Information theoretic learning Renyi's entropy and kernel perspectives /
Information Theoretic Learning (ITL) is a framework where the conventional concepts of second order statistics (covariance, L2 distances, correlation functions) are substituted by scalars and functions with information theoretic underpinnings. This book deals with the ITL algorithms to adapt linear...
| Main Author: | Príncipe, J. C. |
|---|---|
| Other Authors: | SpringerLink (Online service) |
| Format: | eBook |
| Language: | English |
| Published: |
New York ; London :
Springer,
©2010.
New York ; London : [2010] |
| Physical Description: |
1 online resource (xxii, 515 pages) : illustrations. |
| Series: |
Information science and statistics.
|
| Subjects: |
CMU Electronic Access
Electronic Resource Click Here| Location | Call Number: | Status |
|---|---|---|
| CMU Electronic Access | Available |