• Title/Summary/Keyword: Dyadic tree

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Performance Analysis of a TH-PPM UWB System using Dyadic Tree Structure (다이애딕 구조를 이용한 TH-PPM UWB 시스템의 성능 분석)

  • Park, Joong-Hoo;Choi, Ginkyu
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.8 no.3
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    • pp.87-92
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    • 2008
  • In this paper, certain scaling functions are generated using the dyadic subband tree structure and applied to a time-hopping, pulse position modulation, ultra-wideband (TH-PPM UWB) system. Scaling functions can be obtained by iterating a lowpass filter at each level using a critically sampled dyadic tree. The performance of the TH-PPM UWB system employing scaling functions as the mono-cycle waveform is evaluated through computer simulations in a Rayleigh fading environment.

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An Adaptive Active Noise Cancelling Model Using Wavelet Transform and M-channel Subband QMF Filter Banks (웨이브릿 변환 및 M-채널 서브밴드 QMF 필터뱅크를 이용한 적응 능동잡음제거 모델)

  • 허영대;권기룡;문광석
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.1B
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    • pp.89-98
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    • 2000
  • This paper presents an active noise cancelling model using wavelet transform and subband filter banks based on adaptive filter. The analysis filter banks decompose input and error signals into QMF filter banks of lowpass and highpass bands. Each filter bank uses wavelet filter with dyadic tree structure. The decomposed input and error signals are iterated by adaptive filter coefficients of each subband using filtered-X LMS algorithm. The synthesis filter banks make output signal of wideband with perfect reconstruction to prepare adaptive filter output signals of each subband. The analysis and synthesis niter hants use conjugate quadrature filters for Pefect reconstruction. Also, The delayed LMS algorithm model for on-line identification of error path transfer characteristics is used gain and acoustic time delay factors. The proposed adaptive active noise cancelling modelis suggested by system retaining the computational and convergence speed advantage using wavelet subband filter banks.

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