ニューロサイエンス特論
科目名 Course Title |
授業コード |
単位数 |
配当年次 |
開講期間 Term |
科目分類 |
曜日 コマ |
教室 |
担当教員氏名 Instructor |
ニューロサイエンス特論
Advanced Neuro-Science |
P120740001 |
2 |
1 |
前期授業 |
専門科目 |
金3 |
B11-324 |
吉岡 理文 |
オフィスアワー
Office hours: Bldg. B11, 4th floor, Room No.405, Tuesday, 14:35-16:05
授業目標
1. Acquiring knowledge on fundamentals of information science and stochastic process.
2. Acquiring knowledge on neural networks and its application to intelligent signal processing.
3. Understanding the above topics based on implementations by using computer languages and simulations.
教科書
An Information-Theoretic Approach to Neuro Computing, Gustavo D. D. Obradovic(Springer).
授業の概要
1. Fundamentals of information science, Entropy, 2. Kullback-Leibler entropy, 3. Muttual information, 4. Coding theory, 5. Neural network models, 6. Learning paradigms, 7. Feed forward networks, 8. Stochastic recurrent networks, 9. Unsupervised competitive learning, 10. Linear feature extractions, 11. Principal component analysis, 12. Optimal reconstruction, 13. PCA and neural network, 14. Independent component analysis, 15. Mutual information as criterion of ICA
成績評価
Evaluation will be based on the reports.