• The Journal of the Acoustical Society of Korea
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• v.21 no.1
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• pp.37-41
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• 2002

In this paper, we made shorter EDT(early decay time) of room reverberation curve using multiple-channel. The speech signal was processed inverse filtering with full-band and sub-band in the basis MINT, and then the multiple-channel adaptive filters were used LMS (Least Mean Square) and NLMS (Normalized Least Mean Square) algorithm. Experimental results, we could get 1/3 of time reduction at 20dB level in the reverberation curve using full-band NLMS when two microphones were used. Also, it is shown that the speech articulation was improved 80% from the test listeners with the speech, which was to shorten EDT by MINT in the subjective assessments using real room impulse response.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3543-3557
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• 2017

Compression is a very important technique for remotely sensed hyperspectral images. The lossless compression based on the recursive least square (RLS), which eliminates hyperspectral images' redundancy using both spatial and spectral correlations, is an extremely powerful tool for this purpose, but the relatively high computational complexity limits its application to time-critical scenarios. In order to improve the computational efficiency of the algorithm, we optimize its serial version and develop a new parallel implementation on graphics processing units (GPUs). Namely, an optimized recursive least square based on optimal number of prediction bands is introduced firstly. Then we use this approach as a case study to illustrate the advantages and potential challenges of applying GPU parallel optimization principles to the considered problem. The proposed parallel method properly exploits the low-level architecture of GPUs and has been carried out using the compute unified device architecture (CUDA). The GPU parallel implementation is compared with the serial implementation on CPU. Experimental results indicate remarkable acceleration factors and real-time performance, while retaining exactly the same bit rate with regard to the serial version of the compressor.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.2
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• pp.426-434
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• 2015

In this paper we proposed a dada-aided Doppler estimation method for underwater acoustic communication. The training sequence is non-dedicate, hence it can be designed for Doppler estimation as well as channel equalization. We assume the channel has been equalized and consider only flat-fading channel. First, based on the training symbols the theoretical received sequence is composed. Next the least square principle is applied to build the objective function, which minimizes the error between the composed and the actual received signal. Then an iterative approach is applied to solve the least square problem. The proposed approach involves an outer loop and inner loop, which resolve the channel gain and Doppler coefficient, respectively. The theoretical performance bound, i.e. the Cramer-Rao Lower Bound (CRLB) of estimation is also derived. Computer simulations results show that the proposed algorithm achieves the CRLB in medium to high SNR cases.

• Journal of Advanced Navigation Technology
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• v.28 no.2
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• pp.172-177
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• 2024

This paper presents a method to overcome the problem of increasing elevation estimation error when estimating elevation in a multipath situation with radar. A multipath situation means that radar reception signals reflected from the same target come from multiple paths. In non-multipath, the monopulse method is accurate. For the opposite case, the least square error method is accurate. In multipath situation and when the elevation angle is very low, a singular occurs where the least square error estimate diverges. This singular was identified based on the propagation factor, and monopulse and least square error estimation methods were selectively used. As a result, we succeeded in increasing the accuracy of elevation estimation. MATLAB simulations were performed to verify the method proposed in this paper.

• Proceedings of the SAREK Conference
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• 2008.11a
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• pp.393-398
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• 2008

In order to protect the environment from the refrigerant pollution, the $CO_2$ may be regarded as one of the most attractive alternative refrigerants for an automotive air-conditioning system. Control methods for a $CO_2$ system should be different because of the unique property of a $CO_2$ as a refrigerant. Especially, the high-side pressure of a $CO_2$ system should be controlled for the efficient operation. The high-side pressure algorithm being composed of the pressure setpoint algorithm and the pressure setpoint reset algorithm was developed. The pressure setpoint algorithm, by using a least square method, was developed. The pressure setpoint reset algorithm, by using a fuzzy logic and by using a proportional logic, was also developed and compared. Simulation results showed that a proportional logic was more practical than a fuzzy logic for the pressure setpoint reset algorithm.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.1
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• pp.57-67
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• 2008

In this paper, we present an adaptive block matching motion estimation using optical flow. In the proposed algorithm, we calculate the temporal and spatial gradient value for each pixel value from tile differential filter, and estimate the optical flow which is used to decide the location and the size of the search region from the gradient values by least square optical flow algorithm. In particular, the proposed algorithm showed a excellent performance with fast and complex motion sequences. From the computer simulation for various motion characteristic sequences. The proposed algorithm shows a significant enhancement of PSNR over previous blocking matching algorithms.

• Journal of KSNVE
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• v.4 no.1
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• pp.59-69
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• 1994

A new LMS algorithm titled constrained LMS' is proposed for problems with constrained structure. The conventional LMS algorithm can not be used because it destroys the constrained structures of the weights or parameters. Proposed method uses error-back propagation, which is popular in training neural networks, for error minimization. The illustrative examplesare shown to demonstrate the applicability of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.95.6-95
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• 2002

1. Introduction 2. Basic Concepts 2.1 Signal Model 2.2. Least-Mean-Square Adaptation Algorithm 3. Minimum Mean-Square Error 4. Bayesian Beamformer References

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.253-260
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• 2018

The acoustic communication channel in shallow underwater is typically shown as time-varying multipath fading channel characteristics. The received signal through channel transmission cause inter-symbol interference (ISI) owing to multiple components of different time delay and amplitude. To compensate for this, several techniques have been used, and one of them is acoustic equalizer. In this study, we used four equalizers - feed forward equalizer (FFE), decision directed equalizer (DDE), decision feedback equalizer (DFE) and combination DDE with DFE to compensate ISI. And we applied two adaptive algorithms to adjust coefficient of equalizers - normalized least mean square algorithm and recursive least square algorithm. As result, we found that it has a significant performance improvement over 6 dB on SNR in nonlinear equalizer. By combination of DFE and DDE has almost best performance in any case.

• Journal of Digital Convergence
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• v.11 no.7
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• pp.135-140
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• 2013

Noise estimation and detection algorithm to adapt quickly to changing noise environment using the LMS Filter. However, the LMS Filter for noise estimation for a certain period of time and need time to adapt. If the signal changes occur, have the disadvantage of being more adaptive time-consuming. Therefore, noise removal method is proposed to a frame basis AELMS Filter to compensate. In this paper, we split the input signal on a frame basis in noisy environments. Remove the LMS Filter by configuring noise predictions using the mean and variance. Noise, even if the environment changes fast adaptation time to remove the noise. Remove noise and environmental noise and speech input signal is mixed to maintain the unique characteristics of the voice is a way to reduce the damage of voice information. Noise removal method using a frame basis AELMS Filter To evaluate the performance of the noise removal. Experimental results, the attenuation obtained by removing the noise of the changing environment was improved by an average of 6.8dB.