• Journal of the Institute of Electronics Engineers of Korea TC
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• v.38 no.11
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• pp.30-40
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• 2001

In this paper, we propose a dynamic slot allocation algorithm for efficient transmission of VBR services in wireless ATM networks. The proposed algorithm is based on a hybrid dynamic parameter(DP) control which combines the strength of in-band control and out-of-band control by considering the variation characteristics of buffer length in distributed mobile terminals. This algorithm consists of four sub-algorithms: dynamic parameter determination algorithm, dynamic parameter transmission algorithm, estimation algorithm of the number of request slots, and prorated-allocation algorithm. As the proposed allocation algorithm based on the hybrid DP control scheme can offer nearly precise MAC level estimations of the requirements for each VBR, the algorithm makes it possible to obtain ideal allocation efficiency. The allocation efficiency of the algorithm is shown by numerical analysis. Simulation results show that the proposed algorithm has better performance than conventional schemes in terms of allocation efficiency, delay and cell loss ratio under VBR traffic.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06c
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• pp.357-360
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• 1998

DS/CDMA system rejected narrow-band interference and additional White Gaussian noise which are occured at multipath, intentional jammer and multiuser to share same bandwidth in mobile communication systems. Because of having not sufficiently obtained processing gain which is related to system performance, they were not effectively suppressed. In this paper, an matched filter channel model using backpropagation neural network based on complex multilayer perceptron is presented for suppressing interference of narrow-band of direct sequence spread spectrum receiver in DS/CDMA mobile communication systems. Recursive least square backpropagation algorithm with backpropagation error is used for fast convergence and better performance in matched filter receiver scheme. According to signal noise ratio and transmission power ratio, computer simulation results show that bit error ratio of matched filter using backpropagation neural network improved than that of RAKE receiver of direct sequence spread spectrum considering of con-channel and narrow-band interference.

• Management & Information Systems Review
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• v.3
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• pp.201-214
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• 1999

Adaptive correlator receiver with neural network based on complex multilayer perceptron is persented for suppressing interference of narrow-band of direct spread spectrum communication systems. Recursive least square algorithm with backpropagation error is used for fast convergence and better performance in adaptive correlator scheme. According to signal noise and transmission power, computer simulation results show that bit error ratio of adaptive correlator using neural network improved that of adative transversal filter of direct sequence spread spectrum considering of jamming and narrow-band interference. Bit error ratio of adaptive correlator with neural network is reduced about 10-1 than that of adaptive transversal filter where interference versus signal ratio is 5dB.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.9C
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• pp.1316-1322
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• 2004

Recently, the UWB (ultra wide-band) wireless communication technology, which provides high data transmission and is capable of linearly trading between throughput and signal-to-noise ratio (SNR), has drawn much attention for short-range wireless networks. Fully exploiting its notable features and minimizing its interference to coexisting other systems require the knowledge of SNR's at receivers In this paper, we propose an algorithm for estimating the pulse energy to noise ratio Ep/No of UWB signal with utilization of outputs from a correlator at a receiver, and evaluate the performance of the proposed algorithm through computer simulation. According to simulation results, the maximum standard deviation is about 1 13 dB with a block size of 500. Except for Ep/No=O and 2 dB cases with a block size of 500, no errors greater than 3 dB were observed in all the remaining experiments. Generally speaking, it improves as the true Ep/No, increases and as the block size increases A notable feature of the proposed algorithm is that it does not reduce the effective throughput because the estimation process does not require sending additional training signal of any specific format.

• Korean Journal of Remote Sensing
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• v.22 no.4
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• pp.275-284
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• 2006

The noise sources of a Hyperion image are mainly due to the atmospheric effects, the sensor's instrumental errors, and A/D conversion. Though uncalibrated, overlapping, and all deep water absorption bands generally are removed, there still exist noisy bands. The visual inspection for selecting clean and stable processing bands is a simple practice, but is a manual, inefficient, and subjective process. In this paper, we propose that the extrema ratio be used for noise estimation and unsupervised band selection. The extrema ratio was compared with existing SNR and entropy measures. First, Gaussian, salt and pepper, and Speckle noises were added to ALI (Advanced Land Imager) images with relatively low noises, and the relation of noise level and those measures was explored. Second, the unsupervised band selection was performed through the EM (Expectation-Maximization) algorithm of the measures which were extracted from a Hyperion images. The Hyperion data were classified into 5 categories according to the image quality by visual inspection, and used as the reference data. The experimental result showed that the extrema ratio could be used effectively for band selection of Hyperion images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.5
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• pp.1172-1179
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• 1996

General adaptive noise canceller(ANC) suffers from the misadjustment of adaptive filter weights, because of the gradient-estimate noise at steady state. In this paper, an adaptive noise cancellation algorithm with speech detector which is distinguishing speech from silence and adaptation-transient region is proposed. The speech detector uses property of adaptive prediction-error filter which can filter the highly correlated speech. To detect speech region, estimation error which is the output of the adaptive filter is applied to the adaptive prediction-error filter. When speech signal apears at the input of the adaptive prediction-error filter. The ratio of input and output energy of adaptive prediction-error filter becomes relatively lower. The ratio becomes large when the white noise appears at the input. So the region of speech is detected by the ratio. Sign algorithm is applied at speech region to prevent the weights from perturbing by output speech of ANC. As results of computer simulation, the proposed algorithm improves segmental SNR and SNR up to about 4 dBand 11 dB, respectively.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.6
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• pp.60-69
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• 2000

In this paper we propose a new two-color signal processing algorithm for efficient target tracking under complicated condition including interfernces such as background noises and countermeasures. For the efficient target tracking, we adopt two detection bands, and define the ratio between two band signals which represents the spectral distribution characteristics of a target or interference. The proposed algorithm detects the ratio of interference, and extracts only the target signal from the target and the interference mixed signal by using it. To evaluate the performance of the proposed algorithm, we apply it to a rosette tracker and perform various simulations. The simulation results show that the proposed algorithm extracts the target signal from the mixed signal well. The proposed algorithm is also ready to be applied to a real system since it is simple and adaptive for environment change.

• Journal of the Korean earth science society
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• v.40 no.4
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• pp.315-328
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• 2019

Since the Coastal Zone Color Scanner (CZCS)/Nimbus-7 was launched in 1978, a variety of studies have been conducted to retrieve ocean color variables from multi-satellites. Several algorithms and formulations have been suggested for estimating ocean color variables based on multi band data at different wavelengths. Chlorophyll-a (chl-a) concentration is one of the most important variables to understand low-level ecosystem in the ocean. To retrieve chl-a concentrations from the satellite observations, an appropriate algorithm depending on water properties is required for each satellite sensor. Most operational empirical algorithms in the global ocean have been developed based on the band-ratio approach, which has the disadvantage of being more adapted to the open ocean than to coastal areas. Alternative algorithms, including the semi-analytical approach, may complement the limits of band-ratio algorithms. As more sensors are planned by various space agencies to monitor the ocean surface, it is expected that continuous monitoring of oceanic ecosystems and environments should be conducted to contribute to the understanding of the oceanic biosphere and the impact of climate change. This study presents an overview of the past and present algorithms for the estimation of chl-a concentration based on multi-satellite data and also presents the prospects for ongoing and upcoming ocean color satellites.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.49-52
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• 2000

This paper is to propose an algorithm to reduce the calculation time to perform the 2-dimensional Discrete Wavelet Transform(2DWT). We call this algorithm as Reduced 2-dimensional Discrete Wavelet Transformation(R2DWT). This algorithm uses a modified Mallat-tree such that in each level, the column transform is performed only with the low-pass filtered row transform result. The resulting number of sub-band regions is 2L＋1, meanwhile the original(2DWT) has 3L＋1 sub-regions, where L is the transform level. To show the proposed algorithm is useful without much loss in SNR(Signal-to-Noise Ratio), we performed experiments with various images. The results showed that above 5:1 in compression ratio, the proposed algorithm has less than 0.SdB difference in SNR from 2DWT with about 25% reduction in calculation time.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.193-198
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• 2006

Among 242 Hyperion bands, there are 46 bands that contain completely no information and some other bands with various kinds of noise. It is mainly due to the atmosphenc absorption and the low signal-to-noise ratio. The visual inspection for selecting clean and stable bands is a simple practice, but is a manual, inefficient, and subjective Process. Though uncalibrated, overlapping, and all deep water absorption bands are removed, there still exist noisy bands. In this paper, we propose that the extrema ratio be measured for noise estimation and the unsupervised band selection be performed using the Expectation-Maximization algorithm. The Hyperion data were classified into 5 categories according to the image quality by visual inspection, and used as the reference data. The accuracy of the proposed method was compared with signal-to-noise ranking and entropy ranking. As a result, the proposed mettled was effective as preprocessing step for band selection.