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Advances in Neural Networks – ISNN 2019

16th International Symposium on Neural Networks, ISNN 2019, Moscow, Russia, July 10–12, 2019, Proceedings, Part I

  • Huchuan Lu
  • Huajin Tang
  • Zhanshan Wang
Conference proceedings ISNN 2019

Part of the Lecture Notes in Computer Science book series (LNCS, volume 11554)

Also part of the Theoretical Computer Science and General Issues book sub series (LNTCS, volume 11554)

Table of contents

  1. Front Matter
    Pages i-xxii
  2. Learning System, Graph Model, and Adversarial Learning

    1. Front Matter
      Pages 1-1
    2. Wen Yu, Xiaoou Li, Jesus Gonzalez
      Pages 3-10
    3. Anton Agafonov, Alexander Yumaganov
      Pages 11-18
    4. Tatiana T. Kaverzneva, Galina F. Malykhina, Dmitriy A. Tarkhov
      Pages 19-27
    5. Isaac Chairez, Alexander Poznyak, Alexander Nazin, Tatyana Poznyak
      Pages 28-38
    6. Ling Yu, Zhen Zhang, Xuetao Xie, Hua Chen, Jian Wang
      Pages 48-57
    7. Xingjian Chen, Jianbo Su, Jun Zhang
      Pages 58-66
    8. Yuriy Fedorenko, Valeriy Chernenkiy, Yuriy Gapanyuk
      Pages 67-76
    9. Yi Lu, Yaran Chen, Dongbin Zhao, Jianxin Chen
      Pages 97-105
    10. Yaoman Li, Irwin King
      Pages 106-115
    11. Bixiao Meng, Baomin XU, Erjing Zhou, Shuangyuan YU, Hongfeng Yin
      Pages 124-132
    12. Yun Luo, Li-Zhen Zhu, Bao-Liang Lu
      Pages 141-150
  3. Time Series Analysis, Dynamic Prediction, and Uncertain Estimation

    1. Front Matter
      Pages 163-163
    2. Ryotaro Miura, Lukáš Pichl, Taisei Kaizoji
      Pages 165-172
    3. Mikhail S. Tarkov
      Pages 194-201
    4. Rajesh Mangannavar, Gopalakrishnan Srinivasaraghavan
      Pages 202-212
    5. Rodrigo Rivera-Castro, Ivan Nazarov, Yuke Xiang, Alexander Pletneev, Ivan Maksimov, Evgeny Burnaev
      Pages 213-222
    6. Di Liu, Wenwu Yu, Simone Baldi
      Pages 232-239
    7. Lihua Zhou, Minrui Fei, Dajun Du, Wenting Li, Huosheng Hu, Aleksandar Rakić
      Pages 240-250
    8. Guoqiang Tan, Jidong Wang, Zhanshan Wang, Xiaolong Qian
      Pages 251-260
    9. Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov, Kirill Neklyudov, Dmitry Vetrov
      Pages 261-269
    10. Zhongting Jiang, Dong Wang, Jin Sun, Hengyue Shi, Huijie Shang, Yuehui Chen
      Pages 278-287
    11. Weidong Guan, Dengwei Yan, Lidan Wang, Shukai Duan
      Pages 288-296
  4. Model Optimization, Bayesian Learning, and Clustering

    1. Front Matter
      Pages 297-297
    2. Ninglei Fan, Yuping Wang, Junhua Liu, Yiu-ming Cheung
      Pages 299-308
    3. Seyed Jalaleddin Mousavirad, Azam Asilian Bidgoli, Hossein Ebrahimpour-Komleh, Gerald Schaefer, Iakov Korovin
      Pages 309-317
    4. Junhui Mei, Xinyi Le, Xiaoting Zhang, Charlie C. L. Wang
      Pages 328-339
    5. Tingting Liu, Chuyi Song, Jingqing Jiang
      Pages 351-358
    6. Jesús Silva, Noel Varela, Hugo Martínez Caraballo, Jesús García Guiliany, Luis Cabas Vásquez, Jorge Navarro Beltrán et al.
      Pages 359-369
    7. Mikhail Leontev, Alexander Mikheev, Kirill Sviatov, Sergey Sukhov
      Pages 370-378
    8. Hong Zhao, Zhi-Hui Zhan, Wei-Neng Chen, Xiao-Nan Luo, Tian-Long Gu, Ren-Chu Guan et al.
      Pages 379-388
    9. Yan Zhou, Yaochu Jin, Jinliang Ding
      Pages 389-398
    10. Jia-Xing Yang, Xiao-Feng Gong, Gui-Chen Yu
      Pages 399-408
    11. Evgenii Egorov, Kirill Neklydov, Ruslan Kostoev, Evgeny Burnaev
      Pages 409-417
    12. Manish Aggarwal, Madasu Hanmandlu
      Pages 418-425
    13. Katsiaryna Krasnashchok, Aymen Cherif
      Pages 426-433
    14. Kanghao Du, Ruizhuo Song, Qinglai Wei, Bo Zhao
      Pages 434-443

Other volumes

  1. Advances in Neural Networks – ISNN 2019
    16th International Symposium on Neural Networks, ISNN 2019, Moscow, Russia, July 10–12, 2019, Proceedings, Part I
  2. 16th International Symposium on Neural Networks, ISNN 2019, Moscow, Russia, July 10–12, 2019, Proceedings, Part II

About these proceedings

Introduction

This two-volume set LNCS 11554 and 11555 constitutes the refereed proceedings of the 16th International Symposium on Neural Networks, ISNN 2019, held in Moscow, Russia, in July 2019.

The 111 papers presented in the two volumes were carefully reviewed and selected from numerous submissions. The papers were organized in topical sections named: Learning System, Graph Model, and Adversarial Learning; Time Series Analysis, Dynamic Prediction, and Uncertain Estimation; Model Optimization, Bayesian Learning, and Clustering; Game Theory, Stability Analysis, and Control Method; Signal Processing, Industrial Application, and Data Generation; Image Recognition, Scene Understanding, and Video Analysis; Bio-signal, Biomedical Engineering, and Hardware.

 

Keywords

adaptive control systems artificial intelligence classification data mining estimation evolutionary algorithms genetic algorithms image processing image reconstruction image segmentation imaging systems learning algorithms linear matrix inequalities matrix algebra neural networks numerical methods process control signal detection signal processing Support Vector Machines (SVM)

Editors and affiliations

  • Huchuan Lu
    • 1
  • Huajin Tang
    • 2
  • Zhanshan Wang
    • 3
  1. 1.Dalian University of TechnologyDalianChina
  2. 2.Sichuan UniversityChengduChina
  3. 3.Northeastern UniversityShenyangChina

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-22796-8
  • Copyright Information Springer Nature Switzerland AG 2019
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-030-22795-1
  • Online ISBN 978-3-030-22796-8
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site
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