• Journal of Multimedia Information System
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• v.9 no.3
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• pp.233-244
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• 2022

A MATLAB program was developed to calculate the half-wavelength of a sine-curve baseband signal with white noise by using an autocorrelation function, a SG filter, and zero-crossing detection. The frequency of the input signal can be estimated from 1) the first zero-crossing (corresponding to ¼λ) and 2) the R value (the Y axis of the correlogram) at the center of the segment. Thereby, the frequency information of the preceding segment can be obtained. If the segment size were optimized, and a portion with a large zero-crossing dynamic range were obtained, the frequency discrimination ability would improve. Furthermore, if the values of the correlogram for each frequency prepared on the CPU side were prepared in a table, the volume of calculations can be reduced by 98%. As background, period detection by autocorrelation coefficients requires an integer multiple of 1/2λ (when using a sine wave as the object of the autocorrelation function), otherwise the correlogram drawn by R value will not exhibit orthogonality. Therefore, it has not been used in bio-telemetry where the frequencies move around.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.5
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• pp.100-108
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• 2010

An autocorrelation method is used in pitch estimation. Autocorrelation values in time and frequency domains, which have different characteristics, correspond to the pitch period and fundamental frequency, respectively. We utilize an integrated autocorrelation method in time and frequency domains. It can remove the errors of pitch doubling and having. In the time and frequency domains, pitch period and fundamental frequency have reciprocal relation to each other. Especially, fundamental frequency estimation ends up as an error because of the resolution of FFT. To reduce these artifacts, interpolation methods are applied in the integrated autocorrelation domain, which decreases pitch errors. Moreover, only for the pitch candidates found in a time domain, the corresponding frequency-domain autocorrelation values are calculated with reduced computational complexity. Using linear interpolation, we can decrease the required number of FFT coefficients by 8 times. Thus, compared to the conventional methods, computational complexity can be reduced by 9.5 times.

• Journal of applied mathematics & informatics
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• v.4 no.1
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• pp.39-46
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• 1997

Given to be the $m^{th}$ correlation coefficient of the Rudin-Shapiro polynomials of degrees $2^n-1$, $$\mid$a_m$\mid$ \leq C(2^n)^{\frac{3}{4}}$ and there exists $\kappa \neq 0$ such that $$\mid$a_{\kappa}$\mid$ ＞D(2^n)^{0.73}$ (C and D are universal constants). Here we show that the 0.73 is optimal in the upper vound case.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.521-525
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• 1996

An attempt is made to characterize and synthesize engineered surfaces. The proposed method is not only an analytical tool to characterize but alsoto generate/synthesize three-dimensional surfaces. The developed method expresses important engineered surface characteristics such as the autocorrelation or pwoer spectrum density functions in terms of the two-dimensional autoregressive coefficients.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.190-194
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• 2008

This paper presents a speaker identification technique which is one of the basic techniques of the ubiquitous robot companion. Though the conventional mel-frequency cepstral coefficients guarantee high performance of speaker identification in clean condition, the performance is degraded dramatically in noise condition. To overcome this problem, we employed the relative autocorrelation sequence mel-frequency cepstral coefficient which is one of the noise robust features. However, there are two problems in relative autocorrelation sequence mel-frequency cepstral coefficient: 1) the limited information problem. 2) the residual noise problem. In this paper, to deal with these drawbacks, we propose a multi-streaming method for the limited information problem and a hybrid method for the residual noise problem. To evaluate proposed methods, noisy speech is used in which air conditioner noise, classic music, and vacuum noise are artificially added. Through experiments, proposed methods provide better performance of speaker identification than the conventional methods.

• The Journal of Natural Sciences
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• v.7
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• pp.75-82
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• 1995

We obtain the departure process of a D-BMAP/Geo/1/K queue. We also study the burstiness and correlation of the departure process. We have observed that the autocorrelation coefficients of the interdeparture time(correlogram) of the departure process may oscillated.

• Journal of Biomedical Engineering Research
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• v.10 no.1
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• pp.11-16
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• 1989

This paper describes the AR model of EMG signal during maximum voluntary contraction. By comparing the AR coefficients and the reflection coefficients of the AR model with the median frequency of power spectrum, it is proved that muscle fatigue can be measured by the AR and the reflection coefficients. In the estimation procedure of AR model parameter, the autocorrelation method is superior to the covariance method, and it is determined that the optimal order is six. As the muscle becomes fatigue, the median frequency of power spectrum is declined, and the AR coefficient [$a_1$] and the reflection coefficient [$k_1$] are also decreased. Therefore the muscle fatigue can be measured by the AR parameter.

• Geophysics and Geophysical Exploration
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• v.12 no.1
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• pp.121-131
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• 2009

In recent years, microtremor array observations have been used for estimation of shear-wave velocity structures. One of the methods is the conventional spatial autocorrelation (SPAC) method, which requires simultaneous recording at least with three or four sensors. Modified SPAC methods such as 2sSPAC, and linear array methods, allow estimating shear-wave structures by using only two sensors, but suffer from instability of the spatial autocorrelation coefficient for frequency ranges higher than 1.0 Hz. Based on microtremor measurements from four different size triangular arrays and four same-size triangular and linear arrays, we have demonstrated the stability of SPAC coefficient for the frequency range from 2 to 4 or 5 Hz. The phase velocities, obtained by fitting the SPAC coefficients to the Bessel function, are also consistent up to the frequency 5 Hz. All data were processed by the SPAC method, with the exception of the spatial averaging for the linear array cases. The arrays were deployed sequentially at different times, near a site having existing Parallel Seismic (PS) borehole logging data. We also used the imaginary part of the SPAC coefficients as a data-quality indicator. Based on perturbations of the autocorrelation spectrum (and in some cases on visual examination of the record waveforms) we divided data into so-called 'reliable' and 'unreliable' categories. We then calculated the imaginary part of the SPAC spectrum for 'reliable', 'unreliable', and complete (i.e. 'reliable' and 'unreliable' datasets combined) datasets for each array, and compared the results. In the case of insufficient azimuthal distribution of the stations (the linear array) the imaginary curve shows some instability and can therefore be regarded as an indicator of insufficient spatial averaging. However, in the case of low coherency of the wavefield the imaginary curve does not show any significant instability.

• Journal of Biomedical Engineering Research
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• v.20 no.4
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• pp.471-477
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• 1999

Many researches have been performed whether electrical stimulation could be used for diagnosis and treatment on the auditory system impairment. Unfortunately, there were no standard methods or theoretical background for choosing stimulus conditions because of the lack of understanding on the transmission of electrical stimulation through the auditory pathway. This research was conducted to observe the effect of electrical stimulation on the tinnitus-induced animals. Nine guniea pigs were used for the experment and divided into two groups, five animals for the experimental group(A) and four animals for the control group(B). Experimental conditions were divided into four steps, before tinnitus induction and 1, 6, 12 hours after tinnitus induction using salicylate based on the Jastreboff model. In each experimental condition, ABR and ECochG were obtained, and autocorrelation coefficients were calculated from normalized waveforms based on rms values. Sum of all the autocorrelation coefficients was extracted as a parameter to observe the changes between before and after the electrical stimulation. As a result, ABR parameter values were rapidly increased 6 hours after tinnitus induction, the gradually returned back to the initial state. On the other hand, when electrical stimulation was applied, parameter values did not change compared with the initial sate. Parameter values of ECochG showed that the effect of electrical stimulation appeared 12 hours after the tinnitus induction. It was concluded that an electrical stimulation to the tinnitus-induced model changes the correlation coefficients of ABR and ECochG waveforms.

• Journal of the Korea Society of Computer and Information
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• v.16 no.12
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• pp.187-196
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• 2011

Induction motors play a vital role in aeronautical and automotive industries so that many researchers have studied on developing a fault detection and classification system of an induction motor to minimize economical damage caused by its fault. With this reason, this paper extracts robust feature vectors from the normal/abnormal vibration signals of the induction motor in noise circumstance: partial autocorrelation (PARCOR) coefficient, log spectrum powers (LSP), cepstrum coefficients mean (CCM), and mel-frequency cepstrum coefficient (MFCC). Then, we classified different types of faults of the induction motor by using the extracted feature vectors as inputs of a neural network. To find optimal feature vectors, this paper evaluated classification performance with 2 to 20 different feature vectors. Experimental results showed that five to six features were good enough to give almost 100% classification accuracy except features by CCM. Furthermore, we considered that vibration signals could include noise components caused by surroundings. Thus, we added white Gaussian noise to original vibration signals, and then evaluated classification performance. The evaluation results yielded that LSP was the most robust in noise circumstance, then PARCOR and MFCC followed by LSP, respectively.