| Summary: | Frequency estimation is used everywhere as it is one of the main issues in the field of signal
processing and communications. It is an important topic because various fields in the world
use this. Currently, many researchers are using traditional methods in finding the frequency
estimation of a signal, which can still give accurate and reliable results.
In recent years, deep learning has gained recognition and people are starting to incorporate
deep learning into their research as it is known to have a higher accuracy and speed. It also can
process large amount of data which makes it very powerful when dealing with unstructured
data.
This project aims to understand the various methods that have been used to estimate the
frequency of signals, followed by the study of deep learning algorithms available. The main
objective of this project is to incorporate deep learning into finding the frequency estimation
of a noisy signal. This is done by studying the behaviour of DNN which displays the
phenomenon of F-principle, where it captures the low frequency first then the high frequency.
This algorithm is then tested on noisy signal to estimate the frequency of the signal.
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