Neural Network Optimization for Classification Signals with Linear Frequency Modulation

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG43__%2F26%3A00564730" target="_blank" >RIV/60162694:G43__/26:00564730 - isvavai.cz</a>

Result on the web

<a href="http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=11061248" target="_blank" >http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=11061248</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICMT65201.2025.11060897" target="_blank" >10.1109/ICMT65201.2025.11060897</a>

Result language

angličtina

Original language name

Neural Network Optimization for Classification Signals with Linear Frequency Modulation

Original language description

This paper presents the design, implementation and training of a signal classifier based on Wigner-Ville spectral analysis using an artificial neural network composed of fully connected layers. The classifier is developed to discriminate between linear frequency modulation and carrier signals under different signal-to-noise ratio conditions. Deterministic linear frequency modulation signals are generated with random frequency ranges and durations, combined with noise, and analyzed using the Wigner-Ville transform to extract signal features from the spectrogram. The neural network architecture is optimized using multiple fully connected layers, regularization of the outage and normalization of the z-score. The system achieves a high signal classification rate in a challenging noise environment, demonstrating the effectiveness of the proposed method for time-frequency signal analysis.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

20200 - Electrical engineering, Electronic engineering, Information engineering

Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

2025 10th International Conference on Military Technologies, ICMT 2025 - Proceedings

ISBN

979-8-3315-2338-1

ISSN

—

e-ISSN

—

Number of pages

5

Pages from-to

24-28

Publisher name

Institute of Electrical and Electronics Engineers Inc.

Place of publication

Brno

Event location

Brno, Czech Republic

Event date

May 27, 2025

Type of event by nationality

EUR - Evropská akce

UT code for WoS article

001545807300001