2003 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (IEEE Cat. No.03TH8684)
DOI: 10.1109/aspaa.2003.1285795
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Frequency warped Burg's method for AR-modeling

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Cited by 23 publications
(25 citation statements)
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“…Roth and Keiler [5] give a good description of the Burg's method applied onto one band. The Burg method estimates a model in a recursive manner with reduced computational effort.…”
Section: B Ar Model Fitmentioning
confidence: 99%
See 1 more Smart Citation
“…Roth and Keiler [5] give a good description of the Burg's method applied onto one band. The Burg method estimates a model in a recursive manner with reduced computational effort.…”
Section: B Ar Model Fitmentioning
confidence: 99%
“…The Burg method is one method to solve this problem and described by Roth [5]. Burg's method calculates the reflection coefficients k l so that they minimize the sum of the forward and backward residual error.…”
Section: ) Single Band Ar Filter Estimationmentioning
confidence: 99%
“…Nevertheless, they could not establish a correlation with the percentage of the stenosis development, which is an important factor in the early detection and diagnosis of the problem. Only a few studies have indicated that changes in the percentage of the vascular diameter affect stenosis severity [11,12,17].…”
Section: Frequency Features and Characteristicsmentioning
confidence: 99%
“…Some studies state that higher frequencies, in the range of 300 Hz and above, correlate with a higher degree of stenosis [11][12][13].Several analytical techniques have been applied to analyze these acoustic signal features to correlate them with the stages of the stenosis problem. These include root mean square (RMS), true RMS (TRMS), amplitude (A) [11], shorttime Fourier transform (STFT) and wavelet transform (WT) [13][14][15], artificial neural network (ANN) [16], Burg's method [17,18], fuzzy Petri net (FPN), probabilistic neural network (PNN) [12,19], and classifiers such as principal component analysis (PCA) [3], support vector machine (SVM) [3,20], and many others, as summarized in Table 1. They indicated that with these unique frequency features and their characteristics, normal and abnormal vascular sounds can be differentiated.…”
Section: Current Workmentioning
confidence: 99%
“…• Autoregression coefficients: are the coefficients found through the Burg's method that fit an autoregressive model of the input s [Roth et al, 2003]. This operation is applied to the signal in the time domain and produces an output of 4 features corresponding to the algorithm order such as in [Khan et al, 2010a].…”
Section: Feature Mapping and Dataset Generationmentioning
confidence: 99%