TY  - CHAP
AU  - Benítez-Pérez H.
AU  - Ortega-Arjona J. L.
ED  - Josphat Igadwa Mwasiagi
Y1  - 2011-01-21
PY  - 2011
T1  - Fault Localization upon Non-Supervised Neural Networks and Unknown Input Observers for Bounded Faults
N2  - Kohonen Self Organizing Maps (SOM) has found application in practical all fields, especially those which tend to handle high dimensional data. SOM can be used for the clustering of genes in the medical field, the study of multi-media and web based contents and in the transportation industry, just to name a few. Apart from the aforementioned areas this book also covers the study of complex data found in meteorological and remotely sensed images acquired using satellite sensing. Data management and envelopment analysis has also been covered. The application of SOM in mechanical and manufacturing engineering forms another important area of this book. The final section of this book, addresses the design and application of novel variants of SOM algorithms.
BT  - Self Organizing Maps
SP  - Ch. 28
UR  - https://doi.org/10.5772/13484
DO  - 10.5772/13484
SN  - 
PB  - IntechOpen
CY  - Rijeka
Y2  - 2024-04-19
ER  -