Abstract:
Cooperative topology of Participle Swarm Optimization (PSO) heuristic (CPSO) is implemented for system identification over ad-hoc Networks. The main achievement is the de...Show MoreMetadata
Abstract:
Cooperative topology of Participle Swarm Optimization (PSO) heuristic (CPSO) is implemented for system identification over ad-hoc Networks. The main achievement is the development of PSO heuristic for system identification instead of the conventional diffusion topology of the Least Mean Square called DLMS algorithm which reveals a significant improvement in terms of the Mean Square Error (MSE). The CPSO heuristic demonstrates an important MSE convergence result beyond the theoretical boundary of noise variance. In the aggregation stage, each sensor exchanges the local best objective function along with the related local best estimate to near-by neighboring sensors. The simulations indicate that the developed CPSO approach achieves extraordinary MSE and MSD improvements against existing DLMS algorithms when the input block size and population are increased.
Date of Conference: 20-23 February 2023
Date Added to IEEE Xplore: 06 February 2024
ISBN Information: