotemporal Representations from Natural Script Knowledge Ziyun Zeng · Yuying Ge · Xihui Liu · Bin Chen · Ping Luo · Shu-Tao Xia · Yixiao … home improvement banner image