Search Results for author: Shankar Narasimhan

Found 6 papers, 2 papers with code

Identification of Errors-in-Variables ARX Models Using Modified Dynamic Iterative PCA

no code implementations30 Nov 2020 Deepak Maurya, Arun K. Tangirala, Shankar Narasimhan

We propose a novel identification algorithm based on a modified Dynamic Iterative Principal Components Analysis (DIPCA) approach for identifying the EIV-ARX model for single-input, single-output (SISO) systems where the output measurements are corrupted with coloured noise consistent with the ARX model.

Identification of MISO systems in Minimal Realization Form

1 code implementation12 Aug 2020 Chaithanya K. Donda, Deepak Maurya, Arun K. Tangirala, Shankar Narasimhan

In this work, we deal with the challenging problem of identifying order, delay in each input of minimal realization form separately while estimating the transfer functions.

Systems and Control Systems and Control

ARX Model Identification using Generalized Spectral Decomposition

3 code implementations11 Aug 2020 Deepak Maurya, Arun K. Tangirala, Shankar Narasimhan

This article is concerned with the identification of autoregressive with exogenous inputs (ARX) models.

Systems and Control Systems and Control

Learning Conserved Networks from Flows

no code implementations21 May 2019 Satya Jayadev P., Shankar Narasimhan, Nirav Bhatt

A challenging problem in complex networks is the network reconstruction problem from data.

Network Topology Identification using PCA and its Graph Theoretic Interpretations

no code implementations1 Jun 2015 Aravind Rajeswaran, Shankar Narasimhan

We show that identification is equivalent to learning a model $\mathbf{A_n}$ which captures the approximate linear relationships between the different variables comprising $\mathbf{X}$ (i. e. of the form $\mathbf{A_n X \approx 0}$) such that $\mathbf{A_n}$ is full rank (highest possible) and consistent with a network node-edge incidence structure.

Deconstructing Principal Component Analysis Using a Data Reconciliation Perspective

no code implementations2 May 2015 Shankar Narasimhan, Nirav Bhatt

Data reconciliation (DR) and Principal Component Analysis (PCA) are two popular data analysis techniques in process industries.


Cannot find the paper you are looking for? You can Submit a new open access paper.