A Second Order Hyperstable Adaptive Filter With No Post-error Filtering

2005 ◽  
Author(s):  
M. Padmanabhan ◽  
K. Martin
Keyword(s):  
Adaptive Filter ◽  
Second Order ◽  
Error Filtering

scholarly journals Automatic speech signal segmentation based on the innovation adaptive filter

2014 ◽  
Vol 24 (2) ◽  
pp. 259-270 ◽  
Author(s):  
Ryszard Makowski ◽  
Robert Hossa
Keyword(s):  
Speech Recognition ◽  
Automatic Speech Recognition ◽  
Adaptive Filter ◽  
Speech Signal ◽  
Detection Efficiency ◽  
Difficult Problem ◽  
Second Order ◽  
Signal Segmentation ◽  
Schur Algorithm ◽  
Starting Point

Abstract Speech segmentation is an essential stage in designing automatic speech recognition systems and one can find several algorithms proposed in the literature. It is a difficult problem, as speech is immensely variable. The aim of the authors’ studies was to design an algorithm that could be employed at the stage of automatic speech recognition. This would make it possible to avoid some problems related to speech signal parametrization. Posing the problem in such a way requires the algorithm to be capable of working in real time. The only such algorithm was proposed by Tyagi et al., (2006), and it is a modified version of Brandt’s algorithm. The article presents a new algorithm for unsupervised automatic speech signal segmentation. It performs segmentation without access to information about the phonetic content of the utterances, relying exclusively on second-order statistics of a speech signal. The starting point for the proposed method is time-varying Schur coefficients of an innovation adaptive filter. The Schur algorithm is known to be fast, precise, stable and capable of rapidly tracking changes in second order signal statistics. A transfer from one phoneme to another in the speech signal always indicates a change in signal statistics caused by vocal track changes. In order to allow for the properties of human hearing, detection of inter-phoneme boundaries is performed based on statistics defined on the mel spectrum determined from the reflection coefficients. The paper presents the structure of the algorithm, defines its properties, lists parameter values, describes detection efficiency results, and compares them with those for another algorithm. The obtained segmentation results, are satisfactory.

scholarly journals A Robust Nonlinear RLS Type Adaptive Filter for Second-Order-Intermodulation Distortion Cancellation in FDD LTE and 5G Direct Conversion Transceivers

2019 ◽  
Vol 67 (5) ◽  
pp. 1946-1961 ◽  
Author(s):  
Andreas Gebhard ◽  
Oliver Lang ◽  
Michael Lunglmayr ◽  
Christian Motz ◽  
Ram Sunil Kanumalli ◽  
...  
Keyword(s):  
Adaptive Filter ◽  
Direct Conversion ◽  
Second Order ◽  
Intermodulation Distortion

scholarly journals Learning Characteristics of a new Cascaded Second Order Adaptive Filter.(Dept.E)

2021 ◽  
Vol 25 (1) ◽  
pp. 20-29
Author(s):  
Sherin Kishk ◽  
F. Zaki ◽  
R. El-Awadi
Keyword(s):  
Adaptive Filter ◽  
Second Order
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