TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region最新文献_第8页

Color image compression using bit reduction and Burrows Wheeler transform 彩色图像压缩采用比特缩减和Burrows Wheeler变换

TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region Pub Date : 2003-10-15 DOI: 10.1109/TENCON.2003.1273376

S. Annadurai, R. Shanmugalakshmi

引用次数: 2

Performance analysis of an LMS based Fourier analyzer for sinusoidal signals with time-varying amplitude 基于LMS的傅立叶分析仪对时变振幅正弦信号的性能分析

TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region Pub Date : 2003-10-15 DOI: 10.1109/TENCON.2003.1273150

N. Kudoh, Y. Tadokoro

引用次数: 3

Line segment distribution of sketches for Persian signature recognition 波斯语签名识别中草图的线段分布

TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region Pub Date : 2003-10-15 DOI: 10.1109/TENCON.2003.1273203

A. Chalechale, A. Mertins

引用次数: 33

Effect of GCI perturbation on speech quality in Indian languages GCI扰动对印度语语音质量的影响

TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region Pub Date : 2003-10-15 DOI: 10.1109/TENCON.2003.1273389

P. Lehana, P. C. Pandey

引用次数: 5

Optimally weighted matrix pencil approach for 2-D harmonic retrieval 二维谐波检索的最优加权矩阵铅笔法

TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region Pub Date : 2003-10-15 DOI: 10.1109/TENCON.2003.1273245

Qi Cheng

引用次数: 1

Performance and analysis of the spiral representation of spatial feature for color-spatial image retrieval 彩色空间图像检索中空间特征螺旋表示的性能与分析

TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region Pub Date : 2003-10-15 DOI: 10.1109/TENCON.2003.1273226

W. Hui, N. Kulathuramaiyer, Wang Yin Chai, Ahdelhamid Abdessalam

引用次数: 0

Pitch estimation of polyphonic songs using comb filters and singular value decomposition 利用梳状滤波器和奇异值分解对复调歌曲进行音高估计

TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region Pub Date : 2003-10-15 DOI: 10.1109/TENCON.2003.1273348

M. Yamaguchi, Y. Tadokoro

引用次数: 0

A comparative study on methods for evaluation of lightning impulse parameters 雷电冲击参数评价方法的比较研究

TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region Pub Date : 2003-10-15 DOI: 10.1109/TENCON.2003.1273183

S. Venkatesan, P. Vanaja Ranjan, D. Ashokaraju

{"title":"A comparative study on methods for evaluation of lightning impulse parameters","authors":"S. Venkatesan, P. Vanaja Ranjan, D. Ashokaraju","doi":"10.1109/TENCON.2003.1273183","DOIUrl":"https://doi.org/10.1109/TENCON.2003.1273183","url":null,"abstract":"The parameters of lightning impulse (LI) can be determined as per IEC-60/IEEE-4 standard, if the shape of the impulse is smooth. However, difficulties arise if the oscillations or overshoot are superimposed on the waveform. If the frequency of such oscillation is greater than 0.5 MHz or the duration of overshoot is less than 1 /spl mu/sec, it is essential to determine the mean curve for evaluating LI Parameters. In this work, two approaches in evaluating the mean curve are extensively analyzed. The first approach is based on multiresolution signal decomposition. This technique uses the wavelet transform, where a dyadic-orthonormal function decomposes the signal into a smooth and detailed version of the original signal. After removing high frequency components from detailed signal, the mean curve of the impulse waveform can be reconstructed. The second approach is based on mathematical curve fitting where smooth or oscillating impulse is represented by a non-linear impulse waveform equation, representing a double exponential function with sine and cosine terms and Levenberg-Marquardt algorithm is used to minimize least mean square error. The merits and demerits of the above two methods are compared and analyzed. Case studies involving the standard lightning impulse (SLI), lighting impulse with front oscillations (LIFO), with peak oscillations (LIPO), impulse with long duration overshoot (LILDO), impulse with front as well as peak oscillations (LlFPO) and impulse with noise (LIN) have been considered. Based on the above analysis, a conclusion is arrived.","PeriodicalId":405847,"journal":{"name":"TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130211779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Performance analysis of matched filter techniques for automated detection of blood vessels in retinal images 匹配滤波技术在视网膜图像血管自动检测中的性能分析

TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region Pub Date : 2003-10-15 DOI: 10.1109/TENCON.2003.1273220

A. Banumathi, R. Devi, Raju, V.A. Kumar

引用次数: 25

Subspace and hypothesis based effective segmentation of co-articulated basic-units for concatenative speech synthesis 基于子空间和假设的协同语音合成基本单元有效分割

TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region Pub Date : 2003-10-15 DOI: 10.1109/TENCON.2003.1273351

R. Muralishankar, R. Srikanth, A. Ramakrishnan

{"title":"Subspace and hypothesis based effective segmentation of co-articulated basic-units for concatenative speech synthesis","authors":"R. Muralishankar, R. Srikanth, A. Ramakrishnan","doi":"10.1109/TENCON.2003.1273351","DOIUrl":"https://doi.org/10.1109/TENCON.2003.1273351","url":null,"abstract":"In this paper, we present two new methods for vowel-consonant segmentation of a co-articulated basic-units employed in our Thirukkural Tamil text-to-speech synthesis system (G. L. Jayavardhana Rama et al, IEEE workshop on Speech Synthesis, 2002). The basic-units considered in this are CV, VC, VCV, VCCV and VCCC, where C stands for a consonant and V for any vowel. In the first method, we use a subspace-based approach for vowel-consonant segmentation. It uses oriented principal component analysis (OPCA) where the test feature vectors are projected on to the V and C subspaces. The crossover of the norm-contours obtained by projecting the test basic-unit onto the V and C subspaces give the segmentation points which in turn helps in identifying the V and C durations of a test basic-unit. In the second method, we use probabilistic principal component analysis (PPCA) to get probability models for V and C. We then use the Neymen-Pearson (NP) test to segment the basic-unit into V and C. Finally, we show that the hypothesis testing turns out to be an energy detector for V-C segmentation which is similar to the first method.","PeriodicalId":405847,"journal":{"name":"TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125650990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3