Fujitsu Corporation

Yoichi Kochibe

Shohei Yamane

Takashi Yamazaki

Hiroaki Yamada

Toshiyasu Ohara

Masatoshi Ogawa

Hiroaki Watanabe

Yusuke Oishi

Takashi Kobayashi

The present invention relates to a machine learning program for causing a computer to execute a process. In an example, the process executed by the computer when the program is executed includes: acquiring a current distribution image by an equivalent circuit simulation based on circuit information; acquiring a shape image that indicates a shape of a circuit based on the circuit information; acquiring an EMI value by electromagnetic field analysis based on the circuit information; and generating an EMI prediction model by machine learning based on training data that includes the current distribution image, the shape image, and the EMI value.

Computer-readable recording medium storing machine learning program, information processing apparatus, and machine learning method

A radiated electromagnetic wave estimation is performed by a computer. The estimation process includes: converting a circuit diagram of an electronic circuit board into a combination of a plurality of partial circuits; and predicting radiated electromagnetic waves from the electronic circuit board by using a prediction result of a radiated electromagnetic wave for each of the partial circuits obtained by the converting.

Program storage medium, method, and information processing device for radiated electromagnetic wave estimation

A non-transitory computer-readable storage medium storing a n EMI calculation program that causes at least one computer to execute a process, the process includes inputting circuit information of a first circuit to a machine learning model; acquiring an EMI value at a certain frequency of the first circuit; selecting, based on an impedance characteristic of the first circuit and the EMI value at the certain frequency, first EMI information from a plurality of pieces of EMI information in each of which an impedance characteristic of each of a plurality of circuits is associated with EMI values at a plurality of frequencies of each of the plurality of circuits; and acquiring an EMI value at another frequency different from the certain frequency of the first circuit based on the EMI value at the certain frequency and the first EMI information.

Storage medium, EMI calculation method, and EMI calculation apparatus

An information processing apparatus calculates a value based on the lengths of wires included in inner layers selecting the inner layers other than outermost layers and layers adjacent to the outermost layers from among a plurality of layers included in circuit data. The information processing apparatus generates training data including first layer data corresponding to the patterns of the outermost layers, second layer data corresponding to the patterns of the layers adjacent to the outermost layers, and the value based on the lengths of the wires. The information processing apparatus trains a machine learning model by using the training data.

Machine learning method and computing system

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.

Training data generating method and computing system

An estimation method is performed by a computer for estimating a far field of electromagnetic waves or heat. The method includes: generating an emphasis pattern image obtained by emphasizing each target element of a pattern image of a target circuit by an emphasizing method that corresponds to a type of each target element, with respect to the target element which is at least a part of elements included in the target circuit; and estimating the far field of electromagnetic waves or heat radiated from the target circuit by an existing estimation model using the emphasis pattern image.

Growing community of inventors

Chiba, Japan

Yoichi Kochibe