| Peter Stepien | Web Site |
The following software has been written by myself. Please do not distribute modified versions of this software. Instead, notify me of any problems so that they can be included in future releases. You may distribute unmodified versions of this software for research and non-profit use.
The following software is available:
All comments and suggestions are most welcome.
The Independent Component Analysis (ICA) program called ica provides source separation for a number or mixed signals where the number of recordings is equal to the number of the sources. A good description of the ICA algorithm used can be found in Anthony J. Bell and Terrence J. Sejnowski, ``An information-maximisation approach to blind separation and blind deconvolution'', Neural Computation, 7(6):1129-1159, 1995. The non-linearity used to perform the separation is based on either the exp() or tanh() function.
Input to the program can come from one of four different file formats. These include 16 bit integers, 32 bit floating point numbers, 64 bit floating point numbers and the European Data Format (EDF). In the case of the integer and the floating point numbers, these are stored such that the all the values from a particular point in time are stored together. The input data does not have to be zero meaned before being used by this program. The original unmixing matrix can also be set otherwise a unity matrix is used.
The output from the program is optionally the unmixed input stored in a file as either 16 bit integers, 32 bit floating point numbers or 64 bit floating point numbers. The resultant unmixing matrix can also be saved to a file.
The progress of the program is displayed for each loop through the data. After the input data has been processed and the unmixed version saved to a file, the RMS value of the covariance matrix for the unmixed and the mixed signals will be calculated. This is just to give a rough indication on how well the data has been separated. Note that the input data does not get sphered. The displaying of the RMS covariance is optional and is reliant on the unmixed output being saved to a file.
The ica program was written for Unix based systems. The source is available as a tar archive which has been compressed with gzip can be downloaded:
Instructions for building and using the program are contained with the program source.
The Teaching Resource System has been developed to provide a convenient way of generating various teaching resources. The methodology behind the system is that a single source file can be used to generate different resources. For example, lecture notes, lecture slides and lecture slide notes all come from a single source file. This system can also be used for other applications and incidentally has been used to generate what you are currently reading.
A paper on the system has been written and presented at ICECE'2007 in Brazil. To show the utility of the system, it was used to generate the slides for the presentation. More information can be found on a separate web site:
More information regarding this system and also the code used to generate it will be made available here in the future. I have actually said this for a while now, but have not got back to it. My apologies to the people who have expressed interest in this system. Note also that the links on the example TRS1000 web site are now out of date.
| Peter Stepien WebSite 2009-07-12 23:41:30 pstepien |
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