Design of Feature Fusion Classifier for Underwater Targets Recognition

HOU Ping-kui; SHI Xi-zhi; LIN Liang-ji; WANG Xue-jun

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Design of Feature Fusion Classifier for Underwater Targets Recognition

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- Design of Feature Fusion Classifier for Underwater Targets Recognition
- Acta Electronica Sinica Vol. 29, Issue 4, Pages: 443-446(2001)
- 作者机构：
  
  1. 上海交通大学振动、冲击、噪声国家重点实验室,上海,200030
  2. 大连测控技术研究所,大连,116013
  3. 上海大众汽车有限公司,上海,201805
  4. 上海交通大学振动、冲击、噪声国家重点实验室上海,200030
  5. 大连测控技术研究所大连,116013
  6. 上海大众汽车有限公司上海,201805
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN911
- Published：2001
- 稿件说明：
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HOU Ping-kui, SHI Xi-zhi, LIN Liang-ji, et al. Design of Feature Fusion Classifier for Underwater Targets Recognition[J]. Acta Electronica Sinica, 2001, 29(4): 443-446.
DOI：

HOU Ping-kui, SHI Xi-zhi, LIN Liang-ji, et al. Design of Feature Fusion Classifier for Underwater Targets Recognition[J]. Acta Electronica Sinica, 2001, 29(4): 443-446. DOI：

摘要

本文对水下目标识别中的特征融合技术进行了研究

讨论了特征融合技术中的问题和解决途径

并给出了特征融合分类器的特性;设计了模糊融合分类器

给出了具体的算法.该分类器对样本在模式空间中的分布不做任何假定

注重类别间的相互约束

强调各个模式的独立作用

用类似于模糊并运算的方式综合这些作用.在实际应用中

通过与已有的分类器比较

表明模糊融合分类器能够综合多种信号特征

有效地提高了分类性能.

Abstract

This paper discusses feature fusion technique in underwater target recognition and proposes the method dealing with the problem encountered.Then

fuzzy fusion classifier (FFC) was designed based on this concept.FFC does not make any assumption about samples' distribution in pattern space

but emphasizes mutual restraints among classes and the independent role of each pattern and synthesizes those role by operation like combination in fuzzy logic.In practice

FFC can efficiently improve classification performance of recognition system by synthesizing features from multisensors.

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