• The Journal of the Acoustical Society of Korea
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• v.20 no.5
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• pp.5-13
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• 2001

It is well known that there are two experimental errors on acoustic decay measurements. ,One is due to the influence of the band pass filter the other one is that of an averaging device. In this paper the influence of the filter is investigated in detail. To minimize the influence of the filter, the product of the filter bandwidth B (3dB bandwidth) and the reverberation time T/sub 60/ of the room under test should be at least 16. Moreover, if the initial part of an acoustic decay curve is important, the strong requirement, i. e. BT/sub 60/〉64, must be satisfied. In this paper, the wavelet filter bank instead of the band pass filter bank is applied to obtain an acoustic decay curve. As a result, the influence of filter is reduced and then the value of BT/sub 60/ required for obtaining an acceptable decay curve becomes at least 4. The strong requirement for the initial part of a decay curve is also replaced by the BT/sub 60/〉16 instead of BT/sub 60/〉64.

• Journal of Biomedical Engineering Research
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• v.19 no.3
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• pp.269-278
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• 1998

This paper describes a development of efficient stress ECG signal analysis algorithm. The algorithm consists of wavelet adaptive filter(WAF), QRS detector and ST segment detector. The WAF consists of a wavelet transform and an adaptive filter. The wavelet transform decomposed the ECG signal into seven levels using wavelet function for each high frequency bank and low frequency bank. The adaptive filter used the signal of the seventh lowest frequency band among the wavelet transformed signals as primary input. For detection of QRS complex, we made summed signals that are composed of high frequency bands including frequency component of QRS complex and applied the adaptive threshold method changing the amplitude of threshold according to RR interval. For evaluation of the performance of the WAF, we used two baseline wandering elimination filters including a standard filter and a general adaptive filter. WAF showed a better performance than compared filters in the noise elimination characteristics and signal distortion. For evaluation of WAF showed a better performance than compared filters in the noise elimination characteristics and signal distortion. For evaluation of results of QRS complex detection, we compared our algorithm with existing algorithms using MIT/BIH database. Our algorithm using summed signals showed the accuracy of 99.67% and the higher performance of QRS detection than existing algorithms. Also, we used European ST-T database and patient data to evaluate measurement of the ST segment and could measure the ST segment adaptively according to change of heart rate.

• Journal of the Semiconductor & Display Technology
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• v.9 no.4
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• pp.57-61
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• 2010

The wavelet transform was adopted as the transform for JPEG2000. However, wavelet has weakness about smoothness along the contours and limited directional information. So we use to other transform, called contourlet transform in compression. Objective quality assessment methods currently used Peak signal to noise Ratio(PSNR). But that is not very well matched to perceived visual quality. So new image quality assessment is required. In this paper, we propose a new method for image compression based on the contourlet transform, which has been recently introduced. In addition we evaluated compression image quality using PSNR and SSIM. Finally contourlet transform has a good result about images with smooth contours and SSIM is good method for image evaluation compared to PSNR.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.253-256
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• 2000

In this paper, we propose the lossless image compression algorithm using the integer wavelet transform. Recently, the S＋P transform is widely used and computed with only integer addition and bit-shift operations, but not proper to remove the correlation of smooth images. then we compare the Harr wavelet of the S＋P transform with various integer coefficient filter banks and apply 9/7 ICFB to the wavelet transform. In addition, we propose a entropy-coding method that exploits the multiresolution structure and the feedback of the prediction error, and can efficiently compress the transformed image for progressive transmission. Simulation results are compared to the compression ratio using the S+P transform with different types of images.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.130-133
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• 1999

In the view point of further reducing the inter-symbol interferences studied in our previous paper 〔1〕, a quadrature pair of wavelet-based filter banks that are composed of a pair of cosine and sine modulated filter banks is applied to MC-CDMA transmultiplexing. For that fact, the symbol duration gets twice longer than the one in , 〔1〕, the interference effects due to channel overlapping and Doppler spread can be effectively alleviated while increasing the channel utilization efficiency. Moreover, the well-known wavelet properties are exploited to design the prototype filter in such a way to maintain the size of sidelobes much smaller than those of the FFT, the interference reduction effect can be further obtained. To verify the behavior of our proposed quadrature filter bank based MC-CDMA system, the reverse-link bit error rates with respect to SNR under Rayleigh fading and additive white Gaussian noise channel environments are computed. The results show an improved system performance over the conventional MC-CDMA.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1B
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• pp.89-98
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• 2000

This paper presents an active noise cancelling model using wavelet transform and subband filter banks based on adaptive filter. The analysis filter banks decompose input and error signals into QMF filter banks of lowpass and highpass bands. Each filter bank uses wavelet filter with dyadic tree structure. The decomposed input and error signals are iterated by adaptive filter coefficients of each subband using filtered-X LMS algorithm. The synthesis filter banks make output signal of wideband with perfect reconstruction to prepare adaptive filter output signals of each subband. The analysis and synthesis niter hants use conjugate quadrature filters for Pefect reconstruction. Also, The delayed LMS algorithm model for on-line identification of error path transfer characteristics is used gain and acoustic time delay factors. The proposed adaptive active noise cancelling modelis suggested by system retaining the computational and convergence speed advantage using wavelet subband filter banks.

• Proceedings of the Acoustical Society of Korea Conference
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• 1993.06a
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• pp.113-116
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• 1993

본 논문에서는 변형된 wavelet 변환을 통해 추출한 특징벡터를 이용하여 한국어 숫자음을 대상으로 한 음성인식기를 구현하였다. wavelet 변환은 시간 및 주파수 영역에 대해 다중해상도(multiresolution)를 가지는 신호분석법이다. 본 연구에서는 계산량의 감소와 넓은 주파수 대역을 분석하기 위해, mother wavelet의 형태를 분석 주파수 대역에 따라 변화시키는 방법을 제안하였다. 기존의 wavelet 변환으로 실험한 결과 86.5%의 인식율을 얻었고, 변형된 wavelet 변환의 경우 96%의 인식율을 얻었으며 계산량이 감소하였다. 이와 함께 음성인식에서 널리 사용되는 특징 파라미터인 멜켑스트럼과 FFT 멜스케일 필터 대역(mel scale filter bank)과 비교 실험한 결과 인식율의 향상을 보였다. 이는 제안한 방법이 고주파 대역의 세밀한 시간 해상도와 저주파 대역의 세밀한 주파수 해상도를 지니는데 기인하는 것으로 판단된다.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.2
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• pp.36-40
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• 2006

Diagnosis and repair tasks of an unbalanced rigid rotor reduce the chances of unexpected failure and the consequent losses in production, time, and money. This paper presents investigation of a balancing system for equilibration of rigid rotor unbalance. A practical vibration signal based method is developed for unbalance diagnosis using wavelet technology and a Lissajous diagram. This paper shows that a mass unbalance can be efficiently estimated through an appropriate narrow-band filter used to extract the required spectra component. The wavelet technology is used to design specified narrow filter bank. A modified Lissajous diagram is also introduced with statistical analysis to compute the phase position. Several experimental tests demonstrate the effectiveness in balancing the mass unbalance of a rigid rotor.

• Journal of Ocean Engineering and Technology
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• v.28 no.6
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• pp.552-559
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• 2014

In general, the number of underwater transient signals is very limited for research on automatic recognition. Data-dependent feature extraction is one of the most effective methods in this case. Therefore, we suggest WPCC (Wavelet packet ceptsral coefficient) as a feature extraction method. A wavelet packet best tree for each data set is formed using an entropy-based cost function. Then, every terminal node of the best trees is counted to build a common wavelet best tree. It corresponds to flexible and non-uniform filter bank reflecting characteristics for the data set. A GMM (Gaussian mixture model) is used to classify five classes of underwater transient data sets. The error rate of the WPCC is compared using MFCC (Mel-frequency ceptsral coefficients). The error rates of WPCC-db20, db40, and MFCC are 0.4%, 0%, and 0.4%, respectively, when the training data consist of six out of the nine pieces of data in each class. However, WPCC-db20 and db40 show rates of 2.98% and 1.20%, respectively, while MFCC shows a rate of 7.14% when the training data consists of only three pieces. This shows that WPCC is less sensitive to the number of training data pieces than MFCC. Thus, it could be a more appropriate method for underwater transient recognition. These results may be helpful to develop an automatic recognition system for an underwater transient signal.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.5
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• pp.94-102
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• 2007

In de-noising, it is wellknown that wavelet-thresholding algorithm shows near-optimal performances in the minimax sense. However, the wavelet-thresholding algorithm is difficult in realization it on hardware, such as FPGA, because of wavelet function complexity. In this paper, we present a new do-noising technique with the binary tree structured filter bank, which is based on the signal power ratio of each subbands to the total signal power. And we realize it on FPGA. For simple realization, the filter banks are designed by Hadamard transform coefficients. The simulation and hardware experimental results show that the performance of the proposed method is similar with that of soft thresholding de-noising algorithm based on wavelets, nevertheless it is simple.