• Phonetics and Speech Sciences
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• v.4 no.2
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• pp.79-86
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• 2012

In this paper, we propose a novel approach to improve histogram equalization for speaker identification. Our method collects all speech features of UBM training data to make a reference distribution. The ranks of the feature vectors are calculated in the sorted list of the collection of the UBM training data and the test data. We use the ranks to perform order-based histogram equalization. The proposed method improves the accuracy of the speaker recognition system with short utterances. We use four kinds of speech databases to evaluate the proposed speaker recognition system and compare the system with cepstral mean normalization (CMN), mean and variance normalization (MVN), and histogram equalization (HEQ). Our system reduced the relative error rate by 33.3% from the baseline system.

• Journal of Communications and Networks
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• v.11 no.5
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• pp.473-479
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• 2009

Conventional frequency domain equalization (FDE) schemes were originally devised for quasi-static channels. Thus, such equalization schemes could suffer from significant performance degradation in fast-fading channels. This paper proposes a frequency domain equalization algorithm to mitigate the effect of fast time-varying fading. First, a mathematical expression is derived to quantify the total interference resulting from the time variation of the channel. Then, the proposed approach attempts to eliminate the effect of time-variations of the channel. This cancellation allows efficient use of the classical FDE structures in fast time-varying fading environments, although they are built upon the quasi-static channel model. Simulation results of bit-error-rate performance are provided to demonstrate the effectiveness of the proposed algorithm.

• Korean Journal of Optics and Photonics
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• v.13 no.6
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• pp.486-492
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• 2002

In this paper. we presented 1 & 2 dimensional minimum mean-squared-error (MMSE) equalization scheme in a digital holographic data storage system to improve bit-error-rate (BER) and to mitigate inter-symbol interference (ISI) which were generated during the data storage and retrieval processes. We showed experimentally for ten data pages retrieved from the holographic storage system that BER and signal-to-noise ratio (SNR) were improved by adopting MMSE equalization.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.2
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• pp.476-483
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• 2010

If the data are pre-whitened, then gradient adaptive algorithms which are simpler than higher order statistics algorithms can be used in adaptive blind signal estimation. In this paper, we propose a blind subband affine projection algorithm for multiple-input multiple-output adaptive equalization in the blind environments. All of the adaptive filters in subband affine projection equalization are decomposed to polyphase components, and the coefficients of the decomposed adaptive sub-filters are updated by defining the multiple cost functions. An infinite impulse response filter bank is designed for the data pre-whitening. Pre-whitening procedure through subband filtering can speed up the convergence rate of the algorithm without additional computation. Simulation results are presented showing the proposed algorithm's convergence rate, blind equalization and blind signal separation performances.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.4
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• pp.140-145
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• 2008

Fuzzy partition is a conceptual vehicle that encapsulates data into information granules. Fuzzy equalization concerns a process of building information granules that are semantically and experimentally meaningful. A few algorithms generating fuzzy partitions with fuzzy equalization have been suggested. Simulations and experiments have showed that fuzzy partition representing more characteristics of given input distribution usually produces meaningful results. In this paper, given two points and cardinality of fuzzy partition, we prove that it is not true that there always exists a fuzzy partition with fuzzy equalization in which two of points having peaks fall on the given two points. Then, we establish an algorithm that minimizes the maximum distance between given two points and adjacent points having peaks in the partition. A numerical example is presented to show the validity of the suggested algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.753-762
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• 2002

Blind equalization of transmission channel is important in communication areas and signal processing applications because it does not need training sequences, nor dose it require a priori channel information. In this paper, an adaptive blind MMSE channel equalization technique based on second-order statistics in investigated. We present an adaptive blind MMSE channel equalization using multichannel linear prediction error method for estimating cross-correlation vector. They can be implemented as RLS or LMS algorithms to recursively update the cross-correlation vector. Once cross-correlation vector is available, it can be used for MMSE channel equalization. Unlike many known subspace methods, our proposed algorithms do not require channel order estimation. Therefore, our algorithms are robust to channel order mismatch. Performance of our algorithms and comparisons with existing algorithms are shown for real measured digital microwave channel.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.111-113
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• 2004

Histogram Equalization is the most popular algorithm for contrast enhancement due to its effectiveness and simplicity. In this paper, We propose the advanced contrast enhancement method using genetic algorithm. We propose a novel objective criterion for enhancement, and attempt finding the best image according to the respective criterion. Due to the high complexity of the enhancement criterion proposed, we employ a Genetic Algorithm. We compared our method with other enhancement techniques, like Global Histogram Equalization and Partially Overlapped Sub-Block Histogram Equalization(POSHE).

• Journal of Korea Multimedia Society
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• v.11 no.6
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• pp.737-745
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• 2008

In this paper, a novel neighborhood metric of histogram equalization (HE) algorithm for contrast enhancement is presented. We present a refinement of HE using neighborhood metrics with a general framework which orders pixels based on a sequence of sorting functions which uses both global and local information to remap the image greylevels. We tested a novel sorting key with the suggestion of using the original image greylevel as the primary key and a novel neighborhood distinction metric as the secondary key, and compared HE using proposed distinction metric and other HE methods such as global histogram equalization (GHE), HE using voting metric and HE using contrast difference metric. We found that our method can preserve advantages of other metrics, while reducing drawbacks of them and avoiding undesirable over-enhancement that can occur with local histogram equalization (LHE) and other methods.

• Journal of the Korea Society of Computer and Information
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• v.24 no.2
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• pp.57-66
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• 2019

This paper compared the performance with an overview of channel equalization techniques used in high-speed serial transceivers, including the homogeneous architecture and associated components for the GHz interconnect of backplane and cable channels. It also used the MATLAB tool to present system analysis and simulation results for continuous time equivalent structures. In the case of conventional continuous equalization, high frequency deficits occur due to the use of a comparator that is difficult to implement as well as the low speed limit. In this paper, the channel equalization technique based on the power spectrum analysis of clocks was used to compensate for the frequency loss, and the application of the TX+Channel and TX+Equalizer filters enabled the measurement of attenuation and equivalence without comparators. The application of blender and band-pass filters at high speeds also showed significant effectiveness.

• International Journal of Contents
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• v.2 no.4
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• pp.19-24
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• 2006

In this paper, the performance of pre-equalization technique which can be applicable for the B-WLL uplink is evaluated and compared to post-equalization technique under three kinds of rain attenuation channels such as rain, intermittent light rain and thundershower. The BER performance comparisons of two algorithms (LMS and RLS) are investigated in the context of channel models and the length of training sequence. From the simulation results, it is shown that the post-equalization outperforms only at quite good channel conditions such as AWGN, while the pre-equalization can guarantee better BER performance at every channel conditions, especially performance gain increases as the severity of channel increases. It is concluded that the pre-equalizer using LMS algorithm is preferable at delay-tolerant situation where the complexity of algorithm is not a strict factor, while one using RLS is suitable for fast burst transmission with a relatively short training sequence.