ET S Time–Frequency Analysis

he wavelet transform has emerged over recent years as a powerful time–frequency analysis and signal-coding tool suitable for use in the manipulation of complex nonstationary signals. It has been at the forefront of many recent developments in biomedical and biological signal processing, where it has been particularly useful in the study of numerous problematic signals. This overview article covers the emerging role of the wavelet transform in detail, where both continuous and discrete transforms are considered in turn, promoting newmethods that may prove useful for further research in this area. As a result of infinite extent of Fourier integral, analysis is time averaged. Thus, it contains only globally averaged infor-mation and so has the potential to obscure transient or loca-tion-specific features within the signal. This limitation can b