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Engineering and Technology

D-Index
35
Citations
18584
World Ranking
8842
National Ranking
2452

Overview

Eric A. Wan is a researcher affiliated with Portland State University in the United States, contributing primarily within the fields of Engineering and Medicine. Their scholarly work encompasses specialties including Physical Therapy, Sports Therapy and Rehabilitation, Endocrinology, Diabetes and Metabolism, Electrical and Electronic Engineering, Ocean Engineering, and Biomedical Engineering.

Their research addresses topics such as Balance, Gait, and Falls Prevention, Diabetic Foot Ulcer Assessment and Management, Indoor and Outdoor Localization Technologies, Geophysical Methods and Applications, Microwave Imaging and Scattering Analysis, Ultrasonics and Acoustic Wave Propagation, and Cerebral Palsy and Movement Disorders.

Eric A. Wan's recent publications include:

  • Automated Detection of Real-World Falls: Modeled From People With Multiple Sclerosis (2020), IEEE Journal of Biomedical and Health Informatics
  • A pipeline for enhanced multimodal 2D imaging of concrete structures (2021), Materials and Structures
  • Comparing fall detection methods in people with multiple sclerosis: A prospective observational cohort study (2021), Multiple Sclerosis and Related Disorders
  • Design and Experiment of a Fertilization Rotation Speed Control System Based on Radar Speed Feedback (2025), Processes
  • Design and Experiment of a Multi-Row Spiral Quantitative Fertilizer Distributor (2025), Processes

They have collaborated frequently with coauthors including Clara Mosquera-Lopez, Jonathon Folsom, Andrea Hildebrand, Michelle Cameron, and Peter G. Jacobs.

Eric A. Wan's work appears across several publication venues, notably:

  • Processes
  • IEEE Journal of Biomedical and Health Informatics
  • Materials and Structures
  • Multiple Sclerosis and Related Disorders

Best Publications

  • The unscented Kalman filter for nonlinear estimation

    E.A. Wan;R. Van Der Merwe

  • The Unscented Particle Filter

    Rudolph van der Merwe;Arnaud Doucet;Nando de Freitas;Eric A. Wan

  • The square-root unscented Kalman filter for state and parameter-estimation

    R. Van der Merwe;E.A. Wan

  • The Unscented Kalman Filter

    Eric A. Wan;Rudolph van der Merwe

  • Sigma-point kalman filters for probabilistic inference in dynamic state-space models

    Rudolph Van Der Merwe;Eric A. Wan

  • Sigma-Point Kalman Filters for Nonlinear Estimation and Sensor-Fusion: Applications to Integrated Navigation

    Rudolph van der Merwe;Eric Wan;Simon Julier

  • Sigma-Point Kalman Filters for Nonlinear Estimation and Sensor Fusion: Applications to Integrated Navigation

    R van der Merwe;E Wan;SJ Julier

  • Neural network classification: a Bayesian interpretation

    E.A. Wan

  • RSSI-Based Indoor Localization and Tracking Using Sigma-Point Kalman Smoothers

    A.S. Paul;E.A. Wan

  • Dual Estimation and the Unscented Transformation

    Eric A. Wan;Rudolph van der Merwe;Alex T. Nelson

  • Dual Extended Kalman Filter Methods

    Eric A. Wan;Alex T. Nelson

  • Sigma-Point Kalman Filters for Integrated Navigation

    Rudolph van der Merwe;Eric A. Wan

  • Temporal backpropagation for FIR neural networks

    E.A. Wan

  • Gaussian mixture sigma-point particle filters for sequential probabilistic inference in dynamic state-space models

    R. van der Merwe;E. Wan

  • Efficient derivative-free Kalman filters for online learning.

    Rudolph van der Merwe;Eric A. Wan

  • Finite impulse response neural networks with applications in time series prediction

    Eric Andrew Wan

  • Dual Kalman Filtering Methods for Nonlinear Prediction, Smoothing and Estimation

    Eric A. Wan;Alex T. Nelson

  • Neural dual extended Kalman filtering: applications in speech enhancement and monaural blind signal separation

    E.A. Wan;A.T. Nelson

  • Navigation system applications of sigma-point Kalman filters for nonlinear estimation and sensor fusion

    Rudolph van der Merwe;Eric A. Wan;Simon J. Julier

  • Adjoint LMS: an efficient alternative to the filtered-x LMS and multiple error LMS algorithms

    E.A. Wan

  • Nonlinear estimation and modeling of noisy time series by dual kalman filtering methods

    Eric A. Wan;Alex Tremain Nelson

Frequent Co-Authors

Francoise Beaufays
Francoise Beaufays Google (United States)
Hynek Hermansky
Hynek Hermansky Johns Hopkins University
Simon Julier
Simon Julier University College London
Bernard Widrow
Bernard Widrow Stanford University
James McNames
James McNames Portland State University
Arnaud Doucet
Arnaud Doucet University of Oxford
Nando de Freitas
Nando de Freitas DeepMind (United Kingdom)
Jeffrey Kaye
Jeffrey Kaye Oregon Health & Science University
Ah Chung Tsoi
Ah Chung Tsoi University of Wollongong
Giovanni Pellacani
Giovanni Pellacani Sapienza University of Rome

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