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AIMS CDT - Signal Processing Michaelmas Term 2020 Xiaowen Dong - PowerPoint PPT Presentation

AIMS CDT - Signal Processing Michaelmas Term 2020 Xiaowen Dong Department of Engineering Science Representation of Signals 2 /70 What is a representation of a signal? Sum of delta functions in time or space (sampling domain) - good for


  1. AIMS CDT - Signal Processing Michaelmas Term 2020 Xiaowen Dong Department of Engineering Science

  2. Representation of Signals 2 /70

  3. What is a representation of a signal? • Sum of delta functions in time or space (sampling domain) - good for display or playback - not good for analysis (e.g., denoising, compression) t T 3 /70

  4. What is a representation of a signal? • In a time-series setting, useful representation could be past samples • More generally, it involves transformation of the signal into a new domain - where useful characteristics are revealed example: Fourier coe ffi cients reveal rate of change of the signal - Source: http://www.physik.uni-kl.de • Usefulness of the representation depends on the analysis goal which may vary but all share the core desire for simpli fi cation - 4 /70

  5. Example: Denoising 10 Original Signal Denoised Signal 5 0 -5 -10 0 200 400 600 800 1000 1200 goal: separate signal and noise 5 /70

  6. Example: Compression original JPEG 2000 (comp. ratio: 10) JPEG 2000 (comp. ratio: 100) goal: compress fi le size without sacri fi cing (too much) quality 6 /70

  7. Example: Recognition samples true “causes” PCA ICA sparse coding KSVD [Tosic11] goal: capture true “causes” of signals given noisy input 7 /70

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representation via dictionaries • Orthogonal dictionaries signal dictionary coe ffi cients = X Φ = [ φ 0 φ 1 · · · φ N − 1 ] x c “atoms” 8 /70

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