In many classification problems, the class distribution is imbalanced. Learning from the
imbalance data is a remarkable challenge in the knowledge discovery and data mining field …

High resolution range profile (HRRP) has attracted increasing attention in radar automatic
target recognition (RATR). However, the target-aspect missing problem in noncooperative …

A novel machine learning method named multiclass multiple kernel learning based on
support vector data description with negative (MMKL-NSVDD) is developed to classify the …

提出了非均衡数据 目标识别 中 SVM 模型多参数优化选择方法. 首先从理论上分析了 SVM
模型多参数选择的内涵和必要性, 针对非均衡数据的分类识别, 基于 F 测度提 …

Radar target recognition has been studied widely, yet the problem is still far from a solution.
Early studies relied on holistic features or intensity values, which were sensitive to real-world …

Radar high-resolution range profile (HRRP) provides potentially discriminative information
on the geometry of target, which has been shown to be promising signatures for radar …

High-resolution range profile (HRRP) has attracted intensive attention from radar community
because it is easy to acquire and analyze. However, most of the conventional algorithms …

Low signal-to-noise ratio (SNR) in wideband radar reconnaissance degrades performance
of existing signal type recognition methods. To achieve higher correct recognition rate in low …

Radar high-resolution range profiles (HRRPs) are typical high-dimensional and
interdimension dependently distributed data, the statistical modeling of which is a …

One of the radar high‐resolution range profile (HRRP) recognition issues is the target‐
aspect sensitivity. Both theoretical analysis and real‐world data show that the HRRP shows …