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公开(公告)号:EP3992834A1
公开(公告)日:2022-05-04
申请号:EP21194564.7
申请日:2021-09-02
申请人: FUJITSU LIMITED
摘要: An information processing apparatus specifies a first pattern indicating a first layer included in first circuit data. The information processing apparatus generates, based on first wiring included in a second pattern indicating a second layer that is adjacent to the first layer and a slit included in the first pattern, second circuit data by changing the first pattern to a third pattern including second wiring corresponding to the first wiring. The information processing apparatus generates, based on the second circuit data, training data for machine learning.
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22.
公开(公告)号:EP3739497A3
公开(公告)日:2021-03-24
申请号:EP20184634.2
申请日:2018-12-13
申请人: TactoTek Oy
IPC分类号: G06F30/398 , B29C64/112 , B29C64/393 , B29K101/12 , B29L31/34 , B33Y10/00 , B33Y50/02 , G06F30/36 , G06F30/392 , G06F119/18 , G06F115/12
摘要: An electronic arrangement for facilitating circuit layout design in connection with target designs, the arrangement including at least one communication interface for transferring data, at least one processor for processing instructions and other data, and a memory for storing the instructions and other data. The at least one processor being configured, in accordance with the stored instructions, to cause: obtaining and storing information in a data repository hosted by the memory, receiving design input characterizing target design to be produced from a substrate, determining a mapping between locations of the target design and the substrate, and establishing and providing digital output comprising human and/or machine readable instructions indicative of the mapping to a receiving entity, such as a manufacturing equipment, e.g. printing, electronics assembly and/or forming equipment.
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公开(公告)号:EP3706029A1
公开(公告)日:2020-09-09
申请号:EP20158691.4
申请日:2020-02-21
申请人: FUJITSU LIMITED
发明人: AKIMA, Hisanao
IPC分类号: G06F30/27 , G06F30/36 , G06F30/13 , G06N3/00 , G06F119/06
摘要: A program for causing a computer to execute a process, the process includes acquiring, based on a compression model that is acquired by learning processing on a set of data generated by using a combination of values of a plurality of variables and that compresses dimensions of data, a point corresponding to data generated by using a predetermined combination of the values of the plurality of variables within a compressed space; acquiring, based on the point corresponding to the data generated by using the predetermined combination, a target point within the space corresponding to a target value of a characteristic changing in accordance with the values of the plurality of variables, and a regression model within the space for a predetermined variable of the plurality of variables, a change amount of the predetermined variable; and changing the value of the predetermined variable included in the predetermined combination by using the change amount.
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