Paper Info
Title
Analysis window length selection for linear signal models
Abstract
A method is presented for the selection of analysis window length, or the number of input samples, for linear signal modeling without compromising the model assumptions. It is assumed that the signal of interest lies in a known linear space and noisy samples of the signal is provided. The goal is to use as many signal samples as possible to mitigate the effect of noise without violating the assumptions on the model. An application example is provided to illustrate the suggested method.
Year
DOI
Venue
2015
10.1109/SIU.2015.7130078
Signal Processing and Communications Applications Conference
Keywords
Field
DocType
Linear Models,Parameter Estimation,Signal Modeling
Signal modeling,Pattern recognition,Computer science,Signal-to-noise ratio,Linear space,Signal of interest,Artificial intelligence,Matched filter,Signal averaging,Signal transfer function
Conference
ISSN
Citations 
PageRank 
2165-0608
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Yazar, Alper100.68
Çağatay Candan212611.13