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  2. Markov-tree Bayesian Group-sparse Modeling with Wavelets

    www-sigproc.eng.cam.ac.uk/foswiki/pub/Main/GZ243/Markov_Group_Sparse.pdf
    18 Dec 2016: 24VM 7.44 7.99 8.24 8.36 8.46.
  3. 3F4 Digital Modulation Course (supervisor copy) 1 3F4 Digital ...

    www-sigproc.eng.cam.ac.uk/foswiki/pub/Main/NGK/3F4digmodSV.pdf
    11 Feb 2016: m). 24 3F4 Digital Modulation Course – Section 2 (supervisor copy).
  4. COLOR FILTERS: WHEN “OPTIMAL” IS NOT OPTIMAL H. J. ...

    www-sigproc.eng.cam.ac.uk/foswiki/pub/Main/NGK/TrussellErcan_icip_2016_optimal_filters_v5_final.pdf
    18 May 2016: Image Processing, Vol. 24, No. 10,pp. 3048-3059, 2015. [7] N. Shimano, “Optimization of spectral sensitivities with Gaus-sian distribution functions for a color image acquisition devicein the presence of
  5. The Dual-Tree Complex Wavelet Transform – ACoherentFramework for…

    www-sigproc.eng.cam.ac.uk/foswiki/pub/Main/NGK/sp_mag_finalsub.pdf
    15 Jun 2016: The figure shows the value of the waveletcoefficient d(0, 8) (the 8th coefficient at stage 3 in Figure 24) asa function of no. ... G0(ej ω)| = |H0(ej ω)|, (24)G0(ej ω) 6= H0(ej ω) 0.5 ω.
  6. Variational Bayesian Image Restoration with Group-sparse Modeling of…

    www-sigproc.eng.cam.ac.uk/foswiki/pub/Main/NGK/ZhangG_DSP_S-14-00575_final_upload.pdf
    18 May 2016: q(ξ) =Di=1. qi(ξi) (24). where D is the total number of disjoint groups. ... 12. form, (24). The key steps of VBMM-based image restoration algorithm areshown in Algorithm 1.
  7. 4F8 Image Coding Course 1 4F8 Image Coding Course ...

    www-sigproc.eng.cam.ac.uk/foswiki/pub/Main/NGK/4F8CODING.pdf
    11 Feb 2016: p(x) dx =[1. 2ex/x0. ]x2x1. = 12(ex1/x0 ex2/x0). 24 4F8 Image Coding - Section 2.
  8. IIB 4F8: Image Processing and Image CodingHandout 0: Introduction ...

    www-sigproc.eng.cam.ac.uk/foswiki/pub/Main/4F8_2012/4F8_Master2016.pdf
    16 Feb 2016: Y (ω1, ω2) = F(ω1, ω2)G(ω1, ω2). 24. Summary of LSI system relationships. ... 4 1 2ej(p1p2) π. 24. Thus. c1(p1, p2) =1. 4 1 2(4).
  9. A Review of Machine Learning Applied to Medical Time ...

    www-sigproc.eng.cam.ac.uk/foswiki/pub/Main/JV365/Technical_Report_Jos_vanderWesthuizen.pdf
    12 Oct 2016: 152.2.2 Neonatal Intensive Care Unit. 24. 2.3 Machine Learning for Sequential Data. ... Data from 35patients was collected over more than 24 hours at 0.1 Hz.
  10. Multimedia Over Cognitive Radio Networks: Algorithms, Protocols, and…

    www-sigproc.eng.cam.ac.uk/foswiki/pub/Main/BIA23/BookChapter.pdf
    29 Apr 2016: 22], the development of Analogue to Digital Converters (ADCs) with high resolutionand reasonable power consumption is relatively behind [23, 24].
  11. Main Technical Lemma in the Finite Sample Analysis of ...

    www-sigproc.eng.cam.ac.uk/foswiki/pub/Main/RV285/main_lemma_finite_sample_analysis.pdf
    31 Jan 2016: Proof of Lemma 3. We begin by demonstrating result (24). By (3) it follows. ... 12. 3τ0L. )(132). Pr(‖1,0‖. N. 24. 3τ0L. ) Pr. (‖Z0‖N 1 243τ0L.

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