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Asynchronous adaptive networks
In a recent article [1] we surveyed advances related to adaptation, learning, and optimization over synchronous networks.
Distributed Clustering and Learning Over Networks
In doing so, the resulting algorithm enables the agents to identify their clusters and to attain improved learning and estimation accuracy over networks.
Asynchronous Adaptation and Learning over Networks - Part II: Performance Analysis
The expressions reveal how the various parameters of the asynchronous behavior influence network performance.
Asynchronous Adaptation and Learning over Networks --- Part I: Modeling and Stability Analysis
In this work and the supporting Parts II [2] and III [3], we provide a rather detailed analysis of the stability and performance of asynchronous strategies for solving distributed optimization and adaptation problems over networks.
Asynchronous Adaptation and Learning over Networks - Part III: Comparison Analysis
First, the results establish that the performance of adaptive networks is largely immune to the effect of asynchronous events: the mean and mean-square convergence rates and the asymptotic bias values are not degraded relative to synchronous or centralized implementations.
