State estimation and tracking problems: A comparison between kalman filter and recurrent neural networks

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3316, Issue , 2004, Pages 275-281

  Kumar Chenna, S ^a,b   Jain, Yogesh Kr ^a   Kapoor, Himanshu ^a   Bapi, Raju S ^a   Yadaiah, N ^c   Negi, Atul ^a   Seshagiri Rao, V ^d   Deekshatulu, B L ^a  

^a UNIVERSITY OF HYDERABAD   (India)

^b HONEYWELL TECHNOLOGY SOLUTIONS   (India)

^c JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY   (India)

^d INDIAN SPACE RESEARCH ORGANISATION   (India)

Author keywords

KF; Real time recurrent learning; Recurrent Neural Network; State estimation; Tracking

Indexed keywords

COMPLEX NETWORKS; KALMAN FILTERS; STATE ESTIMATION; SURFACE DISCHARGES;

DISCRETE TIME; ESTIMATION AND TRACKING; KF; NEURAL FILTERS; REAL TIME RECURRENT LEARNING ALGORITHMS; REAL-TIME RECURRENT LEARNING; RECURRENT NEURAL NETWORK (RNN); SIMULATION STUDIES;

RECURRENT NEURAL NETWORKS;

EID: 35048897081     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: None     Document Type: Review

References (8)

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