Alipour, Hadi and Ayat, Saeed (2021) Suggesting a New Approach on Identifying Degree of Separability in Signal Detection, for Using in Channel Estimation. In: Recent Advances in Mathematical Research and Computer Science Vol. 5. B P International, pp. 126-131. ISBN 978-93-5547-325-7
Full text not available from this repository.Abstract
Signal Detection Noise removal, is a very important issue in channel estimation, and increasing performance of signal transformation in cognitive networks. Therefore it is necessary to have a criterion for evaluating the degree of correctness and reliability of the signals. Nowadays neural networks has very important role in calculations and if it combined with statistical methods they will produce perfect results in separability detection. In this paper, we used the separability degree as a criterion for separating and identifying noise from the main signal. We use statistical Hypotheses and declare some statistical thresholds for signal validity to get the signal more suitable by increasing noise detection quality. This method supposes two states for our signal that are false detection of weak signal, and correct detection of the main signal. All these will be done by statistical_neural methods.
Item Type: | Book Section |
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Subjects: | STM Academic > Mathematical Science |
Depositing User: | Unnamed user with email support@stmacademic.com |
Date Deposited: | 16 Oct 2023 04:14 |
Last Modified: | 16 Oct 2023 04:14 |
URI: | http://article.researchpromo.com/id/eprint/1466 |