Research of constraint constant modulus medical CT image blind equalization algorithm

2012 ◽  
Vol 31 (6) ◽  
pp. 1575-1577
Author(s):  
Yun-shan SUN ◽  
Li-yi ZHANG ◽  
Ji-zhong DUAN
Keyword(s):  
Blind Equalization ◽  
Ct Image ◽  
Constant Modulus ◽  
Equalization Algorithm

Application of Constraint CMA Blind Equalization Algorithm in the Medical Image Restoration

2012 ◽  
Vol 263-266 ◽  
pp. 2109-2112
Author(s):  
Jin Zhang ◽  
Ya Jie Mao ◽  
Li Yi Zhang ◽  
Yun Shan Sun
Keyword(s):  
Image Restoration ◽  
Cost Function ◽  
Medical Image ◽  
Signal To Noise Ratio ◽  
Blind Equalization ◽  
Optimal Solution ◽  
The Novel ◽  
Constant Modulus ◽  
Signal To Noise ◽  
Equalization Algorithm

A constraint constant module blind equalization algorithm for medical image based on dimension reduction was proposed. The constant modulus cost function applied to medical image was founded. In order to improve the effect of image restoration, a constraint item was introduced to restrict cost function, and it guarantees that the algorithm converge the optimal solution. Compared to the traditional methods, the novel algorithm improves peak signal to noise ratio and restoration effects. Computer simulations demonstrate the effectiveness of the algorithm.

Momentum Factor Constant Modulus Algorithm and Theory

2012 ◽  
Vol 263-266 ◽  
pp. 1058-1061
Author(s):  
Heng Yang ◽  
Jing Wang ◽  
Jing Guan ◽  
Wei Lu
Keyword(s):  
Theoretical Analysis ◽  
Blind Equalization ◽  
Weight Vector ◽  
Convergence Speed ◽  
Constant Modulus ◽  
Constant Modulus Algorithm ◽  
Slow Convergence ◽  
Iteration Formula ◽  
Equalization Algorithm ◽  
Factor Constant

The traditional constant modulus algorithm (CMA) has the disadvantage of slow convergence in blind equalization algorithm. This paper studied one improved algorithm based on momentum factor constant modulus algorithm(MCMA) to solve this problem, momentum factor was added to the weight vector iteration formula of CMA to improve the convergence speed. theoretical analysis and simulation showed that: in the case of the same equalization effect, the MCMA converges faster than the traditional constant modulus algorithm, and also different momentum factors have different convergence effects. The larger the momentum factor , the better convergence effect in the defined domain of the momentum factor.

scholarly journals Neural Network Blind Equalization Algorithm Applied in Medical CT Image Restoration

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Yunshan Sun ◽  
Liyi Zhang ◽  
Jin Zhang ◽  
Lijuan Shi
Keyword(s):  
Neural Network ◽  
Image Restoration ◽  
Blind Equalization ◽  
Ct Image ◽  
Original Image ◽  
Equalization Algorithm ◽  
Convergence Performance ◽  
And Performance ◽  
Blind Image ◽  
Method Analysis

A new algorithm for iterative blind image restoration is presented in this paper. The method extends blind equalization found in the signal case to the image. A neural network blind equalization algorithm is derived and used in conjunction with Zigzag coding to restore the original image. As a result, the effect of PSF can be removed by using the proposed algorithm, which contributes to eliminate intersymbol interference (ISI). In order to obtain the estimation of the original image, what is proposed in this method is to optimize constant modulus blind equalization cost function applied to grayscale CT image by using conjugate gradient method. Analysis of convergence performance of the algorithm verifies the feasibility of this method theoretically; meanwhile, simulation results and performance evaluations of recent image quality metrics are provided to assess the effectiveness of the proposed method.

An Optimized Combination of Frequency Domain Adaptive Equalizers

2014 ◽  
Vol 548-549 ◽  
pp. 766-770
Author(s):  
Ke Cheng Leng ◽  
Cheng Bie ◽  
Xi Gong ◽  
Ran Xu ◽  
Ye Cai Guo
Keyword(s):  
Frequency Domain ◽  
Mean Square Error ◽  
Time Domain ◽  
Blind Equalization ◽  
Mean Square ◽  
Constant Modulus ◽  
Equalization Algorithm ◽  
Adaptive Equalizers ◽  
Simulation Results ◽  
The Time Domain

In order to overcome the defects of the high computational loads and selecting the threshold of mean square error (MSE) for time domain decision-directed constant modulus blind equalization algorithm (DD+CMA), a frequency domain parallel decision multi-modulus blind equalization algorithm based on frequency domain MMA(FMMA) and frequency domain LMS (FLMS) algorithm is proposed. The proposed algorithm is composed of the FMMA and FLMS, and the FMMA and FLMS run automatically in soft switching parallel manner. In running process, it is not necessary to selecting the threshold of the MSE. Moreover, the computational loads can be reduced by circular convolution in the frequency domain signals instead of linear one of the time domain signals. Simulation results show that performance of the proposed algorithm outperforms the FLMS and the FMMA algorithm.

Wavelet Frequency Domain Constant Modulus Blind Equalization Algorithm Based on Fractional Lower Order Statistics

2012 ◽  
Vol 198-199 ◽  
pp. 1497-1500
Author(s):  
Jun Guo ◽  
Ye Cai Guo ◽  
Qu Chen ◽  
Yi Bo Zhao
Keyword(s):  
Frequency Domain ◽  
Order Statistics ◽  
Lower Order ◽  
Blind Equalization ◽  
Constant Modulus ◽  
Constant Modulus Algorithm ◽  
Equalization Algorithm ◽  
Domain Constant ◽  
Fractional Lower Order Statistics ◽  
Orthogonal Wavelet Transform

In order to improve the performance of constant modulus algorithm(CMA) in the noise which obeys α-stable distribution, wavelet frequency domain constant modulus blind equalization algorithm based on fractional lower order statistics(WT-FLOSFCMA) is proposed. This proposed algorithm uses fractional lower order statistics to restrain α-stable noise, and its computational loads can be greatly reduced by using FFT technique and the overlapping retention law. In the proposed algorithm, according to the minimum dispersion coefficient criterion, the CMA is optimized, orthogonal wavelet transform is used to improve the convergence rate. The computer simulations in underwater acoustic channels show that the proposed algorithm outperforms than CMA, orthogonal wavelet transform constant modulus algorithm(WT-CMA),and frequency domain blind equalization algorithm based on fractional lower order statistics(FLOSFCMA) in suppressing with inter-symbol interfere, improving convergence rate, and reducing mean square error.

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