Non-linear Manifold Learning Algorithm Based on Intensity of Points

HUANG Shu-ping

Chinese

您当前的位置：

首页 >

文章列表页 >

Non-linear Manifold Learning Algorithm Based on Intensity of Points

更新时间：2026-09-04

- Non-linear Manifold Learning Algorithm Based on Intensity of Points
- Vol. 29, Issue 6, Pages: 10-13(2012)
- 作者机构：
  
  南开大学经济学院,天津,300071
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2012
- 稿件说明：
移动端阅览
黄淑萍. 基于点密集度的非线性流形学习算法[J]. 微电子学与计算机, 2012, 29(6): 10-13.

HUANG Shu-ping. Non-linear Manifold Learning Algorithm Based on Intensity of Points[J]. 2012, 29(6): 10-13.
黄淑萍. 基于点密集度的非线性流形学习算法[J]. 微电子学与计算机, 2012, 29(6): 10-13. DOI：

HUANG Shu-ping. Non-linear Manifold Learning Algorithm Based on Intensity of Points[J]. 2012, 29(6): 10-13. DOI：

摘要

提出一种样本点密集度的非线性流形学习算法.该算法提出了一个有效的数据点密集参数

能够很好地对非均匀数据的低维嵌入进行约束

其嵌效结果明显优于LLE算法.在人工和人脸数据集上的实验结果表明

新算法产生了较好的嵌入及分类结果.

Abstract

This paper presents a non-linear manifold learning algorithm based on intensity of sample points.It proposes an effective intensity parameter of sample points

which constraints the low-dimensional embedding of uneven data well.There is a better embedding result than LLE.The experimental results on the artificial and face datasets show that the new algorithm yields a better embedding and classification result.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Simulation on the DC characteristics of double heterojunction p-GaN HEMT with AlN/GaN hybrid buffer layer

Research on assembly action recognition based on MSS-YOLO-MPHands fusion architecture

Steganography model guided by attention mechanism and improved dense convolution

Implementation and verification of a dual-chain power gating strategy for low power design

Aerial vehicle detection algorithm based on multi-scale fusion and small-object enhancement

Related Author

No data

Related Institution

No data

AI问答

Postal code：100079
Tel：（010）53879206 Email：tmw@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09082226号-64 京公网安备11010602201714号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰