Astronomy and Astrophysics – Astrophysics
Scientific paper
Jun 1996
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1996spie.2750..139q&link_type=abstract
Proc. SPIE Vol. 2750, p. 139-146, Digital Signal Processing Technology, Joseph Picone; Ed.
Astronomy and Astrophysics
Astrophysics
1
Scientific paper
A broad array of applications in the Public Switched Telephone Network (PSTN) require detailed information about type of call being carried. This information can be used to enhance service, diagnose transmission impairments, and increase available call capacity. The increase in data rates of modems and the increased usage of speech compression in the PSTN has rendered existing detection algorithms obsolete. Wavelets, specifically the Discrete Wavelet Transform (DWT), are a relatively new analysis tool in Digital Signal Processing. The DWT has been applied to signal processing problems ranging from speech compression to astrophysics. In this paper, we present a wavelet-based method of categorizing telephony traffic by call type. Calls are categorized as Voice or Data. Data calls, primarily modem and fax transmissions, are further divided by the International Telecommunications Union-Telephony (ITU-T), formerly CCITT, V-series designations (V.22bis, V.32, V.32bis, and V.34).
Adhami Reza R.
Quirk Patrick J.
Tseng Yi-Chyun
No associations
LandOfFree
Efficient wavelet-based voice/data discriminator for telephone networks does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Efficient wavelet-based voice/data discriminator for telephone networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Efficient wavelet-based voice/data discriminator for telephone networks will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1304993