Matched Filters for Better Signal-to-Noise Ratio: A Python and Learning-Based Study

Latha H N , Akhil Karthik , Niharika N

- Signal to Noise Ratio (SNR). Matched filter, signal-to-noise ratio, denoising, PyTorch, convolutional neural network, signal detection.

Matched filters are very commonly implemented at the receiver for improved SNR and better reconstruction of the signal. Matched filters are electronic circuits used in signal processing for filtering out other frequencies. The paper consolidates recent literature on matched filters in radar, sonar, communications, speaker recognition and adaptive denoising. Results show that the matched filter remains a strong baseline for signal detection; whereas the learning-assisted model can improve reconstruction fidelity when sufficient training data are, available. The main advantage of a matched filter is that the output generated by the filter resembles the signal energy in the absence of noise. These characteristics help in maintaining the axial resolution and detecting signal. PyTorch is pythonic in nature, which means it follows the coding style that uses Python's unique features to write readable code. Python is also popular for its use of dynamic computation graphs. It enables developers, scientists, and neural network debuggers to run and test a portion of code in real time instead of waiting for the entire program to be written.

Published Paper   E-Certificate

"Matched Filters for Better Signal-to-Noise Ratio: A Python and Learning-Based Study", JETNR - JOURNAL OF EMERGING TRENDS AND NOVEL RESEARCH (www.JETNR.org), ISSN:2984-9276, Vol.4, Issue 6, page no.b857-b866, June-2026, Available :https://rjpn.org/JETNR/papers/JETNR2606213.pdf

Volume 4 Issue 6, June-2026

Pages : b857-b866

Paper Reg. ID: JETNR_235230

Published Paper Id: JETNR2606213

Downloads: 00051

Research Area: Science and Technology

Country: Bangalore, karnataka, India

Published Paper PDF: https://rjpn.org/JETNR/papers/JETNR2606213

Published Paper URL: https://rjpn.org/JETNR/viewpaperforall?paper=JETNR2606213

ISSN: 2984-9276 | IMPACT FACTOR: 9.87 Calculated By Google Scholar | ESTD YEAR: 2023

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.87 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: RJPN (IJPublication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition