A Fast Karhunen-Loeve Transform for Digital Restoration of Images Degraded by White and Colored Noise

1977 ◽  
Vol C-26 (6) ◽  
pp. 560-571 ◽  
Author(s):  
Jain
Keyword(s):  
Colored Noise ◽  
Digital Restoration ◽  
White And Colored Noise ◽  
Karhunen Loeve Transform

Research on the Speech Enhancement Method based on PCA/KLT Algorithms

2012 ◽  
Vol 239-240 ◽  
pp. 1274-1278
Author(s):  
Guang Yan Wang ◽  
Yan Xiang Geng ◽  
Xiao Qun Zhao
Keyword(s):  
Speech Enhancement ◽  
High Performance ◽  
Large Scale ◽  
Colored Noise ◽  
Minimum Description Length ◽  
Signal To Noise Ratio ◽  
Principal Component ◽  
White And Colored Noise ◽  
Karhunen Loeve Transform ◽  
Subspace Selection

In this paper, we propose a speech enhancement technique in terms of subspace methods to reduce the white or colored noise in strong background noise environment. This subspace approach based on Karhunen-Loève transform (KLT) and implemented via Principal Component Analysis (PCA). The subspace selection provided by the minimum description length (MDL) criterion. An offset factor generated from the white noise was used to modify the variance to adapt to the specified colored noise. The objective speech quality measures SegSNR have been introduced to evaluate the performance of the proposed method in time domain. A large amount of data and figures testify that our algorithm provides high performance for a large scale of input signal-to-noise ratio (-5~10dB). The performance of our algorithm is assessed in white and colored noise.

scholarly journals Dual and joint estimation for speech enhancement

2018 ◽  
Vol 7 (2.7) ◽  
pp. 5
Author(s):  
V Gopi Tilak ◽  
S Koteswara Rao
Keyword(s):  
Kalman Filter ◽  
Speech Enhancement ◽  
Mobile Communications ◽  
Colored Noise ◽  
Signal To Noise Ratio ◽  
Joint Estimation ◽  
Signal To Noise ◽  
Estimation Techniques ◽  
White And Colored Noise

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.

scholarly journals Statistical Characteristics of Signal Parameter Estimation by Normalized Correlation Function Maximization

2018 ◽  
pp. 15-22
Author(s):  
I. V. Gogolev ◽  
G. Yu. Yashin
Keyword(s):  
Correlation Function ◽  
Colored Noise ◽  
Information Matrix ◽  
Likelihood Estimation ◽  
Schwarz Inequality ◽  
Nuisance Parameters ◽  
Statistical Characteristics ◽  
Function Estimation ◽  
Signal Parameter ◽  
White And Colored Noise

In this paper differences between Fisher Information Matrix (FIM) and inverse covariation matrix of normalized correlation estimations for white and colored noise are investigated. It’s shown that implementation of normalized correlation function estimation leads to modification of maximum likelihood estimation FIM elements, so in case of arbitrary energy affected parameter vector, variance of estimation by normalized correlation function maximization is not equal to Cramer–Rao lower bound. Statistical characteristics of joint Doppler stretch and delay estimation by maximization of normalized correlation function for signal with nuisance parameters are derived in this paper. It’s shown that normalized correlator is equal to wideband ambiguity function, but this method of estimation follows from Cauchy–Schwarz inequality without using energy conservation assumptions. Besides, it is proved that estimation of Doppler stretch and delay by normalized correlation function or WBAF of signal with random initial phase and gain is asymptotically unbiased and effective.

scholarly journals Computer-Based Analysis of the Stochastic Stability of Mechanical Structures Driven by White and Colored Noise

2018 ◽  
Vol 10 (10) ◽  
pp. 3419 ◽  
Author(s):  
Aydin Azizi
Keyword(s):  
White Noise ◽  
Pid Controller ◽  
Colored Noise ◽  
Gaussian White Noise ◽  
Active Suspension ◽  
Suspension System ◽  
Pavement Condition ◽  
White And Colored Noise ◽  
Computer Based ◽  
Environment Sustainability

The goal of this paper is to design an effective Proportional Integral Derivative (PID) controller, which will control the active suspension system of a car, in order to eliminate the imposed vibration to the car from pavement. In this research, Gaussian white noise has been adopted to model the pavement condition, and MATLAB/Simulink software has been used to design a PID controller, as well as to model the effect of the white noise on active suspension system. The results show that the designed controller is effective in eliminating the effect of road conditions. This has a significant effect on reducing the fuel consumption and contributes to environment sustainability.

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