Passivity and passification of quaternion‐valued memristive neural networks
In this paper, a class of memristive neural networks with quaternion‐valued connection weights is studied. By starting from some basic quaternion‐valued algorithms, the quaternion‐valued memristive system is obtained; then, some passivity criteria for the memristive neural networks are presented bas...
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| Veröffentlicht in: | Mathematical methods in the applied sciences 2020-03, Vol.43 (4), p.2032-2044 |
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| container_title | Mathematical methods in the applied sciences |
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| creator | Wei, Hongzhi Wu, Baowei Tu, Zhengwen |
| description | In this paper, a class of memristive neural networks with quaternion‐valued connection weights is studied. By starting from some basic quaternion‐valued algorithms, the quaternion‐valued memristive system is obtained; then, some passivity criteria for the memristive neural networks are presented based on some appropriate auxiliary functions. Furthermore, to tackle with the passification problem, two kinds of control protocols are designed. What should be mentioned is that, in the above derived conclusions, the partial order is employed, which can be employed to compare the “magnitude” of two different quaternions, and thus, the closed convex hull consisted by quaternion can be derived correspondingly. In the end, the analytical design are substantiated with two numerical results. |
| doi_str_mv | 10.1002/mma.6030 |
| format | Article |
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By starting from some basic quaternion‐valued algorithms, the quaternion‐valued memristive system is obtained; then, some passivity criteria for the memristive neural networks are presented based on some appropriate auxiliary functions. Furthermore, to tackle with the passification problem, two kinds of control protocols are designed. What should be mentioned is that, in the above derived conclusions, the partial order is employed, which can be employed to compare the “magnitude” of two different quaternions, and thus, the closed convex hull consisted by quaternion can be derived correspondingly. 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In the end, the analytical design are substantiated with two numerical results.</description><subject>Algorithms</subject><subject>Computational geometry</subject><subject>Convexity</subject><subject>Hulls</subject><subject>Memory devices</subject><subject>memristor</subject><subject>Neural networks</subject><subject>passification</subject><subject>Passivity</subject><subject>Quaternions</subject><subject>quaternion‐valued</subject><issn>0170-4214</issn><issn>1099-1476</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp10M1Kw0AUBeBBFKxV8BECbtyk3plkMpllKf5Bgy66H24yMzA1P-1M0tKdj-Az-iSm1q2rw4GPe-EQckthRgHYQ9PgLIMEzsiEgpQxTUV2TiZABcQpo-kluQphDQA5pWxCincMwe1cf4iw1dHm2KyrsHddG3U22g7YG9-O7fvza4f1YHTUmMa70LudiVozeKzH6Ped_wjX5MJiHczNX07J6ulxtXiJl2_Pr4v5Mq6YTCAubUXBIkjEilHJoKTaWpCC55LnJSQGM65tyZngPMltkgkrJGqjGS-FTqbk7nR247vtYEKv1t3g2_GjYgkHSbMshVHdn1TluxC8sWrjXYP-oCio41Zq3EodtxppfKJ7V5vDv04VxfzX_wBRTGyR</recordid><startdate>20200315</startdate><enddate>20200315</enddate><creator>Wei, Hongzhi</creator><creator>Wu, Baowei</creator><creator>Tu, Zhengwen</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><orcidid>https://orcid.org/0000-0002-4673-9834</orcidid></search><sort><creationdate>20200315</creationdate><title>Passivity and passification of quaternion‐valued memristive neural networks</title><author>Wei, Hongzhi ; Wu, Baowei ; Tu, Zhengwen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2930-bfc10fa09aac21920b1dff09758958b03ea65dfb5275538f367f79aded25b7d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Algorithms</topic><topic>Computational geometry</topic><topic>Convexity</topic><topic>Hulls</topic><topic>Memory devices</topic><topic>memristor</topic><topic>Neural networks</topic><topic>passification</topic><topic>Passivity</topic><topic>Quaternions</topic><topic>quaternion‐valued</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wei, Hongzhi</creatorcontrib><creatorcontrib>Wu, Baowei</creatorcontrib><creatorcontrib>Tu, Zhengwen</creatorcontrib><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><jtitle>Mathematical methods in the applied sciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wei, Hongzhi</au><au>Wu, Baowei</au><au>Tu, Zhengwen</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Passivity and passification of quaternion‐valued memristive neural networks</atitle><jtitle>Mathematical methods in the applied sciences</jtitle><date>2020-03-15</date><risdate>2020</risdate><volume>43</volume><issue>4</issue><spage>2032</spage><epage>2044</epage><pages>2032-2044</pages><issn>0170-4214</issn><eissn>1099-1476</eissn><abstract>In this paper, a class of memristive neural networks with quaternion‐valued connection weights is studied. By starting from some basic quaternion‐valued algorithms, the quaternion‐valued memristive system is obtained; then, some passivity criteria for the memristive neural networks are presented based on some appropriate auxiliary functions. Furthermore, to tackle with the passification problem, two kinds of control protocols are designed. What should be mentioned is that, in the above derived conclusions, the partial order is employed, which can be employed to compare the “magnitude” of two different quaternions, and thus, the closed convex hull consisted by quaternion can be derived correspondingly. In the end, the analytical design are substantiated with two numerical results.</abstract><cop>Freiburg</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1002/mma.6030</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0002-4673-9834</orcidid></addata></record> |
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| source | Wiley Online Library Journals Frontfile Complete |
| subjects | Algorithms Computational geometry Convexity Hulls Memory devices memristor Neural networks passification Passivity Quaternions quaternion‐valued |
| title | Passivity and passification of quaternion‐valued memristive neural networks |
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