• Adaptive Graph Filters in Reproducing Kernel Hilbert Spaces: Design and Performance Analysis 

      Elias, Vitor; Gogineni, Vinay Chakravarthi; Martins, Wallace; Werner, Stefan (Peer reviewed; Journal article, 2021)
      This paper develops adaptive graph filters that operate in reproducing kernel Hilbert spaces. We consider both centralized and fully distributed implementations. We first define nonlinear graph filters that operate on ...
    • ADMM for Sparse-Penalized Quantile Regression with Non-Convex Penalties 

      Werner, Stefan; Gogineni, Vinay Chakravarthi; Dasanadoddi Venkategowda, Naveen Kumar (Chapter, 2022)
      This paper studies quantile regression with non-convex and non-smooth sparse-penalties, such as minimax concave penalty (MCP) and smoothly clipped absolute deviation (SCAD). Although iterative coordinate descent and local ...
    • ANN based respiration detection using UWB radar 

      Blehr, Harald (Master thesis, 2017)
      Non-contact detection of human respiration has many possible uses, e.g. health monitoring for clinical institutions, homes or prisons, alarm systems, fire evacuation, industrial or home automation, and triggering of medical ...
    • Communication-efficient and privacy-aware distributed LMS algorithm 

      Gogineni, Vinay Chakravarthi; Moradi, Ashkan; Kumar Dasanadoddi Venkategowda, Naveen; Werner, Stefan (Chapter, 2022)
      This paper presents a private-partial distributed least mean square (PP-DLMS) algorithm that offers energy efficiency while preserving privacy and is suitable for applications with limited resources and strict security ...
    • Communication-Efficient Online Federated Learning Framework for Nonlinear Regression 

      Gogineni, Vinay Chakravarthi; Werner, Stefan; Huang, Yih-Fang; Kuh, Anthony (Peer reviewed; Journal article, 2022)
      Federated learning (FL) literature typically assumes that each client has a fixed amount of data, which is unrealistic in many practical applications. Some recent works introduced a framework for online FL (Online-Fed) ...
    • Communication-Efficient Online Federated Learning Strategies for Kernel Regression 

      Gogineni, Vinay Chakravarthi; Werner, Stefan; Huang, Yih-Fang; Kuh, Anthony (Journal article; Peer reviewed, 2022)
    • 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 ...
    • Consensus-based Distributed Total Least-squares Estimation Using Parametric Semidefinite Programming 

      Gratton, Cristiano; Dasanadoddi Venkategowda, Naveen Kumar; Arablouei, Reza; Werner, Stefan (Chapter, 2019)
      We propose a new distributed algorithm to solve the total least-squares (TLS) problem when data are distributed over a multi-agent network. To develop the proposed algorithm, named distributed ADMM TLS (DA-TLS), we reformulate ...
    • Constrained Phase Noise Estimation in OFDM Using Scattered Pilots Without Decision Feedback 

      Mathecken, Pramod; Riihonen, Taneli; Werner, Stefan; Wichman, Risto (Journal article; Peer reviewed, 2017)
      In this paper, we consider an OFDM radio link corrupted by oscillator phase noise in the receiver, namely the problem of estimating and compensating for the impairment. To lessen the computational burden and delay incurred ...
    • Cooperative renewable energy management with distributed generation 

      Leithon, Johann; Werner, Stefan; Koivunen, Visa (Chapter, 2018)
      We propose an energy cost minimization strategy for cooperating households equipped with renewable energy generation and storage capabilities. The participating households minimize their collective energy expenditure by ...
    • Coordinated Data-Falsification Attacks in Consensus-based Distributed Kalman Filtering 

      Moradi, Ashkan; Dasanadoddi Venkategowda, Naveen Kumar; Werner, Stefan (Chapter; Peer reviewed, 2019)
      Abstract—This paper considers consensus-based distributed Kalman filtering subject to data-falsification attack, where Byzan- tine agents share manipulated data with their neighboring agents. The attack is assumed to be ...
    • Cost-Aware Dual Prediction Scheme for Reducing Transmissions at IoT Sensor Nodes 

      Håkansson, Victor Wattin; Dasanadoddi Venkategowda, Naveen Kumar; Kraemer, Frank Alexander; Werner, Stefan (Chapter, 2019)
      This paper develops a method for deciding when to update the prediction model or transmit a set of measurements from the sensor to the fusion centre (FC) to achieve minimal data transmission in a dual prediction scheme ...
    • Cost-aware renewable energy management: Centralized vs. distributed generation 

      Leithon, Johann; Werner, Stefan; Koivunen, Visa (Journal article; Peer reviewed, 2020)
      We propose optimization strategies for cooperating households equipped with renewable energy assets and storage devices. We consider two system configurations: In the first configuration, households share access to an ...
    • Data-Driven Personalized Cervical Cancer Risk Prediction: A Graph-Perspective 

      Gogineni, Vinay Chakravarthi; Langberg, Geir Severin Rakh Elvatun; Naumova, Valeriya; Nygård, Jan; Nygård, Marie; Grasmair, Markus; Werner, Stefan (Chapter, 2021)
      Routine cervical cancer screening at regular periodic intervals leads to either over-screening or too infrequent screening of patients. For this purpose, personalized screening intervals are desirable that account for ...
    • Decentralized PMU-Assisted Power System State Estimation With Reduced Interarea Communication 

      Kashyap, Neelabh; Werner, Stefan; Huang, Yih-Fang (Journal article; Peer reviewed, 2018)
      This paper presents a decentralized approach to multiarea power system state estimation using a combination of conventional measurement devices and newer phasor measurement units (PMU). We employ a reduced-order approach ...
    • 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 ...
    • Distributed Kalman filtering and control through embedded average consensus information fusion 

      Talebi, Sayed Pouria; Werner, Stefan (Journal article; Peer reviewed, 2019)
      This paper presents a unified framework for distributed filtering and control of state-space processes. To this end, a distributed Kalman filtering algorithm is developed via decomposition of the optimal centralized Kalman ...
    • Distributed Kalman filtering in presence of unknown outer network actuations 

      Talebi, Sayed Pouria; Werner, Stefan (Journal article; Peer reviewed, 2019)
      This letter presents a fully distributed approach for tracking state vector sequences over sensor networks in presence of unknown actuations. The problem arises in large-scale systems where modeling the full dynamics becomes ...
    • Distributed Kalman Filtering with Privacy against Honest-but-Curious Adversaries 

      Moradi, Ashkan; Dasanadoddi Venkategowda, Naveen Kumar; Talebi, Sayedpouria; Werner, Stefan (Chapter, 2021)
      This paper proposes a privacy-preserving distributed Kalman filter (PP-DKF) to protect the private information of individual network agents from being acquired by honest-but-curious (HBC) adversaries. The proposed approach ...
    • Distributed Kalman filtering: Consensus, diffusion, and mixed 

      Talebi, Sayed Pouria; Werner, Stefan (Chapter, 2018)
      A distributed Kalman filtering technique is developed for tracking state-space processes via sensor networks. Considering the optimal solution to multi-agent sequential filtering of linear Gaussian state-space processes, ...