Vector quantization and signal compression
Vector quantization and signal compression
Decentralized Estimation and Control for Multisensor Systems
Decentralized Estimation and Control for Multisensor Systems
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
Multi-target sensor management using alpha-divergence measures
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
A distributed algorithm for managing multi-target identities in wireless ad-hoc sensor networks
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
Decentralized sensor fusion with distributed particle filters
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
A robust architecture for distributed inference in sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Proceedings of the 4th international conference on Embedded networked sensor systems
Tracking multiple targets using binary proximity sensors
Proceedings of the 6th international conference on Information processing in sensor networks
Information fusion for wireless sensor networks: Methods, models, and classifications
ACM Computing Surveys (CSUR)
Decentralized State Initialization with Delay Compensation for Multi-modal Sensor Networks
Journal of VLSI Signal Processing Systems
Information fusion in wireless sensor networks
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Compressing Moving Object Trajectory in Wireless Sensor Networks
International Journal of Distributed Sensor Networks - Sensor Networks, Ubiquitous and Trustworthy Computing
Asynchronous distributed PF algorithm for WSN target tracking
Proceedings of the 2009 International Conference on Wireless Communications and Mobile Computing: Connecting the World Wirelessly
Probabilistic self-localization for sensor networks
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Target tracking with binary proximity sensors
ACM Transactions on Sensor Networks (TOSN)
Congestion-aware, loss-resilient bio-monitoring sensor networking for mobile health applications
IEEE Journal on Selected Areas in Communications - Special issue on wireless and pervasive communications for healthcare
IEEE Transactions on Signal Processing
Distributed sensor localization in random environments using minimal number of anchor nodes
IEEE Transactions on Signal Processing
Stability of cascaded fuzzy systems and observers
IEEE Transactions on Fuzzy Systems
Consensus-based distributed particle filters in sensor networks
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Tracking dynamic boundary fronts using range sensors
EWSN'08 Proceedings of the 5th European conference on Wireless sensor networks
Time-space-sequential distributed particle filtering with low-rate communications
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
INES'10 Proceedings of the 14th international conference on Intelligent engineering systems
Cooperative localization by using knowledge of self-organized regularity
Artificial Life and Robotics
An introduction to Bayesian techniques for sensor networks
WASA'10 Proceedings of the 5th international conference on Wireless algorithms, systems, and applications
Sequential stability analysis and observer design for distributed TS fuzzy systems
Fuzzy Sets and Systems
Multiple-Target Tracking With Binary Proximity Sensors
ACM Transactions on Sensor Networks (TOSN)
Pervasive and Mobile Computing
A predictive duty cycle adaptation framework using augmented sensing for wireless camera networks
ACM Transactions on Sensor Networks (TOSN)
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This paper describes two methodologies for performing distributed particle filtering in a sensor network. It considers the scenario in which a set of sensor nodes make multiple, noisy measurements of an underlying, time-varying state that describes the monitored system. The goal of the proposed algorithms is to perform on-line, distributed estimation of the current state at multiple sensor nodes, whilst attempting to minimize communication overhead. The first algorithm relies on likelihood factorization and the training of parametric models to approximate the likelihood factors. The second algorithm adds a predictive scalar quantizer training step into the more standard particle filtering framework, allowing adaptive encoding of the measurements. As its primary example, the paper describes the application of the quantization-based algorithm to tracking a manoeuvring object.The paper concludes with a discussion of the limitations of the presented technique and an indication of future avenues for enhancement.