| Budget Amount *help |
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2014: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2013: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2012: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Outline of Final Research Achievements |
This research project intended to investigate neural network models based on complex and hypercomplex number systems, from the viewpoints of theoretical analysis and applications to practical/engineering problems. For dealing with high-dimensional data, such as color information and body coordinate systems, neural networks with hypercomplex number systems are expected to work more efficiently than conventional (real-valued) neural networks. In the term of this research project, several researches had been conducted, i.e., the analysis of fundamental properties for associative memories based on quaternionic (four dimensional hypercomplex number) Hopfield networks and the application of counting pedestrians from the sequences of scenery images.
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