23、FPGA-Based Hardware Accelerators for DBSCAN Algorithm

FPGA-Based Hardware Accelerators for DBSCAN Algorithm

1. Introduction to DBSCAN Algorithm

DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is a clustering algorithm that excels in identifying clusters of arbitrary shape from large datasets with noise. Unlike other clustering algorithms such as K-means, DBSCAN does not require the user to specify the number of clusters beforehand. Instead, it identifies dense regions of points, marking outliers as noise. The core concepts of DBSCAN include:

• Epsilon (ε) : The maximum distance between two points for them to be considered neighbors.
• MinPts : The minimum number of points required to form a dense region.

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