Abstract
In recent years, wavelet analysis has become an effective and important computational tool in signal processing and image processing applications. Wavelet analysis is known for its successful approach to solving the problem of signal analysis in both the time domain and frequency domain. The analysis of the nonstationary signal generated by physical phenomena has posed a great challenge for various conversion techniques. Transformation techniques such as Fourier transform (FT) and short Fourier transform (STFT) fail to analyze nonstationary signals. But wavelet transform (WT) techniques may be able to efficiently analyze both stable and unstable signals. WT is able to analyze one-dimensional signals, such as audio signals and two-dimensional signals such as images. In this chapter, we discuss wavelet transduction techniques and their applications in detail and focus on the analysis and processing of the wave-encoded laser signal as one-dimensional electrical signals and its use in alarm systems. In the second stage, we filter the speech signal and determine the fundamental frequencies using wavelet transformation.
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