• Proceedings of the Acoustical Society of Korea Conference
• /
• 1998.06c
• /
• pp.245-248
• /
• 1998

In this paper, a new variable wavelet packet decomposition audio coder, based on the time varying characteristic of the audio signals, is proposed and presents a technique to incorporate psychoacoustic models into an adaptive wave let packet scheme. The proposed filterbank improves the defect of the polyphase filterbank that could not properly represent the critical band and the defect of QMF-tree filter that need high complexity to implement. The filterbank consists of varying number of subband from 4 to 26 bands and use Daubechies 6-order wave let. The codec yields excellent quality at total bit rates of about 128kbps for monophonic CD-quality signals with an sampling frequency of 44.1kHz and reduces complexity by 19% for various bit-rates and sources with encoding and decoding process.

• Journal of Information Processing Systems
• /
• v.13 no.5
• /
• pp.1135-1148
• /
• 2017

Speech recognition is one of the fascinating fields in the area of Computer science. Accuracy of speech recognition system may reduce due to the presence of noise present in speech signal. Therefore noise removal is an essential step in Automatic Speech Recognition (ASR) system and this paper proposes a new technique called combined thresholding for noise removal. Feature extraction is process of converting acoustic signal into most valuable set of parameters. This paper also concentrates on improving Mel Frequency Cepstral Coefficients (MFCC) features by introducing Discrete Wavelet Packet Transform (DWPT) in the place of Discrete Fourier Transformation (DFT) block to provide an efficient signal analysis. The feature vector is varied in size, for choosing the correct length of feature vector Self Organizing Map (SOM) is used. As a single classifier does not provide enough accuracy, so this research proposes an Ensemble Support Vector Machine (ESVM) classifier where the fixed length feature vector from SOM is given as input, termed as ESVM_SOM. The experimental results showed that the proposed methods provide better results than the existing methods.

• Proceedings of the IEEK Conference
• /
• 1998.06a
• /
• pp.619-622
• /
• 1998

본 논문은 웨이브렛 패킷에 기초한 직교 다중화 변복조 방식을 소개하고 특히 시스템 설계자 입장에서 전송 신호의 특성을 시간-주파수 공간에서 신호 파형을 설계하고 채널 특성에 맞게 설계할 수 있는 궂를 제공하는 WPM(wavelet packet modulation) 방식을 기술하였다. 직교 기저 함수 집합을 만들어 시간주파수 공간을 임의적으로 partitioning하고 간섭 잡음 재철에 더잘 적응할 수 있는 구조를 찾는 방법을 소개하였고 튜닝 알고리듬의 실험적인 결과를 가지고 WPM변조 방식의 간섭 잡음에 대한 우수한 성능을 갖음을 보였다.

• Smart Structures and Systems
• /
• v.19 no.2
• /
• pp.181-194
• /
• 2017

In order to investigate the interface debonding defects detection mechanism between steel tube and concrete core of concrete-filled steel tubes (CFSTs), multi-physical fields coupling finite element models constituted of a surface mounted Piezoceramic Lead Zirconate Titanate (PZT) actuator, an embedded PZT sensor and a circular cross section of CFST column are established. The stress wave initiation and propagation induced by the PZT actuator under sinusoidal and sweep frequency excitations are simulated with a two dimensional (2D) plain strain analysis and the difference of stress wave fields close to the interface debonding defect and within the cross section of the CFST members without and with debonding defects are compared in time domain. The linearity and stability of the embedded PZT response under sinusoidal signals with different frequencies and amplitudes are validated. The relationship between the amplitudes of stress wave and the measurement distances in a healthy CFST cross section is also studied. Meanwhile, the responses of PZT sensor under both sinusoidal and sweep frequency excitations are compared and the influence of debonding defect depth and length on the output voltage is also illustrated. The results show the output voltage signal amplitude and head wave arriving time are affected significantly by debonding defects. Moreover, the measurement of PZT sensor is sensitive to the initiation of interface debonding defects. Furthermore, wavelet packet analysis on the voltage signal under sweep frequency excitations is carried out and a normalized wavelet packet energy index (NWPEI) is defined to identify the interfacial debonding. The value of NWPEI attenuates with the increase in the dimension of debonding defects. The results help understand the debonding defects detection mechanism for circular CFST members with PZT technique.

• Smart Structures and Systems
• /
• v.12 no.3_4
• /
• pp.327-344
• /
• 2013

Beam string structure (BSS) is introduced as a new type of hybrid prestressed string structures. The composition and mechanics features of BSS are discussed. The main principles of wavelet packet transform (WPT), principal component analysis (PCA) and support vector machine (SVM) have been reviewed. WPT is applied to the structural response signals, and feature vectors are obtained by feature extraction and PCA. The feature vectors are used for training and classification as the inputs of the support vector machine. The method is used to a single one-way arched beam string structure for damage detection. The cable prestress loss and web members damage experiment for a beam string structure is carried through. Different prestressing forces are applied on the cable to simulate cable prestress loss, the prestressing forces are calculated by the frequencies which are solved by Fourier transform or wavelet transform under impulse excitation. Test results verify this method is accurate and convenient. The damage cases of web members on the beam are tested to validate the efficiency of the method presented in this study. Wavelet packet decomposition is applied to the structural response signals under ambient vibration, feature vectors are obtained by feature extraction method. The feature vectors are used for training and classification as the inputs of the support vector machine. The structural damage position and degree can be identified and classified, and the test result is highly accurate especially combined with principle component analysis.

• Journal of Broadcast Engineering
• /
• v.7 no.1
• /
• pp.55-65
• /
• 2002

Wavelet transform has recently emerged as a promising technique for video processing applications due to its flexibility in representing non-stationary video signals. Motion estimation which uses wavelet transform of octave band division method is applied In many places but if motion estimation error happens in the lowest frequency band. motion estimation error is accumulated by next time strep and there has the Problem that time and the data amount that are cost In calculation at each steps are increased. On the other hand. wavelet packet that achieved the best image quality in a given bit rate from a rate-distortion sense is suggested. But, this method has the disadvantage of time costs on designing wavelet packet. In order to solve this problem we solved this problem by introducing Top_down method. But we did not find the optimum solution in a given butt rate. That image variance can represent image complexity is considered in this paper. In this paper. we propose a fast multiresolution motion estimation scheme based on the adaptive wavelet transform for video compression.

• Journal of Advanced Navigation Technology
• /
• v.23 no.4
• /
• pp.273-280
• /
• 2019

There are many studies that use structure health monitoring to reduce maintenance costs for aircraft and to increase aircraft utilization. Many studies on FBG sensors are also being conducted. However, if the FBG sensor is installed inside the composite, voids will occur between the layers of the composite, resulting in signal split problem. In addition, the FBG sensor is not affected by electromagnetic waves, but will produce electromagnetic noise caused by electronic equipment during post-processing. In this paper, to reduce the error caused by these noises, the stationary wavelet transform, which has the characteristics of movement immutability and is efficient in nonlinear signal analysis, is presented. And in the above situation, we found that noise rejection performance of stationary wavelet transform was better compared with the wavelet packet transform.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.2
• /
• pp.412-434
• /
• 2023

This study discusses the high-order diffusion method in the wavelet domain. It aims to improve the edge protection capability of the high-order diffusion method using wavelet coefficients that can reflect image information. During the first step of the proposed diffusion method, the wavelet packet decomposition is a more refined decomposition method that can extract the texture and structure information of the image at different resolution levels. The high-frequency wavelet coefficients are then used to construct the edge detection function. Subsequently, because accurate wavelet coefficients can more accurately reflect the edges and details of the image information, by introducing the idea of state weight, a scheme for recovering wavelet coefficients is proposed. Finally, the edge detection function is constructed by the module of the wavelet coefficients to guide high-order diffusion, the denoised image is obtained. The experimental results showed that the method presented in this study improves the denoising ability of the high-order diffusion model, and the edge protection index (SSIM) outperforms the main methods, including the block matching and 3D collaborative filtering (BM3D) and the deep learning-based image processing methods. For images with rich textural details, the present method improves the clarity of the obtained images and the completeness of the edges, demonstrating its advantages in denoising and edge protection.

• The Journal of the Acoustical Society of Korea
• /
• v.22 no.8
• /
• pp.670-679
• /
• 2003

This paper deals with application of wavelet transform, which is known to be good for time-frequency analysis, in order to detect the underwater transient signals embedded in ambient noise. A new detector of acoustic transient signals is presented. It combines two detection tools: wavelet analysis and higher-order statistics. Using both techniques, the detection of the transient signal is possible in low signal to noise ratio condition. The proposed algorithm uses the wavelet transform of a partition of the signal on frequency domain, and then higher-order statistics tests the Gaussian nature of the segments.

• Journal of Information Processing Systems
• /
• v.15 no.5
• /
• pp.1068-1081
• /
• 2019

Signal complexity is one point of view to analyze the biological signal. It arises as a result of the physiological signal produced by biological systems. Signal complexity can be used as a method in extracting the feature for a biological signal to differentiate a pathological signal from a normal signal. In this research, Hjorth descriptors, one of the signal complexity measurement techniques, were measured on signal sub-band as the features for lung sounds classification. Lung sound signal was decomposed using two wavelet analyses: discrete wavelet transform (DWT) and wavelet packet decomposition (WPD). Meanwhile, multi-layer perceptron and N-fold cross-validation were used in the classification stage. Using DWT, the highest accuracy was obtained at 97.98%, while using WPD, the highest one was found at 98.99%. This result was found better than the multi-scale Hjorth descriptor as in previous studies.