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A Novel Vertical Wire-Bonding Compensation Structure Adaptively Modeled and Optimized With GRNN and GA Methods for System in Package.

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Title: A Novel Vertical Wire-Bonding Compensation Structure Adaptively Modeled and Optimized With GRNN and GA Methods for System in Package.
Authors: Zhu, Hao-Ran1 (AUTHOR) hrzhu86@gmail.com, Zhao, Ya-Li1 (AUTHOR) ylzhao@163.com, Lu, Jia-Guo2 (AUTHOR) jglu@ustc.edu.cn
Source: IEEE Transactions on Electromagnetic Compatibility. Dec2021, Vol. 63 Issue 6, p2082-2092. 11p.
Subjects: Artificial neural networks, Algorithms, Computational electromagnetics, Electric lines, Interfacial bonding, Mathematical optimization
Abstract: In this article, a novelvertical wire-bonding interconnect structure is intelligently modeled and optimized with general artificial neural network (GRNN) and genetic algorithm (GA) for multilayered system in package. A compensation structure is constructed with a hybrid inductive and capacitive technique, while a capacitive stripline with series inductive short-end via is designed underneath the 50-Ω transmission line. The GRNN algorithm is employed to build the electromagnetic model databases during the procedure of GA optimization. In comparison with the conventional optimization algorithm, the output performances can be directly achieved with collaboratively combined methods, which can significantly reduce the calculation time. From the measurement results, the return loss is improved significantly while the parasitic inductive behavior of the bonding wire is eliminated with the presented design. Moreover, compared with the traditional compensation techniques, no additional area is occupied on the surface plane of the wire-bonding interconnection, which is more suitable for the high-integrated circuit system. [ABSTRACT FROM AUTHOR]
Copyright of IEEE Transactions on Electromagnetic Compatibility is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: A Novel Vertical Wire-Bonding Compensation Structure Adaptively Modeled and Optimized With GRNN and GA Methods for System in Package.
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  Data: <searchLink fieldCode="AR" term="%22Zhu%2C+Hao-Ran%22">Zhu, Hao-Ran</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> hrzhu86@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Zhao%2C+Ya-Li%22">Zhao, Ya-Li</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> ylzhao@163.com</i><br /><searchLink fieldCode="AR" term="%22Lu%2C+Jia-Guo%22">Lu, Jia-Guo</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> jglu@ustc.edu.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22IEEE+Transactions+on+Electromagnetic+Compatibility%22">IEEE Transactions on Electromagnetic Compatibility</searchLink>. Dec2021, Vol. 63 Issue 6, p2082-2092. 11p.
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  Data: <searchLink fieldCode="DE" term="%22Artificial+neural+networks%22">Artificial neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Computational+electromagnetics%22">Computational electromagnetics</searchLink><br /><searchLink fieldCode="DE" term="%22Electric+lines%22">Electric lines</searchLink><br /><searchLink fieldCode="DE" term="%22Interfacial+bonding%22">Interfacial bonding</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: In this article, a novelvertical wire-bonding interconnect structure is intelligently modeled and optimized with general artificial neural network (GRNN) and genetic algorithm (GA) for multilayered system in package. A compensation structure is constructed with a hybrid inductive and capacitive technique, while a capacitive stripline with series inductive short-end via is designed underneath the 50-Ω transmission line. The GRNN algorithm is employed to build the electromagnetic model databases during the procedure of GA optimization. In comparison with the conventional optimization algorithm, the output performances can be directly achieved with collaboratively combined methods, which can significantly reduce the calculation time. From the measurement results, the return loss is improved significantly while the parasitic inductive behavior of the bonding wire is eliminated with the presented design. Moreover, compared with the traditional compensation techniques, no additional area is occupied on the surface plane of the wire-bonding interconnection, which is more suitable for the high-integrated circuit system. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of IEEE Transactions on Electromagnetic Compatibility is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1109/TEMC.2021.3064853
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 11
        StartPage: 2082
    Subjects:
      – SubjectFull: Artificial neural networks
        Type: general
      – SubjectFull: Algorithms
        Type: general
      – SubjectFull: Computational electromagnetics
        Type: general
      – SubjectFull: Electric lines
        Type: general
      – SubjectFull: Interfacial bonding
        Type: general
      – SubjectFull: Mathematical optimization
        Type: general
    Titles:
      – TitleFull: A Novel Vertical Wire-Bonding Compensation Structure Adaptively Modeled and Optimized With GRNN and GA Methods for System in Package.
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            NameFull: Zhu, Hao-Ran
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            NameFull: Zhao, Ya-Li
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            NameFull: Lu, Jia-Guo
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            – D: 01
              M: 12
              Text: Dec2021
              Type: published
              Y: 2021
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            – TitleFull: IEEE Transactions on Electromagnetic Compatibility
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