Publications by Pamandeep Singh Gujral

On multivariate calibration with unlabeled data

Michael Amrhein, Dominique Bonvin, Pamandeep Singh Gujral

In principal component regression (PCR) and partial least-squares regression (PLSR), the use of unlabeled data, in addition to labeled data, helps stabilize the latent subspaces in the calibration step, typically leading to a lower prediction error. A non- ...

Wiley-Blackwell2011

Subspace Correction Methods in Multivariate Calibration

Pamandeep Singh Gujral

Productivity, quality, safety, and environmental concerns have driven major advancements in the development of process analyzers. Analyzers generate measurement data that are useful for characterizing product and process attributes (key variables), thereby ...

EPFL2011

Framework for explicit drift correction in multivariate calibration models

Michael Amrhein, Dominique Bonvin, Pamandeep Singh Gujral

Latent-variable calibrations using principal component regression and partial least-squares regression are often compromised by drift such as systematic disturbances and offsets. This paper presents a two-step framework that facilitates the evaluation and ...

2010

Drift Correction in Multivariate Calibration Models Using On-line Reference Measurements

Michael Amrhein, Dominique Bonvin, Pamandeep Singh Gujral

On-line measurements from first-order instruments such as spectrometers may be compromised by instrumental, process and operational drifts that are not seen during off-line calibration. This can render the calibration model unsuitable for prediction of key ...

2009

Classification of magnetic resonance images from rabbit renal perfusion

Michael Amrhein, Dominique Bonvin, Pamandeep Singh Gujral

The feasibility of using chemometric techniques for the automatic detection of whether a rabbit kidney is pathological or not is studied. Sequential images of the kidney are acquired using Dynamic Contrast-Enhanced Magnetic Resonance Imaging with contrast ...

2009

Partial least-squares regression with unlabeled data

Michael Amrhein, Dominique Bonvin, Pamandeep Singh Gujral

It is well known that the prediction errors from principal component regression (PCR) and partial least-squares regression (PLSR) can be reduced by using both labeled and unlabeled data for stabilizing the latent subspaces in the calibration step. An appro ...

2009

Measurement-Based Drift Correction in Spectroscopic Calibration Models

Michael Amrhein, Dominique Bonvin, Pamandeep Singh Gujral

Correct prediction of analyte concentrations from a new spectrum without drift is possible provided the spectrum lies in the row space spanned by the calibration spectra (space-inclusion condition). However, this condition may be violated as on-line spectr ...

cemagref Languedoc Roussillon2008

On-Line Recalibration of Spectral Measurements Using Metabolite Injections and Dynamic Orthogonal Projection

Michael Amrhein, Urs von Stockar, Michal Dabros, Pamandeep Singh Gujral

Spectrometers are enjoying increasing popularity in bioprocess monitoring due to their non-invasiveness and in-situ sterilizability. Their on-line applicability and high measurement frequency create an interesting opportunity for process control and optimi ...

2007