Wireless sensor networks, including wireless acoustic sensor networks, have found applications in diverse areas including hearing aids, hands-free telephony and target tracking. The objective of this brief is to introduce a new sparsity regularization parameter in sparse distributed network estimation, to achieve a better estimation accuracy in comparison with existing sparse-aware algorithms. In order to further reduce the computational complexity, the algorithm has also been designed for heterogeneous sensor networks, where only a fraction of the sensor nodes use sparse-aware adaptive estimation schemes.by Shravan Kalyankar Kumar and Nithin V. Georg
Sparse approximation has now become a buzzword for classification in numerous research domains. We p...
Abstract—Wireless sensor networks are often designed to perform two tasks: sensing a physical field ...
This letter proposes a sparse diffusion algorithm for 1-bit compressed sensing (CS) in wireless sens...
Advances in wireless communication and adaptive signal processing has resulted in increased interest...
Abstract—The selection of the minimum number of sensors within a network to satisfy a certain estima...
Abstract The issue considered in the current study is the problem of adaptive distributed estimatio...
Abstract—The selection of the minimum number of sensors within a network to satisfy a certain estima...
We introduce a distributed adaptive estimation algorithm operating in an ideal fully connected senso...
Wireless networks have revolutionized nowadays world by providing real time cost-efficient service a...
The goal of this paper is to propose diffusion LMS techniques for distributed estimation over adapti...
The selection of the minimum number of sensors within a network to satisfy a certain estimation perf...
In this paper we propose distributed strategies for the estimation of sparse vectors over adaptive n...
Distributed signal processing algorithms have become a key approach for statistical inference in wir...
This article proposes diffusion LMS strategies for distributed estimation over adaptive networks tha...
The goal of this letter is to propose an adaptive and distributed approach to cooperative sensing fo...
Sparse approximation has now become a buzzword for classification in numerous research domains. We p...
Abstract—Wireless sensor networks are often designed to perform two tasks: sensing a physical field ...
This letter proposes a sparse diffusion algorithm for 1-bit compressed sensing (CS) in wireless sens...
Advances in wireless communication and adaptive signal processing has resulted in increased interest...
Abstract—The selection of the minimum number of sensors within a network to satisfy a certain estima...
Abstract The issue considered in the current study is the problem of adaptive distributed estimatio...
Abstract—The selection of the minimum number of sensors within a network to satisfy a certain estima...
We introduce a distributed adaptive estimation algorithm operating in an ideal fully connected senso...
Wireless networks have revolutionized nowadays world by providing real time cost-efficient service a...
The goal of this paper is to propose diffusion LMS techniques for distributed estimation over adapti...
The selection of the minimum number of sensors within a network to satisfy a certain estimation perf...
In this paper we propose distributed strategies for the estimation of sparse vectors over adaptive n...
Distributed signal processing algorithms have become a key approach for statistical inference in wir...
This article proposes diffusion LMS strategies for distributed estimation over adaptive networks tha...
The goal of this letter is to propose an adaptive and distributed approach to cooperative sensing fo...
Sparse approximation has now become a buzzword for classification in numerous research domains. We p...
Abstract—Wireless sensor networks are often designed to perform two tasks: sensing a physical field ...
This letter proposes a sparse diffusion algorithm for 1-bit compressed sensing (CS) in wireless sens...