Waveform recognition in the presence of domain and amplitude noise

Author

Akra, Mohamad A. ; Mitter, Sanjoy K.

Author_Institution

Dept. of Electr. & Comput. Eng., American Univ. of Beirut, Lebanon

Volume

43

Issue

1

fYear

1997

fDate

1/1/1997 12:00:00 AM

Firstpage

174

Lastpage

182

Abstract

In this paper, we discuss the problem of recognizing single-dimensional, real-valued, functions in the presence of domain noise (i.e., noise that affects the domain rather than the amplitude). This problem is inspired by the field of on-line character recognition where it is more natural to view the hand as deforming the domain of the character rather than adding noise to its amplitude. The results obtained illustrate the difficulties one faces when dealing with both domain and amplitude deformation of waveforms or images. Our major result is a set of sufficient conditions that a recognition metric has to satisfy. Examples of metrics that satisfy these conditions, and hence are appropriate for recognition when the deformation affects the domain rather than the amplitude, include the supnorm metric and the total variation metric. Furthermore, we extend the results to the case when a waveform is corrupted by both amplitude and domain deformation

Keywords

character recognition; image recognition; noise; waveform analysis; amplitude deformation; amplitude noise; domain deformation; domain noise; images; on-line character recognition; recognition metric; single-dimensional real-valued functions; supnorm metric; total variation metric; waveform recognition; Additive noise; Character recognition; Cost function; Counting circuits; Extraterrestrial measurements; Maximum likelihood detection; Noise level; Space technology; Sufficient conditions; White noise;

fLanguage

English

Journal_Title

Information Theory, IEEE Transactions on

Publisher

ieee

ISSN

0018-9448

Type

jour

DOI

10.1109/18.567674

Filename

567674