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[PDF] Top 20 Performance Analysis of STAP Algorithms Based on Fast Sparse Recovery Techniques

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Performance Analysis of STAP Algorithms Based on Fast Sparse Recovery Techniques

Performance Analysis of STAP Algorithms Based on Fast Sparse Recovery Techniques

... SINR performance, we observe that the SL0 and the SpaRSA algorithms are suitable for STAP ...for STAP problems because it can achieve a good SINR performance when N d N s = 4N M ... See full document

18

Algorithms and Array Design Criteria for Robust Imaging in Interferometry

Algorithms and Array Design Criteria for Robust Imaging in Interferometry

... RSC techniques and a generalized notion of bispectrum observable (the ...a fast algorithm for selection of a minimum-variance set of these observables, which is based on the concept of minimum cycle ... See full document

157

Space-Time Adaptive Processing Based on Weighted Regularized Sparse Recovery

Space-Time Adaptive Processing Based on Weighted Regularized Sparse Recovery

... SINR performance is computed using the true clutter plus noise covariance matrix under the ideal case ...SR-STAP algorithms provide a narrower clutter notch and a better SINR performance ... See full document

18

Performance analysis of transformation 
		techniques with prediction algorithms on diagnosing carotid plaques

Performance analysis of transformation techniques with prediction algorithms on diagnosing carotid plaques

... prediction algorithms involving smart concepts is being developed for the medical diagnosis field ...the performance indications of different prediction algorithms which involves intelligent ... See full document

7

Complexity Analysis and Accuracy of Image Recovery Based on Signal Transformation Algorithms

Complexity Analysis and Accuracy of Image Recovery Based on Signal Transformation Algorithms

... the performance of 32 and 64 point FFT is computed applying multiple RADIX ...three algorithms: Radix-2, Radix-4 and Radix-8 is used for ...‘minutiae based approach’ the authors applied ‘image ... See full document

6

A fast STAP method using persymmetry covariance matrix estimation for clutter suppression in airborne MIMO radar

A fast STAP method using persymmetry covariance matrix estimation for clutter suppression in airborne MIMO radar

... enhance STAP performance with small training samples support, has been attracting increasing attentions of re- searchers and practitioners ...recently, based on the sparsity of clutter distribution ... See full document

13

A Novel Non-Homogeneous STAP Algorithm for Target-Like Signal Elimination Based on Sparse Reconstruction

A Novel Non-Homogeneous STAP Algorithm for Target-Like Signal Elimination Based on Sparse Reconstruction

... the performance of target detection in heterogeneous environments, training data selection techniques have been proposed, such as generalized inner product (GIP) algorithm [8, 9], adaptive power residue ... See full document

11

Deterministic aided single dataset STAP method based on sparse recovery in heterogeneous clutter environments

Deterministic aided single dataset STAP method based on sparse recovery in heterogeneous clutter environments

... (NHD) algorithms [11–15] have been applied in the het- erogeneous environments, such as the power-selected training (PST) algorithm [11] and the generalized inner product (GIP) algorithm ...acceptable ... See full document

14

Fast Iterative Subspace Algorithms for Airborne STAP Radar

Fast Iterative Subspace Algorithms for Airborne STAP Radar

... recursive algorithms in order to reduce the computational complexity of the conventional STAP algorithms and to deal with a possible nonhomogeneity of the data ...tracking algorithms as PAST, ... See full document

8

Compressive sensing for sparse approximations: constructions, algorithms, and analysis

Compressive sensing for sparse approximations: constructions, algorithms, and analysis

... a sparse collection of entries [CR09], Ames and Vavasis have used similar techniques to provide average case analysis of NP- HARD combinatorial optimization problems [AV09], and Vandenberghe and ... See full document

248

The utilization of data analysis techniques in predicting student performance in massive open online courses (MOOCs)

The utilization of data analysis techniques in predicting student performance in massive open online courses (MOOCs)

... the analysis, various areas have been explored, which can be used to predict performance, namely machine learning and social media ...current techniques, within our institution, can be adapted to ... See full document

18

ISAR Imaging Based on Iterative Reweighted Lp Block Sparse Reconstruction Algorithm

ISAR Imaging Based on Iterative Reweighted Lp Block Sparse Reconstruction Algorithm

... the performance of the proposed ISAR imaging ...some sparse signal recovery methods including BP method [20], SBL method [18], L 1 L 0 method [12] and S -method ... See full document

8

A Geo-Statistical Approach for Crime hot spot Prediction

A Geo-Statistical Approach for Crime hot spot Prediction

... SMSCT based NNHSC, K-Means and STAC clustering ...SMSCT based Nearest Neighbour Clustering algorithm is applied on preprocess dataset than number of cluster found is ...SMSCT based K-Means and STAC ... See full document

11

FPGA Hardware Accelerators - Case Study on Design Methodologies and Trade-Offs

FPGA Hardware Accelerators - Case Study on Design Methodologies and Trade-Offs

... in performance, design time, and resource utilization between the two design ...of algorithms is important because implementing different algorithms provides additional information on how they vary ... See full document

65

A Soft-Input Soft-Output Target Detection Algorithm for Passive Radar

A Soft-Input Soft-Output Target Detection Algorithm for Passive Radar

... algorithm based on Compressive Sensing (CS) ...under-determined sparse estimation problem, if some conditions on the sparsity and the number of available samples ...another sparse estimation ... See full document

12

Comprehensive Analytics of Dehazing: A Review

Comprehensive Analytics of Dehazing: A Review

... dehazing techniques proposes a framework that evacuates/ removes haziness from images and rewards the dehazed image a general sharpened appearance to get a clearer unmistakable quality and smooth ...dehazing ... See full document

5

An Investigation of Performance Analysis of Anomaly Detection Techniques for Big Data in SCADA Systems

An Investigation of Performance Analysis of Anomaly Detection Techniques for Big Data in SCADA Systems

... detection techniques for big data and this ignites a confusion for the data ...detection techniques based on nearest neighbours, clustering and statistical approaches and investigate the ... See full document

16

3 T Imaging of the Cochlear Nerve and Labyrinth in Cochlear Implant Candidates: 3D Fast Recovery Fast Spin Echo versus 3D Constructive Interference in the Steady State Techniques

3 T Imaging of the Cochlear Nerve and Labyrinth in Cochlear Implant Candidates: 3D Fast Recovery Fast Spin Echo versus 3D Constructive Interference in the Steady State Techniques

... 2). The spiral lamina and modiolus were adequately visualized with both techniques (Fig 3). Loss of fluid signal intensity in the labyrinth, particularly in the semicircular canals, was encountered on 3D FRFSE ... See full document

5

Comparative Analysis of Recall-based (Drawmetric) and Click-based (Locimetric) Graphical Password Authentication Schemes

Comparative Analysis of Recall-based (Drawmetric) and Click-based (Locimetric) Graphical Password Authentication Schemes

... recall-based algorithms, the most common drawbacks were the difficulty to remember the sequence of authentication required to be ...recall- based algorithms are most resistant to ... See full document

5

Machine Learning Credentials Inventiveness

Machine Learning Credentials Inventiveness

... This is one of my favorite algorithm and I use it quite frequently. It is a type of supervised learning algorithm that is mostly used for classification problems. Surprisingly, it works for both categorical and ... See full document

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