• Complex-Valued Nonlinear Adaptive Filters With Applications in α-Stable Environments 

      Talebi, Sayed Pouria; Werner, Stefan; Mandic, Danilo (Journal article; Peer reviewed, 2019)
      A nonlinear adaptive filtering framework for processing complex-valued signals is derived. The introduced adaptive filter extends the fractional-order framework of the authors for dealing with real-valued signals to the ...
    • Distributed adaptive filtering of alpha-stable signals 

      Talebi, Sayed Pouria; Werner, Stefan; Mandic, Danilo (Journal article; Peer reviewed, 2018)
      A cost-effective framework for distributed adaptive filtering of α-stable signals over sensor networks is proposed. First, the filtering paradigm of α-stable signals through multiple observations made over a network of ...
    • Fractional-order correntropy adaptive filters for distributed processing of alpha-stable signals 

      Gogineni, Vinay Chakravarthi; Talebi, Sayed Pouria; Werner, Stefan; Mandic, Danilo (Peer reviewed; Journal article, 2020)
      This work revisits the problem of distributed adaptive filtering in multi-agent sensor networks. In contrast to classical approaches, the formulation relaxes the Gaussian assumption on the signal and noise to the generalized ...
    • Fractional-Order Correntropy Adaptive Filters for Distributed Processing of α -Stable Signals 

      Gogineni, Vinay Chakravarthi; Werner, Stefan (Journal article; Peer reviewed, 2020)
      This work revisits the problem of distributed adaptive filtering in multi-agent sensor networks. In contrast to classical approaches, the formulation relaxes the Gaussian assumption on the signal and noise to the generalized ...
    • On Stability and Convergence of Distributed Filters 

      Talebi, Sayedpouria; Werner, Stefan; Gupta, Vijay; Huang, Yih-Fang (Peer reviewed; Journal article, 2021)
      Recent years have bore witness to the proliferation of distributed filtering techniques, where a collection of agents communicating over an ad-hoc network aim to collaboratively estimate and track the state of a system. ...
    • Privacy-Preserving Distributed Maximum Consensus 

      Dasanadoddi Venkategowda, Naveen Kumar; Werner, Stefan (Peer reviewed; Journal article, 2020)
      We propose a privacy-preserving distributed maximum consensus algorithm where the local state of the agents and identity of the maximum state owner is kept private from adversaries. To that end, we reformulate the maximum ...