This paper presents an efficient adaptive combination strategy for diffusion algorithms over adaptive networks in order to improve the robustness against the spatial variation of SNR over the network. The diffusion least-mean square (LMS) algorithm with the proposed combination rule and its mean transient analysis are included. Simulation results show that the diffusion LMS algorithm with our combiners outperforms those with existing static combiners and the incremental LMS algorithm
We study the problem of distributed adaptive estimation over networks where nodes cooperate to estim...
We consider the problem of distributed estimation, where a set of nodes is required to collectively ...
We show how the convergence time of an adaptive network can be estimated in a distributed manner by ...
This paper presents an efficient adaptive combination strategy for the distributed estimation proble...
In this paper, we develop a modified adaptive combination strategy for the distributed estimation pr...
We propose diffusion least-mean-square (LMS) algorithms that use multi-combination step. We allow ea...
We formulate and study distributed estimation algorithms based on diffusion protocols to implement c...
This paper analyzes the implementation of least-mean-squares (LMS)-based, adaptive diffusion algorit...
In this work, we analyze the mean-square performance of different strategies for distributed estimat...
In this paper, the problem of distributed estimation over adaptive networks is studied. A new diffus...
To address the conflicting requirement of fast convergence rate and low misadjustment, a new non-par...
In this paper we consider the issue of distributed adaptive estimation over sensor networks. To deal...
International audienceDiffusion LMS is an efficient strategy for solving distributed optimization pr...
We propose a new diffusion least mean squares algorithm that utilizes adaptive gains in the adaptati...
International audienceDiffusion adaptation is a powerful strategy for distributed estimation and lea...
We study the problem of distributed adaptive estimation over networks where nodes cooperate to estim...
We consider the problem of distributed estimation, where a set of nodes is required to collectively ...
We show how the convergence time of an adaptive network can be estimated in a distributed manner by ...
This paper presents an efficient adaptive combination strategy for the distributed estimation proble...
In this paper, we develop a modified adaptive combination strategy for the distributed estimation pr...
We propose diffusion least-mean-square (LMS) algorithms that use multi-combination step. We allow ea...
We formulate and study distributed estimation algorithms based on diffusion protocols to implement c...
This paper analyzes the implementation of least-mean-squares (LMS)-based, adaptive diffusion algorit...
In this work, we analyze the mean-square performance of different strategies for distributed estimat...
In this paper, the problem of distributed estimation over adaptive networks is studied. A new diffus...
To address the conflicting requirement of fast convergence rate and low misadjustment, a new non-par...
In this paper we consider the issue of distributed adaptive estimation over sensor networks. To deal...
International audienceDiffusion LMS is an efficient strategy for solving distributed optimization pr...
We propose a new diffusion least mean squares algorithm that utilizes adaptive gains in the adaptati...
International audienceDiffusion adaptation is a powerful strategy for distributed estimation and lea...
We study the problem of distributed adaptive estimation over networks where nodes cooperate to estim...
We consider the problem of distributed estimation, where a set of nodes is required to collectively ...
We show how the convergence time of an adaptive network can be estimated in a distributed manner by ...