Optimisation of quantisers in the frequency domain

Access Full Text

Optimisation of quantisers in the frequency domain

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Add to cart
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)
Add to cart

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
Electronics Letters — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

© IEE
Published

The author presents a procedure for optimising the scalar quantiser, based on the power spectrum density of the quantisation noise. The input signal is assumed to be stationary in the wide sense, but no restriction is made concerning its probability density function.

Inspec keywords: noise; quantisation (signal); optimisation

Other keywords: quantisation noise; probability density function; power spectrum density; stationary input signal; scalar quantiser; frequency domain

Subjects: Optimisation techniques; Optimisation techniques; Information theory; Signal processing and detection

References

    1. 1)
      • M.D. Paez , T.H. Glisson . Minimum mean-squared-error quantisation inspeech PCM and DPCM systems. IEEE Trans. Commun. , 225 - 230
    2. 2)
      • Alencar, M.S.: `Measurement of the probability density function of communicationsignals', Proc. IEEE Instrumentation and MeasurementTechnology Conf. - IMTC'89, April 1989, Washington DC, p. 513–516.
    3. 3)
      • B. Lévine . (1973) Fondements théoriques de la radiotechnique statistique.
    4. 4)
      • Alencar, M.S.: `Near optimum filtering of quantised signals', Proc. IEEE Int. Symp. on Information Theory, September 1995, Whistler, Canada, p. 117.
    5. 5)
      • J. Max . Quantising for minimum distortion. IEEE Trans. Inf.Theory , 1 , 7 - 12
    6. 6)
      • Alencar, M.S., Aguiar Neto, B.G.: `Estimation of the probabilitydensity function by spectral analysis: a comparative study', Proc. Treizième Colloque sur le Traitement du Signal etdes Images - GRETSI, September 1991, Juan-Les-Pins, France, p. 377–380 .
    7. 7)
      • A.B. Sripad , D.L. Snyder . A necessary and sufficient condition for quantisationerrors to be uniform and white. IEEE Trans. Accoust., SpeechSignal Process. , 5
    8. 8)
      • W.R. Bennett . Spectra of quantised signals. Bell Syst. Tech. J. , 446 - 472
    9. 9)
      • S.P. Lloyd . Least squares quantisation in PCM. IEEE Trans.Inf. Theory , 2 , 129 - 137
    10. 10)
      • M.S. Jayant , P. Noll . (1984) Digital coding of waveforms.
    11. 11)
      • Alencar, M.S.: `A frequency domain approach to the optimisation of scalarquantisers', Proc. IEEE Int. Symp. on InformationTheory, January 1993, San Antonio, USA, p. 440.
http://iet.metastore.ingenta.com/content/journals/10.1049/el_19980169
Loading

Related content

content/journals/10.1049/el_19980169
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading