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A Fast Converge Dual-Mode Modified Constant Norm Blind Equalization Algorithm

2016 Revista Técnica de la Facultad de Ingeniería Universidad del Zulia  
A dual-mode blind equalization algorithm for quadrature amplitude modulation signals is proposed in this paper.  ...  The proposed algorithm firstly starts the equalization by CNA and then introduces DD when the eyediagram is convergent. The switching rule is carried out by the mixed gradient.  ...  The selection of cost function is key point of Bussgang Blind Equalization Algorithm.  ... 
doi:10.21311/001.39.6.43 fatcat:cavriiu4d5d27kdfvuk34hs4mi

Novel On-Line Adaptive Learning Algorithms for Blind Deconvolution Using the Natural Gradient Approach

Shun-ichi Amari, Scott C. Douglas, Andrzej Cichocki, Howard H. Yang
1997 IFAC Proceedings Volumes  
The single-channel algorithms are based on Bussgang blind error criteria, and the multichannel algorithm is based on a modi ed maximum entropy formulation.  ...  In this paper, the e cient natural gradient Amari et.al. (1996)] o r relative gradient Cardoso and Laheld (1996) ] is extended to derive a set of on-line adaptive algorithms for single channel and combined  ...  An important practical issue of Bussgang techniques is their relatively-slow c o nvergence speeds, as these methods may fail to obtain proper equalization in a reasonable number of iterations for channels  ... 
doi:10.1016/s1474-6670(17)42972-7 fatcat:fimpwwszkneafbb6qcmia5s7we

Effects of blind channel equalization using the regressive accelerator algorithm version ɣ

Johanna Andrea Hurtado Sánchez, Pablo Emilio Jojoa Gómez
2018 Sistemas y Telemática  
This way, simulations of the obtained results are done in comparison with the algorithms based on the stochastic gradient and with the Bussgang algorithms.  ...  We present a blind channel equalization scheme, applied to ɣ version regressive acceleration algorithm, which uses self-taught equalization techniques to study the characteristics of both, the second and  ...  The results of the blind equalizer implementation by using the ARγ algorithm and the superior order statistics of the Bussgang algorithms show the blind channel equalization through a minimal squared error  ... 
doi:10.18046/syt.v16i46.3009 fatcat:k3gqtrtqtzellf25afisyvcqyi

Fast Fixed-Point Neural Blind-Deconvolution Algorithm

S. Fiori
2004 IEEE Transactions on Neural Networks  
The aim of the present Letter is to introduce a new blind deconvolution algorithm based on fixed-point optimization of a 'Bussgang'-type cost function.  ...  The main feature of the presented algorithm is fast convergence that guarantees good deconvolution performances with limited computational demand compared to algorithms of the same class.  ...  Hyvärinen (HUT, Helsinki -Finland) for kindly bringing to my attention the "super-exponential" algorithm [14] .  ... 
doi:10.1109/tnn.2004.824258 pmid:15384537 fatcat:gnwoahxn25cpbahxx4td5yla5u

Blind deconvolution by a Newton method on the non-unitary hypersphere

S. Fiori
2012 International Journal of Adaptive Control and Signal Processing  
The aim of the present paper is to introduce a class of Newton-type algorithms to optimize the Bussgang cost function on the inverse-filter parameter space whose geometrical structure is induced by the  ...  The aim of the present contribution is to discuss a class of Newton-type algorithms to optimize the Bussgang cost function on the parameter space whose geometrical nature is induced by the automatic gain  ...  the enhanced Bussgang algorithm (4), the Bussgang algorithm (5), the Bussgang algorithm with natural gradient (6), the enhanced Bussgang algorithm with natural gradient (7), the fixed-point enhanced Bussgang  ... 
doi:10.1002/acs.2324 fatcat:ninkwcc7fjallauc67nfpa2dd4

Multi-stage blind clustering equaliser

S. Chen, S. McLaughlin, P.M. Grant, B. Mulgrew
1995 IEEE Transactions on Communications  
The constant modulus algorithm (CMA) is used as a benchmark to assess this multi-stage blind equaliser.  ...  A multi-stage blind clustering algorithm is proposed for equalisation of multi-level quadrature amplitute modulation (M-$AM) channels.  ...  Karaoguz and Ardalan's algorithm, referred to as the soft decision-directed blind algorithm in [12] , is a Bussgang-type algorithm well fitted to the finite nature of digital symbol constella.tion.  ... 
doi:10.1109/26.380093 fatcat:dcss4x2o2bcphegsdmr7za5fse

Statistical reference criteria for adaptive signal processing in digital communications

J. Sala-Alvarez, G. Vazquez-Grau
1997 IEEE Transactions on Signal Processing  
Equations for gradient-based coefficient updates are derived, and the relationship with other existing algorithms like the minimum variance and the Wiener criterion are examined.  ...  The knowledge of the pdf of the wanted signal is used as a discriminator between signals so that interferers with differing distributions are rejected by the algorithm.  ...  The algorithm is sensitive to the pdf of the actual distribution and is thus more robust in the presence of interference than are blind algorithms of the Bussgang-type, although the cost function is still  ... 
doi:10.1109/78.552202 fatcat:rljyie5bxvbppnhr77ba6ptimm

A New Speech Enhancement Algorithm for Car Environment Noise Cancellation with MBD and Kalman Filtering

S. BEACK
2005 IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences  
The final performance evaluated with the severely car noise corrupted speech shows that our algorithm produces noticeably enhanced speech. key words: speech enhancement, multichannel blind deconvolution  ...  Our algorithm is composed of two main parts, i.e., the spatial and the temporal processes.  ...  Frequency Domain Block-Based MBD (FB-MBD) Gradient algorithms show fast convergence properties when their estimations are based on block processes due to the more accurate gradient vector estimation [  ... 
doi:10.1093/ietfec/e88-a.3.685 fatcat:5u7g66elnjh7vhjhilgg4lptlm

Adaptive blind signal processing-neural network approaches

S. Amari, A. Cichocki
1998 Proceedings of the IEEE  
Keywords-Blind deconvolution and equalization, blind separation of signals, independent component analysis (ICA), natural gradient learning, neural networks, self-adaptive learning rates, unsupervised  ...  Learning algorithms and underlying basic mathematical ideas are presented for the problem of adaptive blind signal processing, especially instantaneous blind separation and multichannel blind deconvolution  ...  This channel equalization methodology is the multichannel equivalent of the traditional Bussgang blind equalization schemes [61] , [88] , [103] .  ... 
doi:10.1109/5.720251 fatcat:jg337aeuxnd3rec634qd3qjfde

Comparative Survey of Signal Processing and Artificial Intelligence Based Channel Equalization Techniques and Technologies

John Martin Ladrido, De La Salle University, Philippines
2019 International Journal of Emerging Trends in Engineering Research  
These equalizers were compared, contrasted, and their key differentiation was identified.  ...  It was found that gaps such as complexity and convergence time are potential areas for extending the performance and limits of existing channel equalizers.  ...  Another popular adaptive blind equalization is the Bussgang algorithm (the Godard algorithm) or constant modulus (CMA) and fraction-spaced CMA algorithms [62] .  ... 
doi:10.30534/ijeter/2019/14792019 fatcat:rz2vabommrhdrgw47zpino5vou

Blind channel estimation and data detection using hidden Markov models

C. Anton-Haro, J.A.R. Fonollosa, J.R. Fonollosa
1997 IEEE Transactions on Signal Processing  
In this correspondence, we propose applying the hidden Markov models (HMM) theory to the problem of blind channel estimation and data detection.  ...  Additionally, a version of the algorithm that is suitable for timevarying channels is also presented.  ...  Blind equalization/estimation methods developed so far can be classified in three families: 1) Bussgang algorithms [1] , [2] 2) polyspectra and cumulant-based algorithms [1] , [3] 3) probabilistic  ... 
doi:10.1109/78.552223 fatcat:gzoj3znx6fbfhp2oilynjhcmuu

Relative optimization for blind deconvolution

A.M. Bronstein, M.M. Bronstein, M. Zibulevsky
2005 IEEE Transactions on Signal Processing  
Index Terms-blind deconvolution, Newton method, natural gradient, maximum likelihood.  ...  We propose a relative optimization framework for quasi maximum likelihood (QML) blind deconvolution and the relative Newton method as its particular instance.  ...  A wide class of the so-called Bussgang algorithms estimate directly the inverse kernel W (z) = A −1 (z) by minimizing some cost function using gradient descent iterations.  ... 
doi:10.1109/tsp.2005.847822 fatcat:upvhzboxwnfnzo2bt4bns27qyy

Analysis Of Blind Decision Feedback Equalizer Convergence: Interest Of A Soft Decision

S. Cherif, S. Marcos, M. Jaidane
2008 Zenodo  
In this paper the behavior of the decision feedback equalizers (DFEs) adapted by the decision-directed or the constant modulus blind algorithms is presented.  ...  Computer simulations show that these modified algorithms present better ability to avoid local minima than conventional ones.  ...  Among them, the Bussgang-type algorithms are initially introduced and analyzed for a transversal structure of the equalizer [3] , [4] .  ... 
doi:10.5281/zenodo.1076903 fatcat:hsfrptqwlnhi3cjn2dtnkkecqu

Multichannel blind deconvolution of spatially misaligned images

F. Sroubek, J. Flusser
2005 IEEE Transactions on Image Processing  
Existing multichannel blind restoration techniques assume perfect spatial alignment of channels, correct estimation of blur size, and are prone to noise.  ...  Index Terms-Image restoration, maximum a posteriori (MAP) estimator, multichannel blind deconvolution, subspace methods, variational integral.  ...  MC blind deconvolution based on the Bussgang algorithm was proposed in [26] , which performs well on spatially uncorrelated data, such as binary text images and spiky images.  ... 
doi:10.1109/tip.2005.849322 pmid:16028551 fatcat:mbdaswcmi5fkbmrop35ezcxoru

Blind adaptive energy estimation for decorrelating decision-feedback CDMA multiuser detection using learning-type stochastic approximations

Po-Rong Chang, Chih-Chien Lee, Chin-Feng Lin
1999 IEEE Transactions on Vehicular Technology  
In this paper, a new novel blind estimation mechanism is proposed to estimate all the users' energies using a stochastic approximation algorithm without training data.  ...  In order to increase the convergence speed of the energy estimation, a linear reinforcement learning technique is conducted to accelerate the stochastic approximation algorithms.  ...  blind equalization [13] .  ... 
doi:10.1109/25.752579 fatcat:7u2u2a3teverbb5fzzftqvi5r4
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