• The Journal of the Acoustical Society of Korea
• /
• v.14 no.6
• /
• pp.27-31
• /
• 1995

In this paper, the determination method of available bandwidth for automation of the split-spectrum processing(SSP) has been studied. The SSP is used for the visibility enhancement of the ultrasonic signal with grain noise. Even though the SSP has proved useful in signal-to-noise ratio enhancement, its application and automation have been limited due to ambiguity in the determination of available bandwidth. Until recently, it is the usual practice to optimize the available bandwidth by trial and error. The spectral histogram is the statistical distribution of the spectral windows that is selected by the minimization algorithm with the whole band of the spectrum of the received ultrasonic signal. Since the available bandwidth can be determined adaptively using spectral histogram, this method can be used for automation of the SSP. In order to evaluate the determination technique of the available bandwidth using spectral histogram, this method is applied to experimental ultrasonic data. The experimental results show that the spectral histogram is an efficient method for determination of the available bandwidth and automation of the SSP.

• The Journal of the Acoustical Society of Korea
• /
• v.16 no.5
• /
• pp.68-75
• /
• 1997

Spectral subtraction is widely-used preprocessing technique for speech recognition in additive noise environments, but it requires a good estimate of the noise power spectrum. In this paper, we employ the histogram technique for the estimation of noise spectrum. This technique has advantages over other noise estimation methods in that it does not requires speech/non-speech detection and can estimate slowly-varying noise spectra. According to the speaker-independent isolated word recognition in both colored Gaussian and car noise environments under various SNR conditions. Histogram-technique-based spectral subtraction method yields superier performance to the one with conventional noise estimation method using the spectral average of initial frames during non-speech period.

• Journal of Broadcast Engineering
• /
• v.19 no.6
• /
• pp.967-970
• /
• 2014

An efficient peak detection algorithm in magnitude spectrum is proposed to distinguish the M-frequency shift keying(FSK) signals from other digitally modulated signal. In addition, recognition of the modulation order estimation of FSK signals is also studied based on the fact that the magnitude spectrum of FSK signals reveals the number of peaks equal to the modulation order. When no a priori information about the signals, we utilize the histogram of the magnitude spectrum to determine the threshold which is important factor in peak detection algorithm. The simulation results show high probability of classification under 500 symbols and signal-to-noise ratio(SNR) higher than 4dB.

• The Journal of the Acoustical Society of Korea
• /
• v.19 no.6
• /
• pp.53-61
• /
• 2000

In the speech recognition under the noisy environments, reducing the mismatch introduced between training and testing environments is an important issue. Spectral subtraction is widely used technique because of its simplicity and relatively good performance in noisy environments. In this paper, we introduce histogram method as a reliable noise estimation approach for spectral subtraction. This method has advantages over the conventional noise estimation methods in that it does not need to detect non-speech intervals and it can estimate the noise spectra even in time-varying noise environments. Even though spectral subtraction is performed using a reliable average noise spectrum by the histogram method, considerable amount of residual noise remains due to the variations of instantaneous noise spectrum about mean. To overcome this limitation, we propose a new over-estimation technique based on distribution characteristics of histogram used for noise estimation. Since the proposed technique decides the degree of over-estimation adaptively according to the measured noise distribution, it has advantages to be few the influence of the SNR variation on the noise levels. According to speaker-independent isolated word recognition experiments in car noise environment under various SNR conditions, the proposed histogram-based over-estimation technique outperforms the conventional over-estimation technique.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.12 no.1
• /
• pp.88-97
• /
• 2013

Most of the traditional spectrum sensing methods consider only the current detected data sets of Primary User (PU). However previous state of PU is a kind of conditional probability that strengthens the reliability of the detector. Therefore, in the cross entropy spectrum sensing method, relationship of the previous and current spectrum sensing is considered to detect PU signal more effectively. But these cross entropy spectrum sensing methods only consider the ideal system. In other words, PU always occupy the channel during the same period. However, PU can occupy the channel either for a longer or a shorter period than the ideal case in the real system. For this reason, the spectrum sensing performance can be varied. In this paper, we propose the method that can maintain the performance of spectrum sensing in the real system and we confirm the results with the help of simulation.

• Proceedings of the IEEK Conference
• /
• 2003.07d
• /
• pp.1533-1536
• /
• 2003

In this paper, instead of conventional color management method that using spectrum analysis, a simplified color management scheme is proposed that is low-cost required method to reproduce the visual color perception of human. Proposed scheme uses computer color scanner to obtain a bit map image from dyed original color sample, and conducts pixel analysis by image histogram. From obtained image histogram, extract the color and RGB value from histogram that shows dominant pixel distribution of the sample image.

• Proceedings of the IEEK Conference
• /
• 2002.07b
• /
• pp.818-821
• /
• 2002

In this paper, we propose Neuro-Fuzzy discrimination method of the new and old bill using bill money acoustic data. The concept of the histogram is introduced to improve the processing time into the proposal system. The adaptative filter is used in order to remove the motor sound from an observed bill money acoustic data. The output signal of this adaptive digital filter is converted into not only a spectrum but also a histogram. It became easy that features of the paper money sound were extracted from the bill money acoustic data. The spectral data and the histogram is obtained like this, and it become an input pattern of the neural network(NN). Then, the discrimination result of the NN is finally judged by the fuzzy inferece in the new bill or the exhaustion bill.

• Journal of IKEEE
• /
• v.5 no.2 s.9
• /
• pp.190-200
• /
• 2001

This paper is addressed to welding defect feature vector selection and implementation method of welding defect classifier using fuzzy techniques. We compare IAV, zero-crossing number as time domain analysis, power spectrum coefficient as frequency domain, histogram as both domain for welding defect feature selection. We choose histogram as feature vector by graph analysis and find out that maximum frequent occurrence number and section of corresponding signal scale in relative histogram show obvious difference between normal welding and voiding with penetration depth defect. We implement a fuzzy welding defect classifier using these feature vector, test it to verify its effectiveness for 695 welding data frame which consist of 4000 sampled data. As result of test, correct classification rate is 92.96%. Lab experimental results show a effectiveness of fuzzy welding defect classifier using relative histogram for practical Laser welding monitoring system in industry.

• Proceedings of the IEEK Conference
• /
• 2002.06d
• /
• pp.93-96
• /
• 2002

This paper presents robust and efficient scene-based video watermarking method using visual rhythm (spatio-temporal slice) in compressed domain. Scene change can be detected easily using visual rhythm and video sequences are conveniently edited at the scene boundaries. Therefore, scene-based watermark embedding Process it a natural choice. Temporal spread spectrum can be achieved by applying spread spectrum methods to visual rhythm. Additive Gaussian noise, low-pass filtering, median filtering and histogram equalization attack are simulated for all frames. Frame sub-sampling is also simulated as a typical video attack Simulation results show that proposed algorithm is robust and efficient in the presence of such kind of attacks.

• Structural Engineering and Mechanics
• /
• v.17 no.5
• /
• pp.655-670
• /
• 2004

This paper aims to evaluate the effect of typhoons on fatigue damage accumulation in steel decks of long-span suspension bridges. The strain-time histories at critical locations of deck sections of long-span bridges during different typhoons passing the bridge area are investigated by using on-line strain data acquired from the structural health monitoring system installed on the bridge. The fatigue damage models based on Miner's Law and Continuum Damage Mechanics (CDM) are applied to calculate the increment of fatigue damage due to the action of a typhoon. Accumulated fatigue damage during the typhoon is also calculated and compared between Miner's Law and the CDM method. It is found that for the Tsing Ma Bridge case, the stress spectrum generated by a typhoon is significantly different than that generated by normal traffic and its histogram shapes can be described approximately as a Rayleigh distribution. The influence of typhoon loading on accumulative fatigue damage is more significant than that due to normal traffic loading. The increment of fatigue damage generated by hourly stress spectrum for the maximum typhoon loading may be much greater than those for normal traffic loading. It is, therefore, concluded that it is necessary to evaluate typhoon induced fatigue damage for the purpose of accurately evaluating accumulative fatigue damage for long-span bridges located within typhoon prone regions.