Heping Ding

406 citations
33 papers · 288 · h-index 10

Impact in

Papers in

Heping Ding

29 papers receiving 273 citations

Peers

Heping Ding
Comparison fields: 5 of 55
  • Signal Processing 157
  • Computational Mechanics 113
  • Computational Mathematics 2
  • Computer Vision and Pattern Recognition 38
  • Bioengineering 10
Replace Naoki Ono with:
Naoki Ono Japan
Yoshikazu Yamaguchi Japan
Huadong Wang China
Chin-Cheng Hsu Taiwan
Yung‐Fang Chen Taiwan
Refka Ghodhbani Saudi Arabia
Dusan Petranovic United States
Germano Nicollini Italy
Hao Shen China
Andrea Ferrise Italy
Heping Ding relative to Naoki Ono Japan Naoki Ono's profile →
Citations per field
00.5×4.8×
Naoki Ono · 1×
Citations per year

Countries citing papers authored by Heping Ding

Since Specialization
Citations

This map shows the geographic impact of Heping Ding's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Heping Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Heping Ding more than expected).

Fields of papers citing papers by Heping Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Heping Ding. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Heping Ding. The network helps show where Heping Ding may publish in the future.

Co-authors

The 25 scholars most cited alongside Heping Ding, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Heping Ding Line = papers co-authored together Heping Ding links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201554
2 201044
3 200725
4 201022
5 200718
6 202018
7 200218
8 202016
9
A survey of double-talk detection schemes for echo cancellation applications
20049
10 20119
11 20128
12 20046
13 20105
14 20035
15 20103
16 20063
17
DOUBLE-TALK DETECTION SCHEMES FOR ECHO CANCELLATION
20043
18 20183
19 20202
20 19922

About Heping Ding

Heping Ding is a scholar working on Signal Processing, Computational Mechanics, Biomedical Engineering, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering, having authored 33 papers that have together received 288 indexed citations. Recurring topics across this work include Speech and Audio Processing (19 papers), Advanced Adaptive Filtering Techniques (17 papers), Blind Source Separation Techniques (11 papers), Advanced Data Compression Techniques (5 papers), Advanced Sensor and Energy Harvesting Materials (4 papers), Nanomaterials and Printing Technologies (3 papers), Advanced Steganography and Watermarking Techniques (2 papers) and Digital Media Forensic Detection (2 papers). The work is most often cited by research in Signal Processing (157 citations), Computational Mechanics (113 citations), Computational Mathematics (2 citations), Computer Vision and Pattern Recognition (38 citations) and Bioengineering (10 citations). Heping Ding has collaborated with scholars based in Canada, China and United States. Frequent co-authors include Fuliang Yin, Lin Wang, Ye Tao, Lin Wang, Christophe Py, Ta‐Ya Chu, Afshin Dadvand, Henry Leung, Siyue Chen and Wei Zhou. Their work appears in journals such as IEEE Transactions on Audio Speech and Language Processing, IEEE Transactions on Instrumentation and Measurement, Journal of Luminescence, Applied Physics A and IEEE Transactions on Signal Processing.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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