• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6C
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• pp.384-390
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• 2011

The paper derives formulas for the mean-squared error distortion and resulting signal-to-noise (SNR) ratio of a fixed-rate scalar quantizer designed optimally in the minimum mean-squared error sense for a Gaussian density with the standard deviation ${\sigma}_q$ when it is mismatched to a Laplacian density with the standard deviation ${\sigma}_q$. The SNR formulas, based on the key parameter and Bennett's integral, are found accurate for a wide range of $p\({\equiv}\frac{\sigma_p}{\sigma_q}\){\geqq}0.25$. Also an upper bound to the SNR is derived, which becomes tighter with increasing rate R and indicates that the SNR behaves asymptotically as $\frac{20\sqrt{3{\ln}2}}{{\rho}{\ln}10}\;{\sqrt{R}}$ dB.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.67-75
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• 2012

Optimal quantizers in conducting the entropy-constrained quantization for high bit rates have the lattice structure. The quantization process is simple due to the regular structure, and various quantization algorithms are proposed depending on the lattice. Such a lattice vector quantizer (VQ) can be implemented by using the sample-adaptive product quantizer (SAPQ) and its output can also be easily entropy encoded. In this paper, the entropy encoding scheme for the lattice VQ is proposed based on SAPQ, and the performance of the proposed lattice VQ, which is based on SAPQ with the entropy coder, is asymptotically compared as the rate increases. It is shown by experiment that the gain for the memoryless Gaussian source also approaches the theoretic gain for the uniform density case.

• ETRI Journal
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• v.33 no.5
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• pp.814-817
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• 2011

In this letter, the distributions of direct current (DC) coefficients for P-frames in H.264/AVC are analyzed, and the distortion model of the Gaussian source under the quantization of the dead-zone plus-uniform threshold quantization with uniform reconstruction quantizer is derived. Experimental results show that the DC coefficients of P-frames are best approximated by the Laplacian distribution and the Gaussian distribution at small quantization step sizes and at large quantization step sizes, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.12 no.3
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• pp.216-223
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• 1987

This paper presents an analysis of the effects of statistically independent channel errors on the mean-squared error performance of image transform coding systems. The analysis is discussed for several different stochasic statistics of the quantizer input valuse. The stochastic distributions under consideration here are Laplacian, Gaussian and uniform. For each case of the distributions, we evaluate the MSE performance when NBC, FBC, MDC and Gray code respectively is employed for encoding the quantized values of the transformed coeffecients into the corresponding code words. The result of this study shows that what code is desired to be chosen to minimize the MSE for the given stochastic distributions of the quantizer input values.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.9
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• pp.792-797
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• 2013

This paper has derived the conversion loss according to the synchronized condition between the transmitted and locally generated spreading signals for the civil global positioning system (GPS) receiver in the heavy wideband Gaussian noise environments. From this, the outputs of the 2-bit nonuniform quantizer, which has the minimum conversion loss, is set to ${\pm}1$ and ${\pm}2$, while the quantization step size is approximated to the jamming-to-signal power ratio.

• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.437-442
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• 2005

For the purpose of speaker normalization in speaker independent speech recognition systems, experiments are conducted on a method based on Gaussian mixture model(GMM). The method, which is an improvement of the previous study based on vector quantizer, consists of modeling the probability distribution of canonical feature vectors by a GMM with an appropriate number of clusters, and of estimating the warp factor of a test speaker by making use of the obtained probabilistic model. The purpose of this study is twofold: improving the existing ML based methods, and comparing the performance of what is called 'soft decision' method with that of the previous study based on vector quantizer. The effectiveness of the proposed method is investigated by recognition experiments on the TIMIT corpus. The experimental results showed that a little improvement could be obtained tv adjusting the number of clusters in GMM appropriately.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1A
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• pp.48-55
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• 2000

In this paper, an assumption to design a quantizer, is proposed that if one small region of a probability density function is represented larger probability and bigger total error than another neighbour region, then the quantizer is not optimal. It is tested when the probability functions are Gaussian, Laplacian and uniform density function by the computer simulations. A new LBG algorithm which originates from this assumption in addition to LBG algorithm, is designed for the vector quantizer. The new LBG algorithm presents better performance than the original LBG algorithm in the average error and the variance of the error.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.663-666
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• 2004

In this paper, a modified-SOYA (soft output viterbi algorithm) of turbo codes is proposed for quantized channel receiver filter outputs. We derive optimum branch values for the Viterbi algorithm. Here we assume that received filter outputs are quantized and the channel is additive white Gaussian noise. The optimum non-uniform quantizer is used to quantize channel receiver filter outputs. To compare the BER (bit error rate) performance we perform simulations for the modified SOYA algorithm and the general SOYA

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.106-109
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• 1998

Wireless communication systems, in particular, must operate in a crowded electro-magnetic environmnet where in-band undesired signals are treated as noise by the receiver. These interfering signals are often random but not Gaussian Due to nongaussian noise, the distribution of the observables cannot be specified by a finite set of parameters; instead r-dimensioal sample space (pure noise samples) is equiprobably partitioned into a finite number of disjointed regions using quantiles and a vector quantizer based on training samples. If we assume that the detected symbols are correct, then we can observe the pure noise samples during the training and transmitting mode. The algorithm proposed is based on a piecewise approximation to a regression function based on quantities and conditional partition moments which are estimated by a RMSA (Robbins-Monro Stochastic Approximation) algorithm. In this paper, we develop a diversity combiner with modified detector, called Non-Linear Detector, and the receiver has a differential phase detector in each diversity branch and at the combiner each detector output is proportional to the second power of the envelope of branches. Monte-Carlo simulations were used as means of generating the system performance.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.5
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• pp.29-38
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• 1985

In this paper we have designed and implemented in real time a simple, efficient and flexible AOPCM cosec using a high speed digital processor, NEC 7720. For ADPCM system, we have used an instantaneous adaptive quantizer and a first-order fixed predictor. The software for NEC 7720 has been developed and it was found that the NEC 7720 was capable of performing the entire ADPCAt algorithm for 4 channels in real time as optimizing the program. Computer simulation has born made to investigate a computational accuracr of NEC 7720 and to de-termine necessary parameters for a ADPCM codec. Real telephone speech, RC-shaped Gaussian noise and 1004 Hz tone signal were used for simulation. In simulation, the parameters werc optimized from the computed SNR and the informal listening test. The developed software was tested in real time operation using a hardware emulator for NEC 7720. It took a maximum 23.25$\mu$s to encode one sample and 113.5$\mu$s, including all the necessary 1/0 operations, to encode 4 channels. In the case of decoding process, it took 24.75$\mu$s to decode one sample and 119.5$\mu$s to decode 4 channels.