ITM Web Conf.
Volume 30, 201929th International Crimean Conference “Microwave & Telecommunication Technology” (CriMiCo’2019)
|Number of page(s)||6|
|Section||Information Technology in Telecommunications (3a)|
|Published online||27 November 2019|
Blind signal deconvolution based on pulsed neuron model
Sevastopol State University, 299053 Sevastopol, Russian Federation
* Corresponding author: email@example.com
In this paper, we consider the vector-matrix model of a pulsed neuron, focused on solving problems of digital signal processing. We extend the application domain of the model to the blind signal deconvolution problem. To achieve this goal we propose an unsupervised learning algorithm, which maximizes the absolute value of the normalized kurtosis of the output signal of the deconvolution filter using vector-matrix model of a pulsed neuron. To show the validity of the proposed learning algorithm, some examples of deconvolution of speech signals distorted by reverberation are presented.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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