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An Assessment of Qualitative Performance of Machine Learning Architectures : Modular Feedback Networks

Author
MO CHEN1 ; GAUTAMA, Temujin2 ; MANDIC, Danilo P1
[1] Department of Electrical and Electronic Engineering, Communication and Signal Processing, Imperial College London, London SW7 2BT, United Kingdom
[2] Philips Leuven, Leuven 3001, Belgium
Source

IEEE transactions on neural networks. 2008, Vol 19, Num 1, pp 183-189, 7 p ; ref : 14 ref

CODEN
ITNNEP
ISSN
1045-9227
Scientific domain
Electronics; Computer science; Psychology, psychopathology, psychiatry
Publisher
Institute of Electrical and Electronics Engineers, New York, NY
Publication country
United States
Document type
Article
Language
English
Author keyword
Delay vector variance nonlinearity pipelined recurrent neural networks (PRNNs) qualitative performance sensitivity
Keyword (fr)
Analyse qualitative Analyse quantitative Analyse sensibilité Architecture modulaire Architecture réseau Espace phase Evaluation performance Génie biomédical Intelligence artificielle Méthode vectorielle Optimisation Processeur pipeline Retard Réseau neuronal récurrent Réseau neuronal Traitement signal Variance
Keyword (en)
Qualitative analysis Quantitative analysis Sensitivity analysis Modular architecture Network architecture Phase space Performance evaluation Biomedical engineering Artificial intelligence Vector method Optimization Pipeline processor Delay Recurrent neural nets Neural network Signal processing Variance
Keyword (es)
Análisis cualitativo Análisis cuantitativo Análisis sensibilidad Arquitectura modular Arquitectura red Espacio fase Evaluación prestación Ingeniería biomédica Inteligencia artificial Método vectorial Optimización Procesador oleoducto Retraso Red neuronal Procesamiento señal Variancia
Classification
Pascal
001 Exact sciences and technology / 001D Applied sciences / 001D02 Computer science; control theory; systems / 001D02C Artificial intelligence

Discipline
Computer science : theoretical automation and systems
Origin
Inist-CNRS
Database
PASCAL
INIST identifier
20005942

Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS

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