Sunil L. Kukreja

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Representation and identification of a parallel pathway description of ankle dynamics as a model of the nonlinear autoregressive, moving average exogenous (NARMAX) class is considered. A nonlinear difference equation describing this ankle model is derived theoretically and shown to be of the NARMAX form. Identification methods for NARMAX models are applied(More)
— In many applications of system identification, output measurements are available, but measurements of the input are not available. In these cases, sensor-only identification techniques are needed. In the present paper, we define a discrete-time MIMO pseudo transfer function (PTF) between sensor measurements in a sampled-data system with multiple(More)
Model refinement is directly applicable to health monitoring, where the goal is to determine changes in a system that may reflect damage. As data become available, an initial model for the undamaged system is updated; the updated model is then compared with the original model, and changes in the model are analyzed to deduce potential damage. We propose that(More)
— Motivated by passive health monitoring applications , we consider identification where only sensor measurements are available. The goal is to exploit unknown ambient disturbances and thus avoid the need for controlled actuation. To achieve this, we identify a pseudo transfer function (PTF) between sensor measurements. For the single-input case, one sensor(More)
Basis pursuit denoising is a new approach for data-driven estimation of parametric images from dynamic positron emission tomography (PET) data. At present, this kinetic modeling technique does not allow for the estimation of the errors on the parameters. These estimates are useful when performing subsequent statistical analysis, such as, inference across a(More)
A "Multimode" or "switched" system is one that switches between various modes of operation. When a switch occurs from one mode to another, a discontinuity may result followed by a smooth evolution under the new regime. Characterizing the switching behavior of these systems is not well understood and, therefore, identification of multimode systems typically(More)
— We consider the problem of data-based model refinement, where we assume the availability of an initial model, which may incorporate both physical laws and empirical observations. With this initial model as a starting point, our goal is to use additional measurements to refine the model. In particular, components of the model that are poorly modeled can be(More)
Data-based model refinement improves the fidelity of a model based on empirical observations. The model refinement structure is a closed-loop system consisting of an initial model, which is assumed to be known, and a feedback correction, which is unknown. We take advantage of the similarity between the feedback structure of model refinement and adaptive(More)
BACKGROUND Traumatic injuries to the thoracolumbar spine result in a high incidence of unstable fractures. The goal of the surgical management is to achieve an adequate decompression and stabilization. We have analyzed operative and postoperative features of anterior surgical approaches. METHODS We retrospectively analyzed the medical records of 45(More)