Sanmitra Ghosh : Publications

Drift removal in plant electrical signals via IIR filtering using wavelet energy

Saptarshi Das‚ Barry Juans Ajiwibawa‚ Shre Kumar Chatterjee‚ Sanmitra Ghosh‚ Koushik Maharatna‚ Srinandan Dasmahapatra‚ Andrea Vitaletti‚ Elisa Masi and Stefano Mancuso

In Computers and Electronics in Agriculture. Vol. 118. Pages 15 − 23. October, 2015.

Details about Drift removal in plant electrical signals via IIR filtering using wavelet energy | BibTeX data for Drift removal in plant electrical signals via IIR filtering using wavelet energy | DOI (10.1016/j.compag.2015.08.013)

Fast approximate Bayesian computation for estimating parameters in differential equations

Sanmitra Ghosh‚ Srinandan Dasmahapatra and Koushik Maharatna

In Statistics and Computing. Vol. 27. No. 1. Pages 19–38. January, 2017.

Details about Fast approximate Bayesian computation for estimating parameters in differential equations | BibTeX data for Fast approximate Bayesian computation for estimating parameters in differential equations | DOI (10.1007/s11222-016-9643-4)

Fast approximate Bayesian computation for inference in non−linear differential equations

Sanmitra Ghosh

PhD Thesis University of Southampton. 2016.

Details about Fast approximate Bayesian computation for inference in non−linear differential equations | BibTeX data for Fast approximate Bayesian computation for inference in non−linear differential equations | Link to Fast approximate Bayesian computation for inference in non−linear differential equations

Forward and inverse modelling approaches for prediction of light stimulus from electrophysiological response in plants

Shre Kumar Chatterjee‚ Sanmitra Ghosh‚ Saptarshi Das‚ Veronica Manzella‚ Andrea Vitaletti‚ Elisa Masi‚ Luisa Santopolo‚ Stefano Mancuso and Koushik Maharatna

In Measurement. Vol. 53. Pages 101 − 116. July, 2014.

Details about Forward and inverse modelling approaches for prediction of light stimulus from electrophysiological response in plants | BibTeX data for Forward and inverse modelling approaches for prediction of light stimulus from electrophysiological response in plants | DOI (10.1016/j.measurement.2014.03.040)