• Proceedings of the IEEK Conference
• /
• 2001.09a
• /
• pp.869-872
• /
• 2001

Blind identification and equalization of communication channel is important because it does not need training sequence, nor does it require a priori channel information. So, we can increase the bandwidth efficiency. The linear prediction error method is perhaps the most attractive in practice due to the insensitive to blind channel estimator and equalizer length mismatch as well as for its simple adaptive algorithms. In this paper, we propose method for fractionally spaced blind equalizer with arbitrary delay using one-step forward prediction error filter from second-order statistics of the received signals for SIMO channel. Our algorithm utilizes the forward prediction error as training sequences for data estimation and desired signal for channel estimation.

• Proceedings of the IEEK Conference
• /
• 2001.06a
• /
• pp.69-72
• /
• 2001

Blind equalization of transmission channel is important in communication areas and signal processing applications because it does not need training sequence, nor does it require a priori channel information. Recently, Tong et al. proposed solutions for this problem exploit the diversity induced by antenna array or time oversampling, leading to the second order statistics techniques, fur example, subspace method, prediction error method, and so on. The linear prediction error method is perhaps the most attractive in practice due to the insensitive to blind equalizer length mismatch as well as for its simple adaptive filter implementation. Unfortunately, the previous one-step prediction error method is known to be limited in arbitrary delay. In this paper, we induce the optimal delay, and propose the adaptive blind equalizer with multi-step linear prediction using RLS-type algorithm. Simulation results are presented to demonstrate the proposed algorithm and to compare it with existing algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.9C
• /
• pp.1235-1243
• /
• 2004

In this paper, a new blind equalizer algorithm is proposed which operates on dual mode and combines the benefits of both the Sign-Godard algorithm and the radius-directed algorithm The proposed algorithm has both the properties of good initial convergence of the Sign-Godard algorithm and low residual errors after convergence of the radius-directed algorith High order statistics are used for blind phase recovery and gor avoiding local minima. Simulation results show that the new algorithm has not only faster convergence rated but also lower residual errors than those of the conventional algorithms.

• Journal of the Optical Society of Korea
• /
• v.12 no.3
• /
• pp.121-125
• /
• 2008

We address the problem of Blind Source Separation(BSS) of superimposed signals in situations where one signal has constant or slowly varying intensities at some consecutive locations and at the corresponding locations the other signal has highly varying intensities. Independent Component Analysis(ICA) is a major technique for Blind Source Separation and the existing ICA algorithms fail to estimate the original intensities in the stated situation. We combine the advantages of existing sparse methods and Kernel ICA in our technique, by proposing wavelet packet based sparse decomposition of signals prior to the application of Kernel ICA. Simulations and experimental results illustrate the effectiveness and accuracy of the proposed approach. The approach is general in the way that it can be tailored and applied to a wide range of BSS problems concerning one-dimensional signals and images(two-dimensional signals).

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2003.05a
• /
• pp.839-845
• /
• 2003

This paper introduces multichannel blind source separation (BSS) and multichannel blind deconvolution (MBD) based on higher order statistics of signals from convolutive mixtures. In particular, we are concerned with the case that the number of inputs is the same as the number of outputs. Simulations for two input two output cases are carried out and their performances are assessed. One of the major applications of those sequential algorithms (BSS and MBD) is demonstrated through the fault signal detection from only a single measurement of rotating machine, which offers a certain degree of practicability in the engineering field such as machine health monitoring or condition monitoring.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.4 no.4
• /
• pp.295-299
• /
• 2011

Blind equalization techniques have been widely used in wireless communication systems. In this paper, we propose to apply the balanced information potentials to the criterion of minimum Euclidian distance between two PDFs with constant modulus errors for adaptive blind equalizers. One of the two PDFs is constructed with constant modulus error samples and another does with Dirac delta functions. Two information potentials derived from the criterion are balanced in order to have better performance by putting a weighting factor to each information potentials. The proposed blind algorithm has shown in the MSE convergence performance that it can produce enhanced performance by over 3 dB of steady state MSE.

• Journal of IKEEE
• /
• v.10 no.1 s.18
• /
• pp.62-68
• /
• 2006

In this paper, we propose an adaptation strategy for blind equalizers, which combines a blind algorithm based on high order statistics and the decision directed LMS algorithm. In contrast to 'Stop-and-Go' algorithm, where adaptation is stopped for unreliable signals, the proposed algorithm applies high order statistics (HOS) blind algorithm to the unreliable signals and applies DD-LMS for the reliable signals. The proposed algorithm, named 'Run-and-Go' algorithm, inherits minimum MSE performance of DD-LMS and acquisition ability of blind algorithms. Furthermore, by updating the reliable signal region according to signal quality in each iteration, the convergence speed and acquisition ability is further improved.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.2
• /
• pp.3-10
• /
• 2013

Please In this paper, to cope with biased impulsive noise problems, a new information potential is proposed that can move the transmitted symbol points by modifying the information potential designed with Dirac-delta functions. Based on the proposed information potential a new blind algorithm is derived by employing an augmented filter structure. From the simulation results in the environment of biased impulsive noise, the conventional algorithms yield performance degradation by over 15 dB, but the proposed algorithm shows no performance degradation and holds the same steady state MSE of below -25 dB as after the initial convergence regardless of the channel conditions.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.21 no.4
• /
• pp.996-1007
• /
• 1996

In this paper, a blind adaptation method for a decision feedback equalizer (DFE) is proposed to deal with nominimum phase channels. This equalizer is composed of a linear transversal filter and a prediction error filter which are trained separately using constant modulus and decision feedback prediction algorithms, respectively, during the learnign time. The proposed algorithm guaranetees the DFE to converge to a suboptimal point on the condition that a linear transversal of the proposed scheme is illustrated and the performance is compared with conventional blind equlization algorithms.

• Proceedings of the IEEK Conference
• /
• 2002.07c
• /
• pp.1901-1904
• /
• 2002

A good performance on communication systems is obtained by decreasing the length of training sequence In the initial stage of adaptive equalization. This paper presents a new approach to accomplish this, with the use of a training adaptive equalizer. The approach is based on combining the training and tracking modes, in which the training equalizer is updated by the LMS algorithm with the training sequence and then updated by a blind algorithm. By computer simulations, it is shown that a class of the proposed equalizers provides better performance than the conventional training equalizer.