Online speech dereverberation with time-varying assumption of acoustic transfer functions for teleconferencing systems

2012 ◽  
Author(s):  
Masahito Togami ◽  
Yohei Kawaguchi ◽  
Nobuo Nukaga
Keyword(s):  
Transfer Functions ◽  
Time Varying ◽  
Speech Dereverberation

Using Sliding Mode Control to Adjust Drum Level of a Boiler Unit With Time Varying Parameters

2010 ◽  
Author(s):  
Hamed Moradi ◽  
Firooz Bakhtiari-Nejad ◽  
Majid Saffar-Avval ◽  
Aria Alasty
Keyword(s):  
Water Level ◽  
Transfer Functions ◽  
Sliding Mode ◽  
Operating Conditions ◽  
Model Parameters ◽  
Feed Water ◽  
Time Varying ◽  
Boiler Unit ◽  
Varying Parameters ◽  
Time Varying Parameters

Stable control of water level of drum is of great importance for economic operation of power plant steam generator systems. In this paper, a linear model of the boiler unit with time varying parameters is used for simulation. Two transfer functions between drum water level (output variable) and feed-water and steam mass rates (input variables) are considered. Variation of model parameters may be arisen from disturbances affecting water level of drum, model uncertainties and parameter mismatch due to the variant operating conditions. To achieve a perfect tracking of the desired drum water level, two sliding mode controllers are designed separately. Results show that the designed controllers result in bounded values of control signals, satisfying the actuators constraints.

scholarly journals Analysis of nonstationarity in renal autoregulation mechanisms using time-varying transfer and coherence functions

2008 ◽  
Vol 295 (3) ◽  
pp. R821-R828 ◽  
Author(s):  
Ki H. Chon ◽  
Yuru Zhong ◽  
Leon C. Moore ◽  
Niels H. Holstein-Rathlou ◽  
William A. Cupples
Keyword(s):  
Transfer Functions ◽  
Low Frequency ◽  
Time Varying ◽  
Frequency Range ◽  
Sprague Dawley ◽  
Dynamic Complexity ◽  
Spontaneously Hypertensive ◽  
Renal Autoregulation ◽  
Blood Flow Dynamics ◽  
Frequency Coherence

The extent to which renal blood flow dynamics vary in time and whether such variation contributes substantively to dynamic complexity have emerged as important questions. Data from Sprague-Dawley rats (SDR) and spontaneously hypertensive rats (SHR) were analyzed by time-varying transfer functions (TVTF) and time-varying coherence functions (TVCF). Both TVTF and TVCF allow quantification of nonstationarity in the frequency ranges associated with the autoregulatory mechanisms. TVTF analysis shows that autoregulatory gain in SDR and SHR varies in time and that SHR exhibit significantly more nonstationarity than SDR. TVTF gain in the frequency range associated with the myogenic mechanism was significantly higher in SDR than in SHR, but no statistical difference was found with tubuloglomerular (TGF) gain. Furthermore, TVCF analysis revealed that the coherence in both strains is significantly nonstationary and that low-frequency coherence was negatively correlated with autoregulatory gain. TVCF in the frequency range from 0.1 to 0.3 Hz was significantly higher in SDR (7 out of 7, >0.5) than in SHR (5 out of 6, <0.5), and consistent for all time points. For TGF frequency range (0.03–0.05 Hz), coherence exhibited substantial nonstationarity in both strains. Five of six SHR had mean coherence (<0.5), while four of seven SDR exhibited coherence (<0.5). Together, these results demonstrate substantial nonstationarity in autoregulatory dynamics in both SHR and SDR. Furthermore, they indicate that the nonstationarity accounts for most of the dynamic complexity in SDR, but that it accounts for only a part of the dynamic complexity in SHR.

scholarly journals Binary dragonfly optimization for feature selection using time-varying transfer functions

2018 ◽  
Vol 161 ◽  
pp. 185-204 ◽  
Author(s):  
Majdi Mafarja ◽  
Ibrahim Aljarah ◽  
Ali Asghar Heidari ◽  
Hossam Faris ◽  
Philippe Fournier-Viger ◽  
...  
Keyword(s):  
Feature Selection ◽  
Transfer Functions ◽  
Time Varying

Speech Dereverberation Based on Maximum-Likelihood Estimation With Time-Varying Gaussian Source Model

2008 ◽  
Vol 16 (8) ◽  
pp. 1512-1527 ◽  
Author(s):  
Tomohiro Nakatani ◽  
Biing-Hwang Juang ◽  
Takuya Yoshioka ◽  
Keisuke Kinoshita ◽  
Marc Delcroix ◽  
...  
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Likelihood Estimation ◽  
Source Model ◽  
Time Varying ◽  
Speech Dereverberation ◽  
Gaussian Source

Model order reduction based on discrete-time Laguerre functions for discrete linear periodic time-varying systems

2020 ◽  
Vol 42 (16) ◽  
pp. 3281-3289
Author(s):  
Li-Li Sun ◽  
Kang-Li Xu ◽  
Yao-Lin Jiang
Keyword(s):  
Model Order Reduction ◽  
Transfer Functions ◽  
Order Reduction ◽  
Time Varying ◽  
Laguerre Functions ◽  
Model Order ◽  
Reduced Order ◽  
Engineering Problems ◽  
Time Varying Systems ◽  
Order Reduction Method

Many engineering problems can be modelled as linear periodic time-varying (LPTV) systems, which naturally leads to the need for model order reduction of LPTV systems. This paper investigates a new model order reduction method for discrete LPTV systems. First, the state-space realization in the Fourier-lifted form of discrete LPTV system is constructed by representing periodic matrices in exponentially modulated periodic (EMP) Fourier series. By using Laguerre functions to expand the transfer function of the resulting Fourier-lifted system, the corresponding model order reduction algorithm is developed. Furthermore, the proposed algorithm is used to reduce the discrete LPTV system in the standard-lifted form. Theoretical analysis indicates that the transfer functions of both reduced order systems can match a certain number of moments. Finally, two numerical examples are given to verify the effectiveness of the proposed method.

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