Science Explorer Interactive view Map

Neural Networks Stability and Synchronization

Neural Networks Stability and Synchronization is a research topic within Computer Networks and Communications. Science Explorer counts 22k research works in it since 1955. 28.9% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the synchronization of complex dynamical networks, particularly addressing topics such as pinning control, global stability, time delays, impulsive control, and stochasticity in neural networks and memristor-based networks.

  • Synchronization
  • Complex Networks
  • Dynamical Systems
  • Pinning Control
  • Global Stability
  • Time Delays
  • Neural Networks
  • Impulsive Control
  • Stochasticity
  • Memristor-based Networks
Research works
22k
fractional, since 1955
In the world top 10%
6.4k
per year above
Top-10% rate
28.9%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+24%
the tick is no change

Which countries lead Neural Networks Stability and Synchronization research?

By volume, China and India publish the most (3.2k and 178 works in 2022–2025).

By volume, 2022–2025

  1. 1 China 3.2k works
  2. 2 India 178 works
  3. 3 United States 123 works
  4. 4 South Korea 105 works
  5. 5 Iran 63 works
  6. 6 France 56 works
  7. 7 Japan 48 works
  8. 8 Italy 48 works
  9. 9 United Kingdom 47 works
  10. 10 Australia 46 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 81.7%India: 4.6%United States: 3.1%South Korea: 2.7%6 others listed: 7.9%82%largest
China3,188 · 81.7%India178 · 4.6%United States123 · 3.1%South Korea105 · 2.7%6 others listed309 · 7.9%

Shares of the rows listed above, not of the whole node.

Which institutions lead Neural Networks Stability and Synchronization research?

By volume in 2022–2025, Southeast University publishes the most Neural Networks Stability and Synchronization research, followed by Harbin Institute of Technology and Northeastern University.

Who are the leading researchers in Neural Networks Stability and Synchronization?

The most-cited researchers publishing on Neural Networks Stability and Synchronization include Guanrong Chen, Peng Shi and Tasawar Hayat.

  1. 1 Guanrong Chen Hong Kong 5.4k citations
  2. 2 Peng Shi Australia 5k citations
  3. 3 Tasawar Hayat Pakistan 4.6k citations
  4. 4 Zidong Wang United Kingdom 4.4k citations
  5. 5 Jinde Cao China 4.2k citations
  6. 6 Leon O. Chua United States 4.1k citations
  7. 7 Frank L. Lewis United States 3.8k citations
  8. 8 Qing‐Long Han Australia 3.8k citations
  9. 9 Brian D. O. Anderson Australia 3.6k citations
  10. 10 C. L. Philip Chen Macau 3.6k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is Neural Networks Stability and Synchronization research done?

The largest centres of Neural Networks Stability and Synchronization research in 2022–2025 are Beijing (China), Nanjing (China), Shanghai (China) and Harbin (China). Among places with at least 20 works in it, it is an unusually large share of all research in Huangshi, Jinzhou and Qufu.

Largest cities, 2022–2025

  1. 1 Beijing China 269 works
  2. 2 Nanjing China 258 works
  3. 3 Shanghai China 170 works
  4. 4 Harbin China 159 works
  5. 5 Jinan China 132 works
  6. 6 Chongqing China 130 works
  7. 7 Wuhan China 128 works
  8. 8 Chengdu China 116 works
  9. 9 Xi'an China 108 works
  10. 10 Guangzhou China 108 works

Where it is the local speciality

  1. HuangshiCN · 38.4 works92×
  2. JinzhouCN · 50.7 works47×
  3. QufuCN · 38.2 works46×
  4. Ma'anshan CityCN · 30.3 works38×
  5. LinyiCN · 23.7 works38×
  6. LiaochengCN · 23.9 works28×
  7. QinhuangdaoCN · 37.0 works21×
← less than its size predictsmore →

Location quotient: how much more of its research is in Neural Networks Stability and Synchronization than the world average.

See Neural Networks Stability and Synchronization on the map

Where is the best place to study Neural Networks Stability and Synchronization?

Among universities, judged by research, Southeast University, Texas A&M University at Qatar and Southwest University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%60%mean 35.71%fractional works in this node (log) →share in the world top 10% →Southeast University: 90, 38.9%Texas A&M University at Qatar: 9, 46.6%Southwest University: 44, 31.3%Hunan Normal University: 28, 35.0%Yeungnam University: 15, 50.7%Xinjiang University: 45, 37.4%Shandong University of Science and Technology: 42, 25.1%Qingdao University: 28, 31.7%Harbin Institute of Technology: 79, 29.9%Northeastern University: 79, 30.5%Texas A&M University…Southeast UniversityHunan Normal Univers…Southwest University
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 Southeast UniversityChina 76.038.9%15.7×90 +55.9%
2 Texas A&M University at QatarQatar 74.246.6%73.7×9 +138.2%
3 Southwest UniversityChina 72.731.3%18.9×44 +448.1%
4 Hunan Normal UniversityChina 71.235.0%27.6×28 +483.0%
5 Yeungnam UniversitySouth Korea 69.350.7%16.0×15 +11.9%
6 Xinjiang UniversityChina 69.037.4%24.2×45 +85.0%
7 Shandong University of Science and TechnologyChina 67.925.1%20.0×42 +211.9%
8 Qingdao UniversityChina 67.631.7%12.0×28 +176.2%
9 Harbin Institute of TechnologyChina 67.429.9%11.3×79 +44.4%
10 Northeastern UniversityChina 67.230.5%21.0×79 +38.5%

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Neural Networks Stability and Synchronization research growing?

Output in 2018–2022 was 24% higher than in 2013–2017, peaking in 2022. The fastest-growing topics are Neural Networks Stability and Synchronization.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.