• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.321-324
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• 1997

In this paper, Active Noise Control(ANC) algorithm is proposed based on the estimated frequency estimator of the reference signal. The conventional feedforward ANC algorithms should measure the reference and use it to calculate the gradient of the squared error and filter coefficients. For ANC systems applied to aircrafts and passenger ships, engines from which reference signal is usually measured is so far from seats where main part of controller is placed that the scheme might be difficult to implement or very costly. Feedback ANC algorithm which doesn't need to measure the reference uses the error signal to update the filter and is sensitive to unexpected transient noise like a sneeze, clapping of hands and so on The proposed algorithm estimates frequencies of the desired signal in real time using adaptive notch filter. New frequency estimation algorithm is proposed with the improved convergence rate, threshold SNR and computational simplicity. Reference is not measured but created with the estimated frequencies. It has strong similarity to the conventional feedback control because reference is made from error signal. Enhanced error signal is used to update the controller for better performance under the measurement noise and impact noise. The proposed ANC algorithm is compared with the conventional feedback control.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.649-664
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• 2011

Cooperative spectrum sensing (CSS) with decision fusion is considered as a key technology for tackling the challenges caused by fading/shadowing effects and noise uncertainty in spectrum sensing in cognitive radio. However, most existing solutions assume an error-free decision transmission, which is obviously not the case in realistic scenarios. This paper extends the general decision-fusion-based CSS scheme by considering the fading/shadowing effects and noise corruption in the common control channels. With this more practical model, the fusion centre first estimates the local decisions using a binary minimum error probability detector, and then combines them to get the final result. Theoretical analysis and simulation of this CSS scheme are performed over typical channels, which suggest some performance deterioration compared with the pure case that assumes an error-free decision transmission. Furthermore, the fusion strategy optimization in the proposed cooperation model is also investigated using the Bayesian criteria. The numerical results show that the total error rate of noisy CSS is higher than that of the pure case, and the optimal values of fusion parameter in the counting rule under both cases decrease as the local detection threshold increases.

• Journal of Korea Multimedia Society
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• v.7 no.2
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• pp.164-172
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• 2004

Halftoning of gray-scale image is a process to produce a binary image. The error diffusion halftoning method produces high qualify binary image but that has some defects such as sharpening and directional artifacts. We propose the threshold modulation to reduce such defects. The proposed algorithm uses thresholds reflecting local characteristic of image. We calculate thresholds which minimize errors of flat region of each gray-scale level by using a linear gain between original image and error-diffused image and then represent edge by compensating thresholds in proportion to edge information. The proposed method improves on halftone quality by minimizing an error which cause sharpening and directional artifact.

• The Journal of the Korea Contents Association
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• v.9 no.7
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• pp.141-148
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• 2009

Recently there have been many research efforts focused on imbalanced data classification problems, since they are pervasive but hard to be solved. Approaches to the imbalanced data problems can be categorized into data level approach using re-sampling, algorithmic level one using cost functions, and ensembles of basic classifiers for performance improvement. As an algorithmic level approach, this paper proposes to use multilayer perceptrons with higher-order error functions. The error functions intensify the training of minority class patterns and weaken the training of majority class patterns. Mammography and thyroid data-sets are used to verify the superiority of the proposed method over the other methods such as mean-squared error, two-phase, and threshold moving methods.

• Journal of Wind Energy
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• v.15 no.2
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• pp.10-22
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• 2024

This research is a comprehensive analysis of wind power prediction sensitivity using a Long Short-Term Memory (LSTM) deep learning neural network model, accounting for the inherent uncertainties in wind speed estimation. Utilizing a year's worth of operational data from an operational wind farm, the study forecasts the power output of both individual wind turbines and the farm collectively. Predictions were made daily at intervals of 10 minutes and 1 hour over a span of three months. The model's forecast accuracy was evaluated by comparing the root mean square error (RMSE), normalized RMSE (NRMSE), and correlation coefficients with actual power output data. Moreover, the research investigated how inaccuracies in wind speed inputs affect the power prediction sensitivity of the model. By simulating wind speed errors within a normal distribution range of 1% to 15%, the study analyzed their influence on the accuracy of power predictions. This investigation provided insights into the required wind speed prediction error rate to achieve an 8% power prediction error threshold, meeting the incentive standards for forecasting systems in renewable energy generation.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.9
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• pp.39-48
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• 2004

Turbo codes, whose performance in bit error rate is close to the Shannon limit, have been adopted as a part of standard for the third-generation high-speed wireless data services. Iterative Turbo decoding results in decoding delay and high power consumption. As wireless communication systems can only use limited power supply, low power design techniques are essential for mobile device implementation. This paper proposes new effective criteria for stopping the iteration process in turbo decoding to reduce power consumption. By setting two stopping criteria, decodable threshold and undecodable threshold, we can effectively reduce the number of decoding iterations with only negligible error-correcting performance degradation. Simulation results show that the number of unsuccessful error-correction can be reduced by 89% and the number of decoding iterations can be reduced by 29% on the average among 12500 simulations when compared with those of an existing typical method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.4
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• pp.1-10
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• 2000

The error diffusion technique is frequently utilized for the digital Imaging output devices to convert continuous level Image into bi-level Image It Yields the binary image with the high frequency emphasis that gives a pleasing perception to human eyes But, due to the non-homogeneous distribution of dots, It exhibits undesirable patterns that degenerate the perceived quality Various techniques have been proposed to Improve the Image quality by the error diffusion techniques In this paper, the cause of non-homogeneity of dot distribution is analyzed first. A threshold modulation technique that employs a simple sinusoidal function is proposed in this paper The proposed method achieves the homogeneous dot distribution by forcing the minor pixels on the binary Image to maintain the principal distance defined according to their gray levels. It also minimizes the void and clusters of minor pixels.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7C
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• pp.618-627
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• 2010

In this paper, we propose an adaptive K-best algorithm in which the number K of candidates is changed according to the differences of level radii. We also compare the bit error performance and complexity of the proposed algorithm with those of several conventional K-best algorithms, where the complexity is defined as the total number of candidates of which partial Euclidean distances have to be calculated. The proposed algorithm adaptively decides K at each level by eliminating the symbols, whose differences of radii are larger than a threshold, from the set of candidates, and the maximum or average value of differences can be adopted as the threshold. The proposed decoding algorithm shows the better bit error performance and the lower complexity than a conventional K-best decoding algorithm with a constant K, and also has a similar bit error performance and the lower complexity than other adaptive K-best algorithms.

• Journal of the Korea Computer Graphics Society
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• v.25 no.2
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• pp.19-29
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• 2019

We develop a complete system that includes data collection, signal processing, and real-time interaction for effective neurofeedback training. Our system supports a sophisticated technique to find threshold values which are quite important for effective neurofeedback system. A therapist specifies a target success rate of positive feedback, allowable error and time. The system computes a current success rate and compare it with the target one. If the difference between two rates exceeds the allowable error for allowable time, we find an optimum threshold value to obtain the target success rate by using numerical optimization technique. We conduct several experiments by varying input parameters: target success rate, allowable error and time, and demonstrate the effectiveness of our technique by showing the desired target success rate is stably obtained and systematically controlled by input parameters.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.3
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• pp.42-48
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• 2002

Multiple description coding Is source coding for multiple channels such that a decoder which receives an arbitrary subset of the channels may produce a useful reconstruction. This paper presents an efficient multiple description coder using a newly designed EZW coding method. We first propose EZW coder which has expanded threshold and two subordinate passes. And then we present multiple description coder which has two coding channels using the proposed EZW coders. To evaluate the performance of the proposed coder, we provide an image coding applications with two descriptions and compare multiple description image coding results reported to date. Simulation results show that the proposed method has a better performance than the polyphase transform method.