A normalised real time recurrent learning algorithm
Signal Processing - Special issue on current topics in adaptive filtering for hands-free acoustic communication and beyond
Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Parameter Selection in Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
An elitist distributed particle swarm algorithm for RF IC optimization
Proceedings of the 2005 Asia and South Pacific Design Automation Conference
A space-time diffusion scheme for peer-to-peer least-squares estimation
Proceedings of the 5th international conference on Information processing in sensor networks
A scheme for robust distributed sensor fusion based on average consensus
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
A Novel Discrete Particle Swarm Optimization Algorithm for Job Scheduling in Grids
ICNC '08 Proceedings of the 2008 Fourth International Conference on Natural Computation - Volume 01
Diffusion least-mean squares with adaptive combiners
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Diffusion least-mean squares with adaptive combiners: formulation and performance analysis
IEEE Transactions on Signal Processing
Distributed Blind Adaptive Algorithms Based on Constant Modulus for Wireless Sensor Networks
ICWMC '10 Proceedings of the 2010 6th International Conference on Wireless and Mobile Communications
Parallel computation models of particle swarm optimization implemented by multiple threads
Expert Systems with Applications: An International Journal
Microprocessors & Microsystems
Evaluation of parallel particle swarm optimization algorithms within the CUDATM architecture
Information Sciences: an International Journal
Diffusion Least-Mean Squares Over Adaptive Networks: Formulation and Performance Analysis
IEEE Transactions on Signal Processing - Part II
Incremental Adaptive Strategies Over Distributed Networks
IEEE Transactions on Signal Processing
IEEE Communications Magazine
Quantized incremental algorithms for distributed optimization
IEEE Journal on Selected Areas in Communications
Preliminary Study on Wilcoxon Learning Machines
IEEE Transactions on Neural Networks
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In recent years because of substantial use of wireless sensor network the distributed estimation has attracted the attention of many researchers. Two popular learning algorithms: incremental least mean square (ILMS) and diffusion least mean square (DLMS) have been reported for distributed estimation using the data collected from sensor nodes. But these algorithms, being derivative based, have a tendency of providing local minima solution particularly for minimization of multimodal cost function. Hence for problems like distributed parameters estimation of IIR systems, alternative distributed algorithms are required to be developed. Keeping this in view the present paper proposes two population based incremental particle swarm optimization (IPSO) algorithms for estimation of parameters of noisy IIR systems. But the proposed IPSO algorithms provide poor performance when the measured data is contaminated with outliers in the training samples. To alleviate this problem the paper has proposed a robust distributed algorithm (RDIPSO) for IIR system identification task. The simulation results of benchmark IIR systems demonstrate that the proposed algorithms provide excellent identification performance in all cases even when the training samples are contaminated with outliers.