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Ultra Low-Power Biomedical Signal Processing: An Analog Wavelet Filter Approach for Pacemakers 2009 ed. [Hardback]

  • Formāts: Hardback, 215 pages, height x width: 235x155 mm, weight: 1100 g, X, 215 p., 1 Hardback
  • Sērija : Analog Circuits and Signal Processing
  • Izdošanas datums: 30-Apr-2009
  • Izdevniecība: Springer-Verlag New York Inc.
  • ISBN-10: 1402090722
  • ISBN-13: 9781402090721
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  • Formāts: Hardback, 215 pages, height x width: 235x155 mm, weight: 1100 g, X, 215 p., 1 Hardback
  • Sērija : Analog Circuits and Signal Processing
  • Izdošanas datums: 30-Apr-2009
  • Izdevniecība: Springer-Verlag New York Inc.
  • ISBN-10: 1402090722
  • ISBN-13: 9781402090721
Citas grāmatas par šo tēmu:
In ultra low-power applications such as biomedical implantable devices, it is not suitable to implement the WT systems by means of digital circuitry due to the relatively high power consumption associated with the required A/D converter. This title presents a novel method for implementing signal processing based on WT in an analog way.

Often WT systems employ the discrete wavelet transform, implemented on a digital signal processor. However, in ultra low-power applications such as biomedical implantable devices, it is not suitable to implement the WT by means of digital circuitry due to the relatively high power consumption associated with the required A/D converter. Low-power analog realization of the wavelet transform enables its application in vivo, e.g. in pacemakers, where the wavelet transform provides a means to extremely reliable cardiac signal detection.In Ultra Low-Power Biomedical Signal Processing we present a novel method for implementing signal processing based on WT in an analog way. The methodology presented focuses on the development of ultra low-power analog integrated circuits that implement the required signal processing, taking into account the limitations imposed by an implantable device.
The Evolution of Pacemakers: An Electronics Perspective.- Wavelet versus
Fourier Analysis.- Analog Wavelet Filters: The Need for Approximation.-
Optimal State Space Descriptions.- Ultra Low-Power Integrator Designs.- Ultra
Low-Power Biomedical System Designs.- Conclusions and Future Research.