With the exponential increase of the data amount in the past years, data analytics and data processing became essential to any organization. As Moore's law has been exceeded since several years ago, the excessive ...
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ISBN:
(纸本)9781728180847
With the exponential increase of the data amount in the past years, data analytics and data processing became essential to any organization. As Moore's law has been exceeded since several years ago, the excessive data hides indeed highly useful information. The real challenge is to successfully extract the information using an effective process and with a reasonable cost. Therefore, various processing techniques have emerged. Indeed, big data processing methods can be classified into several types like batchbased, stream based, Graph based, DAG based, interactive based and visual based. All data processing techniques follow the same cycle: data collection, data preparation, data input, processing, data output/interpretation and data storage. Although having this similarity, these approaches have certainly different use cases, architectures and tools. This paper focuses on two types, namely: batch-based processing and stream-basedprocessing. After defining these two approaches, a comparative study is conducted and some key features are highlighted.
In recent years, iterative adaptive approach (IAA) has been proposed for super-resolution imaging in scanning radar, providing improved azimuth resolution. Traditional IAA involves computing the correlation matrix R f...
详细信息
ISBN:
(纸本)9798350360332;9798350360325
In recent years, iterative adaptive approach (IAA) has been proposed for super-resolution imaging in scanning radar, providing improved azimuth resolution. Traditional IAA involves computing the correlation matrix R for target scattering in each range cell, leading to iterative row-by-row solving and matrix inversion operations, causing high computational complexity. To this end, this paper proposes a Fast batch-based Iterative Adaptive Approach (FBB-IAA) that enables parallel and synchronized super-resolution processing of each range cell in the echo matrix. Additionally, it utilizes the two-dimensional conjugate gradient (2D-CG) method to avoid matrix inversion operation, significantly reducing the computational complexity compared to traditional IAA. Simulation results validate the superiority of the proposed method.
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