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- Sonjoy Das, Roger G. Ghanem, James C. Spall
- SIAM J. Scientific Computing
- 2008

- Sonjoy Das, James C. Spall, Roger G. Ghanem
- CDC
- 2007

The Fisher information matrix (FIM) is a critical quantity in several aspects of system identification, including input selection and confidence region calculation. Analytical determination of the FIM in a general system identification setting may be difficult or almost impossible due to intractable modeling requirements and/or high-dimensional integration.… (More)

- Sonjoy Das, Roger G. Ghanem, Steven Finette
- J. Comput. Physics
- 2009

- Sonjoy Das, Roger G. Ghanem
- Multiscale Modeling & Simulation
- 2009

A maximum entropy (MaxEnt) based probabilistic approach is developed to model mechanical systems characterized by symmetric positive-definite matrices bounded from below and above. These matrices are typically encountered in the constitutive modeling of heterogeneous materials, where the bounds are deduced by employing the principles of minimum… (More)

- Sonjoy Das, James C. Spall, Roger G. Ghanem
- Computational Statistics & Data Analysis
- 2007

The Fisher information matrix (FIM) is a critical quantity in several aspects of mathematical modeling, including input selection, model selection, and confidence region calculation. For example, the determinant of the FIM is the main performance metric for choosing input values in a scientific experiment with the aims of achieving the most accurate… (More)

- Sonjoy Das
- 2007

The Fisher information matrix (FIM) is a critical quantity in several aspects of mathematical modeling, including input selection and confidence region calculation. Analytical determination of the FIM in a general setting, specially in nonlinear models, may be difficult or almost impossible due to intractable modeling requirements and/or intractable… (More)

- Sonjoy Das
- 2008

xi 1 Chapter 1: Introduction 1 1.1 Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2 Notation and Terminology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2 Chapter 2: Asymptotic Distribution for Polynomial Chaos Representation from Data 5 2.1 Motivation and Problem Description . . . .… (More)

In this paper, we formulate the manipulator Jacobian matrix in a probabilistic framework based on the random matrix theory (RMT). Due to the limited available information on the system fluctuations, the parametric approaches often prove to be inadequate to appropriately characterize the uncertainty. To overcome this difficulty, we develop two RMTbased… (More)

- Javad Sovizi, Aliakbar Alamdari, Sonjoy Das, Venkat N. Krovi
- 2014 IEEE International Conference on Robotics…
- 2014

In this paper, we generalize our random matrix based (RM-based) uncertainty model for manipulator Jacobian matrix to the dynamic model of the robotic systems. Conventional random variable based (RV-based) schemes require a detailed knowledge of the system parameters variation and may be not able to fully characterize the uncertainties of the complex dynamic… (More)

- Javad Sovizi, Sonjoy Das, Venkat N. Krovi
- ArXiv
- 2017

Characterization of the uncertainty in robotic manipulators is the focus of this paper. Based on the random matrix theory (RMT), we propose uncertainty characterization schemes in which the uncertainty is modeled at the macro (system) level. This is different from the traditional approaches that model the uncertainty in the parametric space of micro (state)… (More)