| LDR | | 00000nmm u2200205 4500 |
| 001 | | 000000330084 |
| 005 | | 20241023134429 |
| 008 | | 181129s2018 ||| | | | eng d |
| 020 | |
▼a 9780438208834 |
| 035 | |
▼a (MiAaPQ)AAI10744636 |
| 035 | |
▼a (MiAaPQ)grad.sunysb:13626 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
| 049 | 1 |
▼f DP |
| 082 | 0 |
▼a 519 |
| 100 | 1 |
▼a Kong, Chi. |
| 245 | 10 |
▼a Information Geometry and Dimensionality Reduction. |
| 260 | |
▼a [S.l.] :
▼b State University of New York at Stony Brook.,
▼c 2018 |
| 260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2018 |
| 300 | |
▼a 125 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B. |
| 500 | |
▼a Adviser: Andrew P. Mullhaupt. |
| 502 | 1 |
▼a Thesis (Ph.D.)--State University of New York at Stony Brook, 2018. |
| 520 | |
▼a In the context of information geometry, the framework of differential geometry is applied to probability theory. It has a wide range of applications not limited to statistical inference, including image and signal processing, statistical learnin |
| 520 | |
▼a To summarize our main contributions: 1) We generalize information distance to MIMO LTI systems. When cepstrum are used as coordinates of the manifold, the geometry becomes Euclidean with nice theoretical and computational properties. 2) We devel |
| 590 | |
▼a School code: 0771. |
| 650 | 4 |
▼a Applied mathematics. |
| 690 | |
▼a 0364 |
| 710 | 20 |
▼a State University of New York at Stony Brook.
▼b Applied Mathematics and Statistics. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 79-12B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0771 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2018 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14996835
▼n KERIS |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a 관리자
▼b 관리자 |