Results 251 to 260 of about 500,856 (298)
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Decorrelators for multi‐sensor systems in CDMA networks
European Transactions on Telecommunications, 1995AbstractIn this paper we consider a multi‐sensor detection problem in both additive white Gaussian noise (AWGN) and fading channels with the users using the channel based on a code division multiple access (CDMA) scheme. Several multi‐sensor detectors that have been studied previously do offer good performance; however, these detectors require the ...
Srinivas Kandala +2 more
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Multi-Sensor Multi-Network Positioning
2012This chapter discusses methods for positioning utilizing multiple sensors and networks. For achieving seamless positioning and navigation in a smartphone from satellite signal denied areas such as indoors to everywhere outdoors, various technologies to replace and assist satellite navigation, and flexible integration algorithms for measurement fusion ...
Heidi Kuusniemi, Yuwei Chen, Liang Chen
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Multi sensor data fusion within hierarchical neural networks
1990 IJCNN International Joint Conference on Neural Networks, 1990Presents a hierarchical neural network architecture which can achieve multisensor data fusion at feature level by combining the coherent activities of higher-level neurons in the architecture. The architecture learns very quickly and is highly stable and plastic. Initial results show promise.
J. Rajapakse, R. Acharya
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Autonomous Networked Multi-Sensor Imaging Systems
Imaging and Applied Optics Technical Papers, 2012A demonstration of automated networked multiple sensor operation in airborne environments was performed. This presentation describes the diverse sensors and imagery processing used to demonstrate autonomously interactive detection and tracking of multiple ground targets.
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Multi-Sensor Fusion Boolean Bayesian Filtering for Stochastic Boolean Networks
IEEE Transactions on Neural Networks and Learning Systems, 2023Stochastic Boolean networks (SBNs) take process noise into account, so it is better to fit the actual situation and has a wider application background than Boolean networks (BNs). However, the presence of noise influences us to estimate the real state of the system.
Fangfei Li, Yang Tang
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Design of Smart Car Networking System based on Multi-Sensor Network
2021 6th International Conference on Inventive Computation Technologies (ICICT), 2021Rapid development of intelligent methodologies will leverage novel approaches for enhancing the car monitoring and scheduling system. Hence, this paper studies the smart car networking system based on multi-sensor network. The key to the successful operation of active driving services lies in the selection of high-quality services from the massive ...
Rong Xu, Hui Liu, Harry Haoxiang Wang
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MULTI-SENSOR NEURAL-NETWORK PROCESSING OF NOISY SPEECH
International Journal of Neural Systems, 1999In this paper, a novel Artificial Neural-Network (ANN) based multi-sensor multi-band adaptive signal-processing scheme is described for enhancing acoustic-speech corrupted by real noise and reverberation. Numerically robust adaptation-algorithms are employed for the ANN based sub-band filters; and, new simulation experiments are reported using real ...
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Multi-sensor integration with imperfect communication networks
29th IEEE Conference on Decision and Control, 1990Centralized and distributed multi-sensor integration with uncertainties in the communication networks among the sensors are discussed. The uncertainties in the communication networks cause additional errors. However, the algorithms developed minimize the effects of communication network uncertainties in both the local estimation and central integration.
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Multi-sensor networked estimation in electric power grids
2011 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2011The performance of a continuous-discrete Kalman filter using multi-sensor observations with irregular sampling patterns is analyzed in terms of the dynamics of the associated (predicted) error-covariance matrix. Irregular sampling may occur as a result of differences in sampling rates and/or lack of synchrony in a geographically-distributed power ...
null Bei Yan +2 more
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Multi-sensor Fusion through Adaptive Bayesian Networks
2011Common sensory devices for measuring environmental data are typically heterogeneous, and present strict energy constraints; moreover, they are likely affected by noise, and their behavior may vary across time. Bayesian Networks constitute a suitable tool for pre-processing such data before performing more refined artificial reasoning; the approach ...
DE PAOLA, Alessandra +3 more
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