An Efficient Adaptive Window Size Selection Method for Improving Spectrogram Visualization

Abstract

Short Time Fourier Transform (STFT) is an important technique for the time-frequency analysis of a time varying signal. The basic approach behind it involves the application of a Fast Fourier Transform (FFT) to a signal multiplied with an appropriate window function with fixed resolution. The selection of an appropriate window size is difficult when no background information about the input signal is known. In this paper, a novel empirical model is proposed that adaptively adjusts the window size for a narrow band-signal using spectrum sensing technique. For wide-band signals, where a fixed time-frequency resolution is undesirable, the approach adapts the constant Q transform (CQT). Unlike the STFT, the CQT provides a varying time-frequency resolution. This results in a high spectral resolution at low frequencies and high temporal resolution at high frequencies. In this paper, a simple but effective switching framework is provided between both STFT and CQT. The proposed method also allows for the dynamic construction of a filter bank according to user-defined parameters. This helps in reducing redundant entries in the filter bank. Results obtained from the proposed method not only improve the spectrogram visualization but also reduce the computation cost and achieves 87.71% of the appropriate window length selection.

The Free-Swimming Device Leakage Detection in Plastic Water-filled Pipes through Tuning the Wavelet Transform to the Underwater Acoustic Signals

“…In the first step, it is manifested that the frequency band, wherever the acoustic signal has strong components, correlated to relative interfering comprised noise and signals. Consequently, STFT is tuned (window size) [40][41][42][43][44] to non-stationary underwater signals and revealed that the presence of leakage acoustic signal is analogously strong in short-time windows related to other unwanted events (see Figure 4). However, due to an enormous number of mother wavelets availability with different localization properties and scales, it provokes to tune the WT to underwater acoustic signals regarding the nature of events.…”

Clutter noise reduction in B-Mode image through mapping and clustering signal energy for better cyst classification

“…The first step in identifying the location of a cyst and eliminating the clutter inside it starts with calculating the energy of the envelope signal for each of the image lines using the windowing technique [6]. Mapping the envelope signal into energy through the windowing process helps to classify and differentiate from the speckle destructive region and the clutter inside the cyst.…”

Use of Time-Dependent Multispectral Representation of Magnetic Barkhausen Noise Signals for the Needs of Non-Destructive Evaluation of Steel Materials

“…It must be noticed that there is a strict relationship between the representations resolutions in time and frequency domains. If the time period Δ T is increasing, the frequency resolution Δ F is simultaneously decreasing [49,50]. The best resolution is maintained when Δ F = 1/Δ T .…”