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ECE 501 Introduction to BME ECE 501 Dr. Hang
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Part V Biomedical Signal Processing Introduction to Wavelet Transform ECE 501 Dr. Hang
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ECE 501 Dr. Hang Fourier Analysis Introduction
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ECE 501 Dr. Hang Fourier Analysis Introduction A serious drawback: time information is lost Cannot handle transitory characteristics
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ECE 501 Dr. Hang Short-Time Fourier Analysis Introduction A compromise between the time- and frequency-based views of a signal: analyze a small section of the signal at a time A drawback: The window is the same for all frequencies
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ECE 501 Dr. Hang Wavelet Analysis Introduction A windowing technique with variable-sized regions: long time interval for low-frequency information, shorter regions for high-frequency information Time-scale region
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ECE 501 Dr. Hang What is Wavelet Analysis Introduction A wavelet is a waveform of effectively limited duration that has an average value of zero Wavelet analysis is the breaking up of a signal into shifted and scaled versions of the original (mother) wavelet.
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ECE 501 Dr. Hang Fourier Analysis The sum over all time of the signal multiplied by a complex exponential Continuous Wavelet Transform
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ECE 501 Dr. Hang CWT The sum over all time of the signal multiplied by scaled, shifted version of the wavelet function Continuous Wavelet Transform
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ECE 501 Dr. Hang Scaling Scaling a wavelet: stretching or compressing it a: scaling factor Continuous Wavelet Transform
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ECE 501 Dr. Hang Scaling Low scale High frequency High scale Low frequency Continuous Wavelet Transform
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ECE 501 Dr. Hang Shifting Continuous Wavelet Transform
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ECE 501 Dr. Hang Five Steps to a CWT 1.Take a wavelet and compare it to a section at the start of the original signal 2. Calculate the wavelet coefficient C Continuous Wavelet Transform
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ECE 501 Dr. Hang Five Steps to a CWT 3.Shift the wavelet to the right and repeat steps 1 and 2 until the whole signal is covered. Continuous Wavelet Transform
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ECE 501 Dr. Hang Five Steps to a CWT 4.Scale the wavelet and repeat steps 1 through 3 Continuous Wavelet Transform
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ECE 501 Dr. Hang Five Steps to a CWT 5.Repeat steps 1 through 4 for all scales Continuous Wavelet Transform
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ECE 501 Dr. Hang Plot CWT coefficients Continuous Wavelet Transform
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ECE 501 Dr. Hang Plot CWT coefficients Continuous Wavelet Transform
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ECE 501 Dr. Hang Dyadic scales and positions: Mallat algorithm: fast algorithm via filtering Accurate analysis: compression, denoising Discrete Wavelet Transform
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ECE 501 Dr. Hang One-Stage filtering: Approximations and Details Discrete Wavelet Transform Not Efficient!
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ECE 501 Dr. Hang One-Stage filtering: Approximations and Details Discrete Wavelet Transform Efficient!
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ECE 501 Dr. Hang One-Stage filtering: Approximations and Details Discrete Wavelet Transform
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ECE 501 Dr. Hang One-Stage filtering: Approximations and Details Discrete Wavelet Transform
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ECE 501 Dr. Hang Multiple-Level Decomposition Discrete Wavelet Transform
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ECE 501 Dr. Hang Multiple-Level Decomposition Discrete Wavelet Transform
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ECE 501 Dr. Hang Wavelet Reconstruction Discrete Wavelet Transform Up Sampling
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ECE 501 Dr. Hang Wavelet Reconstruction Discrete Wavelet Transform
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ECE 501 Dr. Hang Wavelet Reconstruction Discrete Wavelet Transform
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ECE 501 Dr. Hang Wavelet Families Daubechies family
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ECE 501 Dr. Hang Wavelet Families Symlets
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ECE 501 Dr. Hang Denoising 1.Decompose 2.Threshold detail coefficients 3.Reconstruct
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ECE 501 Dr. Hang Denoising Two thresholding method: (1) Soft (2) Hard
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