Fourier transform methods face constraints in assessing non-stationary signals as they offer comprehensive information about frequency ways but do not include partiality about when those frequency ways occur. This can lead to failure in disclosing evolving spectral characteristics or transient incidents. The time-frequency tools like Short-Time Fourier Transform (STFT) and Wavelet analysis are present to mitigate these hurdles. These T-F tools assist in following frequencies that displace through time and present personalized information on the topic of frequency ways for effective modifications with time. In this way, these tools offer comprehensive and adjusted insights into the non-stationary signals. Moreover, they conserve the advantages of Fourier-based spectral depiction as they allow various types of signal investigations. This essay focuses on the significant descriptions of the STFT and the Wavelet methods with potential advantages and utilization in signal processing. It also emphasizes how these individually tailored ways improve the assessment of non-stationary signals.