SPML Software Download Centre
Software Download Centre of Medical Signal Processing and Machine Learning Group

A hearty welcome to the software Download Centre of SPML working group, Indian Institute of Technology Kharagpur, INDIA.

These packages are developed by SPML members. You can freely use, modify and redistribute it for academic use under GNU General Public License.

If you feel these packages useful, you may cite the respective paper(s) and/or this software corner.

Thank you.

SPML Research Team

Characterization of S1 and S2 Heart Sounds Using Stacked Autoencoder and Convolutional Neural Network

This framework is implemented on MATLAB and PYTHON platforms.

The introductory video is available here.

These audio files of recorded heart sound are used in this study. One can find the complete source code available here.


MAPK Pathway

This algorithm is implemented on MATLAB platform. Download MAPK Pathway Toolbox.


S-system of Synthetic Anaerobic Fermentation Pathway

This algorithm is implemented on MATLAB platform. Download Anaerobic Fermentation Pathway Toolbox.

Reference:

Surajit Panja, Sourav Patra and Anirban Mukherjee; Tweaking Metabolic Networks: A Design Method, INAE Letters, Springer, pp. 1-6, DOI 10.1007/s41403-016-0005-5, 2016.


Model Shift-based Monte Carlo Expectation-Maximization (MSMCEM) Algorithm for Motif Finding in DNA Sequence

This algorithm is implemented on MATLAB platform. Download MSMCEM Toolbox.

Reference:

Aniruddha Maiti and Anirban Mukherjee; On the Monte-Carlo Expectation Maximization for Finding Motifs in DNA Sequences, IEEE Journal of Biomedical and Health Informatics, vol. 19, no. 2, pp. 677-686, 2015.


Vector-Valued Regularized Kernel Function Approximation

This algorithm is implemented on MATLAB platform. Download VVRKFA Toolbox.

Reference:

Santanu Ghorai, Anirban Mukherjee and Pranab K. Dutta; Discriminant Analysis for Fast Multiclass Data Classification through Regularized Kernel Function Approximation, IEEE Trans. Neural Networks, vol. 21, no. 6, pp. 1020-1029, 2010.


Non Parallel-plane Proximal Classifier (NPPC)

This NPPC with unity norm constraint algorithm is implemented on MATLAB platform. Download NPPC (with unity norm constraint) Toolbox.

Reference:

Santanu Ghorai, Shaikh Jahangir Hossain, Anirban Mukherjee, and Pranab K. Dutta; Newton's Method for Nonparallel Plane Proximal Classifier with Unity Norm Hyperplanes, Signal Processing, vol. 90, no. 1, pp. 93-104, 2010.