Wavelet theory is applicable to several subjects. All wavelet transforms may be considered forms of time-frequency representation for continuous-time (analog) signals and so are related to harmonic analysis. Almost all practically useful discrete wavelet transforms use discrete-time filterbanks. These filter banks are called the wavelet and scaling coefficients in wavelets nomenclature. These filterbanks may contain either finite impulse response (FIR) or infinite impulse response (IIR) filters. The wavelets forming a continuous wavelet transform (CWT) are subject to the uncertainty principle of Fourier analysis respective sampling theory: Given a signal with some event in it, one cannot assign simultaneously an exact time and frequency response scale to that event. The product of the uncertainties of time and frequency response scale has a lower bound. Thus, in the scaleogram of a continuous wavelet transform of this signal, such an event marks an entire region in the time-scale plane, instead of just one point. Also, discrete wavelet bases may be considered in the context of other forms of the uncertainty principle.
本帖隐藏的内容
汇总
Introduction to Wavelets Based on 10 Papers.zip
大小:(6.21 MB)
马上下载
本附件包括：
- 10 From_Fourier_to_wavelet_analysis_of_time_series.pdf
- 1 Logarithmic Fourier transformation.pdf
- 2 Wavelet Introductions.pdf
- 3 WAVELETS FOR KIDS(Introductions).pdf
- 4 AN_INTRODUCTION_TO_WAVELETS.pdf
- 5 Wavelets Introduction.pdf
- 6 Wavelets_from_the_Loop_Scheme.pdf
- 7 Wavelets An introduction.pdf
- 8 Wavelets An Introduction.pdf
- 9 Wavelets The introduction.pdf
扫码加好友，拉您进群
全部版块
我的主页
收藏
