| Budget Amount *help |
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2015: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2014: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2013: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
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| Outline of Final Research Achievements |
Due to recent developments in information technology and measurement technology, the data that we deal with have become large and high-dimensional. Therefore, it becomes more important to establish information processing techniques for extracting substantial information from high-dimensional time-series data. In this study, we have proposed statistical algorithms based on slow feature analysis in order to realize extraction of latent features and information recognitions in high-dimensional time-series data.
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