http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
정의봉,안세진,장호엽,장진혁 한국소음진동공학회 2001 한국소음진동공학회 논문집 Vol.11 No.3
An exact spectrum with no leakage error could be obtained when the period of the signal coincides perfectly with the record length. However, the record length will be determined regardless of the period of signal. The Leakage error due to this problem will give a distorted spectrum. In the conventional research, the method was proposed to estimate the three parameters, frequency, amplitude and phase angle, from the spectrum data for an undamped sinusoidal signal. In this paper, some techniques are proposed to estimate frequency, amplitude and damping ratios from the frequency response functions for damped signals. The validation of the proposed techniques is verified by several numerical examples.
정의봉,김봉준,김재호 한국마린엔지니어링학회 2000 한국마린엔지니어링학회지 Vol.24 No.2
Gas pulsation discharged from the cylinder causes noise in the rotary compressor. Mufflers are usually used to reduce the noise generated by the gas pulsation. The muffler has been designed to maximize the acoustic transmission loss of the muffler. The gas which went through muffler is discharged to the cavity in compressor. Thus, the acoustic characteristics of cavity should be taken into account in muffler design. In this paper, the program for the acoustic substructure synthesis method is developed. This program can be interfaced with SYSNOISE which is commercial acoustic package. Several types of mufflers designed to have the better acoustic performance are suggested in this work and compared with the existing commerical muffler in the compressor. The acoustic performance of mufflers taking into consideration of the cavity in the compressor is also carried out by the developed program.
FSVQ, 퍼지 개념 및 이중 스펙트럼 특징을 이용한 HMM에 기초를 둔 음성 인식
정의봉 한국컴퓨터산업학회 2004 컴퓨터産業敎育學會論文誌 Vol.5 No.4
본 논문은 화자 독립의 단독어 인식에 관한 연구로써, FSVQ(first section vector quantization), 퍼지 이론 및 이중 스펙트럼 특징을 이용한 HMM(hidden Markov model) 모델을 제안한다. 제안된 연구 방법에서, 이중 특징 파라메타로써 LPC ?스트럼과 LPC 스트럼의 회귀 계수를 사용한다. 학습 데이터는 몇 개의 구간으로 나누어지며, 첫 번째 구간의 코드북(codebook)을 만든 후, 첫 번째 구간의 코드북으로 부터, 퍼지 개념을 도입하여 확률 값이 큰 순서에 의해 다중 관측열을 구한다. 그 다음, 첫 번째 구간의 관측열을 학습시키고, 같은 방법으로 확률 값을 얻은 단어가 인식되어 진다. 제안된 방법에 의한 인식 실험을 수행하는 것 이외에도 비교를 위하여 다른 방법의 인식 실험을 같은 조건하에서 같은 데이터로 수행하였다. 실험 결과, 본 연구에서 제안한 방법이 다른 방법들보다 인식률이 우수함을 입증하였다. 입증하였다. In this paper, we propose a HMM model using FSVQ(First Section VQ), fuzzy theory and doubly spectral feature, as study on the isolated word recognition system of speaker-independent. In the proposed paper, LPC cepstrum coefficients and regression coefficients of LPC cepstrum as doubly spectral feature be used. And, training data are divided several section and first section is generated codebook of VQ, and then is obtained multi-observation sequences by order of large propabilistic values based on fuzzy nile from the codebook of the first section. Thereafter, this observation sequences of first section is trained and is recognized a word to be obtained highest probaility by same concept. Besides the speech recognition experiments of proposed method, we experiment the other methods under the equivalent environment of data and conditions. In the whole experiment, it is proved that the proposed method is superior to the others in recognition rate.