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» Sensor Errors Prediction Using Neural Networks
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146
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EUSFLAT
2009
184views Fuzzy Logic» more  EUSFLAT 2009»
15 years 11 days ago
Recurrent Neural Kalman Filter Identification and Indirect Adaptive Control of a Continuous Stirred Tank Bioprocess
The aim of this paper is to propose a new Kalman Filter Recurrent Neural Network (KFRNN) topology and a recursive Levenberg-Marquardt (L-M) algorithm of its learning capable to est...
Ieroham S. Baruch, Carlos Román Mariaca Gas...
148
Voted
DSN
2005
IEEE
15 years 8 months ago
TIBFIT: Trust Index Based Fault Tolerance for Arbitrary Data Faults in Sensor Networks
Since sensor data gathering is the primary functionality of sensor networks, it is important to provide a fault tolerant method for reasoning about sensed events in the face of ar...
Mark D. Krasniewski, Padma Varadharajan, Bryan Rab...
126
Voted
IJON
2002
154views more  IJON 2002»
15 years 2 months ago
Nonlinear model predictive control of a cutting process
Nonlinear model predictive control (MPC) of a simulated chaotic cutting process is presented. The nonlinear MPC combines a neural-network model and a genetic-algorithm-based optim...
Primoz Potocnik, Igor Grabec
130
Voted
SECON
2007
IEEE
15 years 8 months ago
INPoD: In-Network Processing over Sensor Networks based on Code Design
—In this paper, we develop a joint Network Coding (NC)-channel coding error-resilient sensor-network approach that performs In-Network Processing based on channel code Design (IN...
Kiran Misra, Shirish S. Karande, Hayder Radha
ICDE
2006
IEEE
163views Database» more  ICDE 2006»
16 years 4 months ago
A Sampling-Based Approach to Optimizing Top-k Queries in Sensor Networks
Wireless sensor networks generate a vast amount of data. This data, however, must be sparingly extracted to conserve energy, usually the most precious resource in battery-powered ...
Adam Silberstein, Carla Schlatter Ellis, Jun Yang ...