The Channel Identification Machines (CIMs) Toolbox provides a set of algorithms for the functional identification of a channel in a system consisting of a communication channel in cascade with an asynchronous sampler, as well as step-by-step demonstrations of the accompanying source code. The channel considered here is modeled as a multidimensional filter, while models of asynchronous sampler are taken from neuroscience and communications and includes integrate-and-fire (IAF) neurons, asynchronous delta-sigma modulators (ASDM), and general oscillators in cascade with zero-crossing detectors.
Future releases of this package may be obtained from the Bionet Group's online code repository1.
This software in this toolbox was written and developed by the following alumni of the Bionet Group2 at Electrical Engineering Department of Columbia University under the supervision of Prof. Aurel A. Lazar:
The software in this toolbox was revised and packaged by
This software is licensed under the BSD License. See the included LICENSE file for more information.
Please direct all questions and comments pertaining to this toolbox to this email.
The algorithms implemented in this toolbox are described in the papers listed in the attached BibTeX bibliography. Further research on channel identification and neural circuitry may be obtained from the Bionet Group publication server3.