๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Robust identification

โœ Scribed by B.T. Poljak; Ja.Z. Tsypkin

Publisher
Elsevier Science
Year
1980
Tongue
English
Weight
851 KB
Volume
16
Category
Article
ISSN
0005-1098

No coin nor oath required. For personal study only.

โœฆ Synopsis

Abstraet~onvenient identification techniques based on maximum likelihood estimators (MLE) are very sensitive to deviations from assumed distributions of observations. Huber's approach to robust estimation is highly fruitful for solving identification problems under incomplete information. In the paper some robust estimators for nonlinear regression problems are proposed and their features are discussed.

๐Ÿ“œ SIMILAR VOLUMES

Robust identification in Hโˆž
Robust identification in Hโˆž
โœ Jonathan R Partington ๐Ÿ“‚ Article ๐Ÿ“… 1992 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 655 KB
Combining classifier decisions for robus
Combining classifier decisions for robust speaker identification
โœ Daniel J. Mashao; Marshalleno Skosan ๐Ÿ“‚ Article ๐Ÿ“… 2006 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 232 KB

In this work, we combine the decisions of two classifiers as an alternative means of improving the performance of a speaker recognition system in adverse environments. The difference between these classifiers is in their feature-sets. One system is based on the popular mel-frequency cepstral coeffic

eigenPulse: Robust human identification
eigenPulse: Robust human identification from cardiovascular function
โœ John M. Irvine; Steven A. Israel; W. Todd Scruggs; William J. Worek ๐Ÿ“‚ Article ๐Ÿ“… 2008 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 949 KB

This paper presents eigenPulse, a new method for human identification from cardiovascular function. Traditional biometric techniques, e.g. face and fingerprint, have used eigen analysis to exploit databases with tens of thousands of entries. One drawback of traditional biometrics is that the credent