9 citations · 14 across the 5 of their papers we have counts for
6 papers
An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation
San Kim, Won Chang, Daniel B. Forger +1
Filtering combines model predictions with measurements to estimate the probability density function (PDF) of a system state over time. The PDF often becomes highly asymmetric and e…
A Level Set Kalman Filter Approach to Estimate the Circadian Phase and its Uncertainty from Wearable Data
Dae Wook Kim, Minki P. Lee, Daniel B. Forger
The circadian clock is an internal timer that coordinates the daily rhythms of behavior and physiology, including sleep and hormone secretion. Accurately tracking the state of the…
The asymmetric particle population density method for simulation of coupled noisy oscillators
Ningyuan Wang, Daniel B Forger
A wide variety of biological phenomena can be modeled by the collective activity of a population of individual units. A common strategy for simulating such a system, the population…
The Level Set Kalman Filter for State Estimation of Continuous-discrete Systems
Ningyuan Wang, Daniel B. Forger
We propose a new extension of Kalman filtering for continuous-discrete systems with nonlinear state-space models that we name as the level set Kalman filter (LSKF). The LSKF assume…
Seasonality and Light Phase-Resetting in the Mammalian Circadian Rhythm
Kevin M. Hannay, Daniel B. Forger, Victoria Booth
We study the impact of light on the mammalian circadian system using the theory of phase response curves. Using a recently developed ansatz we derive a low-dimensional macroscopic…
Macroscopic Models for Networks of Coupled Biological Oscillators
Kevin M. Hannay, Daniel B. Forger, Victoria Booth
The study of synchronization in populations of coupled biological oscillators is fundamental to many areas of biology to include neuroscience, cardiac dynamics and circadian rhythm…