Cellular neural network for seismic pattern recognition

Kou-Yuan Huang; Wen Hsuan Hsieh

doi:10.1190/segam2018-2997758.1

Cellular neural network for seismic pattern recognition

Kou-Yuan Huang^*, Wen Hsuan Hsieh

^*Corresponding author for this work

Department of Computer Science

Research output: Contribution to conference › Paper › peer-review

1 Scopus citations

Abstract

Cellular neural network is adopted for seismic pattern recognition. We design cellular neural network to behave as associative memory according to the stored patterns, and finish the training process of the network. Then we use this associative memory to recognize seismic testing patterns. In the experiment of seismic images, the bright spot pattern can be detected. The result of seismic pattern recognition can help the analysis and interpretation of seismic data.

Original language	English
Pages	2221-2225
Number of pages	5
DOIs	https://doi.org/10.1190/segam2018-2997758.1
State	Published - 1 Jan 2019
Event	88th Society of Exploration Geophysicists International Exposition and Annual Meeting, SEG 2018 - Anaheim, United States Duration: 14 Oct 2018 → 19 Oct 2018

Conference

Conference	88th Society of Exploration Geophysicists International Exposition and Annual Meeting, SEG 2018
Country	United States
City	Anaheim
Period	14/10/18 → 19/10/18

Access to Document

10.1190/segam2018-2997758.1

Link to publication in Scopus

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title = "Cellular neural network for seismic pattern recognition",

abstract = "Cellular neural network is adopted for seismic pattern recognition. We design cellular neural network to behave as associative memory according to the stored patterns, and finish the training process of the network. Then we use this associative memory to recognize seismic testing patterns. In the experiment of seismic images, the bright spot pattern can be detected. The result of seismic pattern recognition can help the analysis and interpretation of seismic data.",

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