Suppression of white and colored noise in Bangla speech using Kalman filter

Author(s):  
Muhammad Navid Anjum Aadit ◽  
Sharadindu Gopal Kirtania ◽  
Mehnaz Tabassum Mahin
2018 ◽  
Vol 7 (2.7) ◽  
pp. 5
Author(s):  
V Gopi Tilak ◽  
S Koteswara Rao

Maintaining good quality and intelligibility of speech is the primary constraint in mobile communications. The present work is on the enhancement of speech under the consideration of additive white and colored noise environments using Kalman filter. Dual and Joint estimation techniques were applied and the quality of speech is analyzed through the signal to noise ratio. The techniques were applied in both ideal and practical cases for two different speech samples.


Author(s):  

An algorithm for tracking of the welded seams grooving by using a Kalman filter based on six characteristic points of the profile obtained using the RF627 laser vision sensor is proposed. In order to reduce the error in weld seams control, a multilayer neural network with a backpropagation algorithm is created to compensate for errors caused by colored noise when using the Kalman filter. Experimental results show that when the algorithm is applied, the error in tracking the trajectory of weld seams is reduced. Keywords tracking of weld seams; multilayer/multi-pass welding; Kalman filter; multilayer perceptron


Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6307
Author(s):  
Lin Su ◽  
Guangxu Zhou ◽  
Dairong Hu ◽  
Yuan Liu ◽  
Yunhai Zhu

Accurate estimation of the state of charge (SOC) of lithium batteries is paramount to ensuring consistent battery pack operation. To improve SOC estimation accuracy and suppress colored noise in the system, a fractional order model based on an unscented Kalman filter and an H-infinity filter (FOUHIF) estimation algorithm was proposed. Firstly, the discrete state equation of a lithium battery was derived, as per the theory of fractional calculus. Then, the HPPC experiment and the PSO algorithm were used to identify the internal parameters of the second order RC and fractional order models, respectively. As discovered during working tests, the parameters identified via the fractional order model proved to be more accurate. Furthermore, the feasibility of using the FOUHIF algorithm was evaluated under the conditions of NEDC and UDDS, with obvious colored noise. Compared with the fractional order unscented Kalman filter (FOUKF) and integer order unscented Kalman filter (UKF) algorithms, the FOUHIF algorithm showed significant improvement in both the accuracy and robustness of the estimation, with maximum errors of 1.86% and 1.61% under the two working conditions, and a terminal voltage prediction error of no more than 5.29 mV.


2020 ◽  
Vol 125 ◽  
pp. 142-151
Author(s):  
Hongjiang Yu ◽  
Wei-Ping Zhu ◽  
Benoit Champagne

2018 ◽  
Vol 232 ◽  
pp. 01009
Author(s):  
Jingru Zeng ◽  
Yansong Li ◽  
Jun Liu

When an optical current transformer is used to measure current, its output signal is mostly non-linear and contains colored noise; on the other hand, when the power system is in steady state operation, the frequency is not stable. This paper proposes an optical current transformer signal processing method based on colored noise extended Kalman filter which can reduce the measurement error caused by colored noise and realize frequency tracking. The following two cases are considered: 1) the dynamic noise is colored noise; 2) the observation noise is colored noise. In these two cases, the corresponding formulas of the proposed method are analyzed and derived. Simulation results showed that the extended Kalman filtering method based on colored noise can effectively filter the colored noise, and the output waveform and output error obtained by this method are improved effectively.


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