• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.6
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• pp.249-254
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• 2006

A new algorithm for estimating power frequency is presented. Unlike conventional algorithms, the proposed algorithm is based on the fact that the magnitude gains of cosine and sine filters become different when the power frequency is deviated from the nominal value. This makes the algorithm capable of providing an accurate and fast estimate of the power frequency. To demonstrate the performance of the developed algorithm, various computer simulated data records are processed. The algorithm showed a high level of robustness as well as high measurement accuracy over a wide range of frequency changes. Moreover, the algorithm was highly immune to harmonics and noise.

• The Journal of the Acoustical Society of Korea
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• v.30 no.3
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• pp.123-128
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• 2011

In this paper, we propose the improved noise power estimation in speech enhancement under various noise environments. The previous MS algorithm tracking the minimum value of finite search window uses the optimal power spectrum of signal for smoothing and adopts minimum probability. From the investigation of the previous MS-based methods it can be seen that a fixed size of the minimum search window is assumed regardless of the various environment. To achieve the different search window size, we use the noise classification algorithm based on the Gaussian mixture model (GMM). Performance of the proposed enhancement algorithm is evaluated by ITU-T P.862 perceptual evaluation of speech quality (PESQ) under various noise environments. Based on this, we show that the proposed algorithm yields better result compared to the conventional MS method.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.2
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• pp.188-194
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• 2014

Recently, indoor localization systems based on wireless sensor networks have received a great deal of attention because they help achieve high accuracy in position determination by using various algorithms. In order to minimize the error in the estimated azimuth that can occur owing to sensor drift and recursive calculation in these algorithms, we propose a novel relative azimuth estimation algorithm. The advantages of the proposed technique in an indoor environment are that an improved weight average filter is used to effectively reduce impulse noise from the raw data acquired from nodes with inherent errors and a rotational displacement algorithm is applied to obtain a precise relative azimuth without using additional sensors, which can be affected by electromagnetic noise. Results from simulations show that the proposed filter reduces the impulse noise, and the acquired estimation error does not accumulate with time by using proposed algorithm.

• Journal of Broadcast Engineering
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• v.6 no.1
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• pp.72-81
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• 2001

An adaptive channel estimation technique for OFDM-based DTV receivers is proposed using a new mobility estimator. Sample mean techniques for channel estimation have displayed good performance in slow fading channels, because averaging reduces noise In channel estimation operation. This paper suggests an algorithm which selects the optimal number of symbols within which the sample mean of consecutive pilot data can be obtained. The designed mobility estimator determines the optimal number by comparing mobility variance and estimated noise valiance. The algorithm using the mobility estimator obtains an optimal channel function under time-invariant or time-variant multipath fading channels, thereby making the best BER performance.

• ETRI Journal
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• v.25 no.1
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• pp.49-51
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• 2003

Pitch estimation is important in various speech research areas, but when the speech is noisy, accurate pitch estimation with conventional pitch detectors is almost impossible. To solve this problem, we propose a new pitch detection algorithm for noisy speech using a noise whitening technique on the background noise and obtain successful results.

• Journal of Broadcast Engineering
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• v.10 no.2
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• pp.166-173
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• 2005

In this paper, we propose a mobile channel estimation algorithm using matching pursuit algorithm for orthogonal frequency division multiplexing (OFDM) systems. Least square (LS) algorithm, which is used as a conventional channel estimation algorithm for OFDM systems, has error probability of channel estimation affected by effects of noise. By estimating the channel of sparse type, the proposed algorithm reduces effects of noise during time intervals that multi-path signal doesn't exist. The proposed algorithm estimates a mobile receivingchannel using pilot information transmitted consequently. We compare performance of the proposed algorithm with the LS algorithm by measuring symbol error rate with 64QAM under a mobile multi-path fading channel model.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.1
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• pp.74-81
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• 2001

The sensorless scheme for Switched Reluctance Motor(SRM) drives must have the robustness and reliability because the noise and error are sensitive. These elements make electrically noisy environments due to the proximity of high current power circuits with small signal electronic circuits when SRM drives. Also, due to the leakage inductances and finite coupling capacitances, these can cause the noise on any low voltage current and voltage measurement circuit. The position estimate error occurs because the current and voltage including the noise are sued as the inputs of sensorless algorithm. In this paper the high robustness and resistance of input noise re described. The fuzzy logic based rotor estimation algorithm and the observer model are used to reduce the tolerance of input data.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.1
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• pp.30-37
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• 2011

In this paper, we propose a fast ICI suppression algorithm with adaptive channel estimation for the LTE-Advanced uplink system. In order to effectively remove phase noise and carrier frequency offset at time varying channel, we use the comb type pilot. The purpose is to improve performance by reducing computational complexity than conventional PNFS(Phase Noise & Frequency offset Suppression) algorithm. We reduce computational complexity by decreasing overlapping computation or unnecessary computation at conventional PNFS algorithm. Also, we propose an effective channel estimation method. We estimate and compensate multipath channel through the proposed adaptive channel estimation method. The BER performance of the proposed method is better about 0.5 dB than the conventional method at the Vehicular A channel.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.101.6-101
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• 2001

This paper deals with inspect algorithm using visual system. One of the major problems that arise during polymer production is the estimation of the noise of the product(bad pallets). An erroneous output can cause a lot of losses (production and financial losses). Therefore new methods for real-time inspection of the noise are demanded. For this reason, we have presented a development of vision system algorithm for the defect inspection of PE pallets. First of all, in order to detect the edge of object, the differential filter is used. And we apply to the labeling algorithm for feature extraction. This algorithm is designed for the defect inspection of pallets ...

• Journal of KSNVE
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• v.8 no.6
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• pp.1037-1042
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• 1998

This paper discusses the dependence of the convergence rate on the acoustic error path in these popular algorithms and introduces new algorithms which increase the convergence region regardless of the time-delay in the acoustic error path. We also Propose a novel control algorithm (AFC/CAFC) for tonal noise cancellation. The proposed algorithm estimates the magnitude and phase of the tonal noise. The algorithm uses the steepest descent method for the phase/magnitude estimation. Performances of tile CAFC algorithm are presented in comparison with those by the AFC algorithm based on computer simulations and experiments.