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Syst."],"published-print":{"date-parts":[[2024,10]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Dynamic Tensor Inversion (DTI) is an emerging issue in recent research, prevalent in artificial intelligence development frameworks such as TensorFlow and PyTorch. Traditional numerical methods suffer significant lagging error when addressing this issue. To address this, Zeroing-type Neural Dynamics (ZND) and Gradient-type Neural Dynamics (GND) are employed to tackle the DTI. However, these two methods exhibit inherent limitations in the resolution process, i.e. high computational complexity and low solution accuracy, respectively. Motivated by this technology gap, this paper proposes an Adaptive Coefficient Gradient Neural Dynamics (ACGND) for dynamically solving the DTI with an efficient and precise manner. Through a series of simulation experiments and validations in engineering applications, the ACGND demonstrates advantages in resolving DTI. The ACGND enhances computational efficiency by circumventing matrix inversion, thereby reducing computational complexity. Moreover, its incorporation of adaptive coefficients and activation functions enables real-time adjustments of the computational solution, facilitating rapid convergence to theoretical solutions and adaptation to non-statinary scenarios. Code is available at <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/github.com\/ACGND-Code-Implementation\">https:\/\/github.com\/Maia2333\/ACGND-Code-Implementation<\/jats:ext-link>.<\/jats:p>","DOI":"10.1007\/s40747-024-01480-6","type":"journal-article","created":{"date-parts":[[2024,5,31]],"date-time":"2024-05-31T09:09:24Z","timestamp":1717146564000},"page":"6143-6157","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["ACGND: towards lower complexity and fast solution for dynamic tensor inversion"],"prefix":"10.1007","volume":"10","author":[{"given":"Aiping","family":"Ye","sequence":"first","affiliation":[]},{"given":"Xiuchun","family":"Xiao","sequence":"additional","affiliation":[]},{"given":"Hua","family":"Xiao","sequence":"additional","affiliation":[]},{"given":"Chengze","family":"Jiang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6055-9648","authenticated-orcid":false,"given":"Cong","family":"Lin","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,5,31]]},"reference":[{"issue":"8","key":"1480_CR1","doi-asserted-by":"publisher","first-page":"7380","DOI":"10.1109\/JIOT.2022.3228781","volume":"10","author":"X Chai","year":"2022","unstructured":"Chai X, Fu J, Gan Z, Lu Y, Zhang Y, Han D (2022) Exploiting semi-tensor product compressed sensing and hybrid cloud for secure medical image transmission. 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We confirm that the manuscript has been read and approved by all named authors and that there are no other persons who satisfied the criteria for authorship but are not listed. We further confirm that the other of authors listed in the manuscript has been approved by all of us and that the second author prepared the revision information letter and addressed most of the comments. We confirm that we have given due consideration to the protection of intellectual property associated with this work and that there are no impediments to publication, including the timing of publication, with respect to intellectual property. In so doing we confirm that we have followed the regulations of our institutions concerning intellectual property. We understand that the Corresponding Author is the sole contact for the Editorial process (including Editorial Manager and direct communications with the office ). He is responsible for communicating with the other authors about progress, submissions of revision and final approve of proof. We confirm that we have provided a current email address which is accessible by the Corresponding Author and which has been configured to accept email from the Complex and Intelligent Systems Editorial Office.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}