This repository contains code to apply the ESPER method to quasi-continuum models of biomolecules exhibiting multiple degrees of freedom, as described in Seitz et al. (2022, IEEE TCI). As inputs into ESPER, detailed instructions are also provided for generating custom synthetic datasets with increasing complexity to mirror known cryo-EM image attributes.

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7200 .csv files, each containing a 10 kHz recording of a 1 ms lasting 100 hz sound, recorded centimeterwise in a 20 cm x 60 cm locating range on a table. 3600 files (3 at each of the 1200 different positions) are without an obstacle between the loudspeaker and the microphone, 3600 RIR recordings are affected by the changes of the object (a book). The OOLA is initially trained offline in batch mode by the first instance of the RIR recordings without the book. Then it learns online in an incremental mode how the RIR changes by the book.

Instructions: 

folder 'load and preprocess offline data': matlab sourcecodes and raw/working offline (no additional obstacle) data files

folder 'lvq and kmeans test': matlab sourcecodes to test and compare in-sample failure with and without LVQ

folder 'online data load and preprocess': matlab sourcecodes and raw/working online (additional obstacle) data files

folder 'OOL': matlab sourcecodes configurable for case 1-4

folder 'OOL2': matlab sourcecodes for case 5

folder 'plots': plots and simulations

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