Webinar on Time-Frequency Analysis
Webinar Title: Time-Frequency Analysis
Registration Fee: - Rs. 1200.
Expert Speaker: - Prof. Ram Bilas Pachori
Webinar Date: 01st November, 2020 Time: 06 PM-09 PM (IST)
About Webinar: -
In real life, signals can be classified as stationary and non-stationary signals. The frequency-domain based methods for signal analysis are suitable for stationary signals. In order to have meaningful analysis of non-stationary signals, time-frequency analysis based methods have been proposed in the literature. Such methods include techniques like short-time Fourier transform (STFT), wavelet transform, Wigner-Ville distribution, Hilbert-Huang transform (HHT), Fourier-Bessel series expansion based empirical wavelet transform (FBSE-EWT), etc. In this webinar, the fundamentals related to time-frequency analysis will be provided. The working principles of various time-frequency analysis techniques will be explained. The various applications of these time-frequency analysis techniques in the areas of biomedical signal processing, speech signal processing, and communication will be provided. The webinar will also discuss about the implementation of these time-frequency techniques in MATLAB.
NIT Warangal | STC on Data Visualization for Deep Learning Using Power BI and Tableau, Apply Now!
NIT Warangal | STC on Advanced Python Programming, Apply Now!
NIT Warangal | STC on Artificial Intelligence Machine Learning and Deep Learning, Apply Now!
NIT Warangal - Organizing an Online Continuing Education Program on “Artificial Intelligence and Machine Learning Applications in Engineering”, Apply by 15 February 2023.
RELIANCE FOUNDATION - Invitation for Reliance Foundation Undergraduate Scholarships 2022-23, Apply by 14ᵗʰ, 2023!
NIT SURATHKAL - Recruitment of JRF in Mech. Eng Dept. , Apply by Feb 15ᵗʰ, 2023!
NIT Warangal - Organizing A Five-Day Short-Term Training Program on Data Science for All with R (Online Mode), Apply by February 18th, 2023.
UpGrad's Full Stack Developer Course (PGD IIITB) Review: Pros and Cons
Edureka's Data Science and Machine Learning Program: A Comprehensive Review