Loading...
Search for:
wavelet-packets
0.005 seconds
On identification of nonlinear systems using volterra kernels expansion on Laguerre and wavelet function
, Article 2010 Chinese Control and Decision Conference, CCDC 2010, 26 May 2010 through 28 May 2010, Xuzhou ; 2010 , Pages 1141-1145 ; 9781424451821 (ISBN) ; Bustan, D ; Sharif University of Technology
2010
Abstract
Application of Volterra series to the modeling of static and dynamic nonlinear systems is investigated in this paper and compared to other methods. For nonlinear systems with memory, Volterra series serves as a generalization of convolution integral. To parameterize the Volterra kernels for limited dimension series, different methods are discussed. We use Laguerre functions and wavelet packets as orthonormal basis and we find the poles for the basis through a genetic algorithm search. Our test system is a hydraulic actuator with a highly nonlinear dynamics which is modeled with Volterra series. The results show that dynamic model with wavelet packets give a more accurate model with respect...
Estimation of remaining useful life of rolling element bearings using wavelet packet decomposition and artificial neural network
, Article Iranian Journal of Science and Technology - Transactions of Electrical Engineering ; Volume 43 , 2019 , Pages 233-245 ; 22286179 (ISSN) ; Aasi, A ; Arghand, H. A ; Sharif University of Technology
Springer International Publishing
2019
Abstract
Rolling element bearings (REBs) are usually considered among the most critical elements of rotating machines. Therefore, accurate prediction of remaining useful life (RUL) of REBs is a fundamental challenge to improve reliability of the machines. Vibration condition monitoring is the most popular method used for diagnosis of REBs and this is a motivating fact to use recorded vibration data in RUL prediction too. However, it is necessary to extract appropriate features from vibration signal that represent actual damage progress in the REB. In this paper, wavelet packet transform is used to extract signal features and artificial neural network is applied to estimate RUL of the REB. To obtain...
A novel fingerprint image compression technique using wavelets packets and pyramid lattice vector quantization
, Article IEEE Transactions on Image Processing ; Volume 11, Issue 12 , 2002 , Pages 1365-1378 ; 10577149 (ISSN) ; Deriche, M ; Boashash, B ; Sharif University of Technology
2002
Abstract
A novel compression algorithm for fingerprint images is introduced. Using wavelet packets and lattice vector quantization, a new vector quantization scheme based on an accurate model for the distribution of the wavelet coefficients is presented. The model is based on the generalized Gaussian distribution. We also discuss a new method for determining the largest radius of the lattice used and its scaling factor, for both uniform and piecewise-uniform pyramidal lattices. The proposed algorithms aim at achieving the best rate-distortion function by adapting to the characteristics of the subimages. In the proposed optimization algorithm, no assumptions about the lattice parameters are made, and...
Object tracking in crowded video scenes based on the undecimated wavelet features and texture analysis
, Article Eurasip Journal on Advances in Signal Processing ; Volume 2008 , 2008 ; 16876172 (ISSN) ; Rabiee, H. R ; Asadi, M ; Ghanbari, M ; Sharif University of Technology
2008
Abstract
We propose a new algorithm for object tracking in crowded video scenes by exploiting the properties of undecimated wavelet packet transform (UWPT) and interframe texture analysis. The algorithm is initialized by the user through specifying a region around the object of interest at the reference frame. Then, coefficients of the UWPT of the region are used to construct a feature vector (FV) for every pixel in that region. Optimal search for the best match is then performed by using the generated FVs inside an adaptive search window. Adaptation of the search window is achieved by interframe texture analysis to find the direction and speed of the object motion. This temporal texture analysis...
Occlusion handling for object tracking in crowded video scenes based on the undecimated wavelet features
, Article 2007 IEEE/ACS International Conference on Computer Systems and Applications, AICCSA 2007, Amman, 13 May 2007 through 16 May 2007 ; 2007 , Pages 692-699 ; 1424410312 (ISBN); 9781424410316 (ISBN) ; Rabiee, H. R ; Asadi, M ; Ghanbari, M ; Sharif University of Technology
2007
Abstract
In this paper, we propose a new algorithm for occlusion handling for object tracking in the crowded video scenes. The algorithm exploits the properties of undecimated wavelet packet transform (UWPT) coefficients and texture analysis to track arbitrary objects. The algorithm is initialized by the user through specifying a region around the object of interest at the reference frame. Then, coefficients of the UWPT of the region construct a Feature Vector (FV) for every pixel in that region. Optimal search for the best match is then performed by using the generated FVs inside an adaptive search window. Adaptation of the search window is achieved by interframe texture analysis to find the...
Feature extraction from optimal time-frequency and time-scale transforms for the classification of the knee joint vibroarthrographic signals
, Article 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003, 14 December 2003 through 17 December 2003 ; 2003 , Pages 709-712 ; 0780382927 (ISBN); 9780780382923 (ISBN) ; Shamsollahi, M. B ; Rahimi, A ; Behzad, M ; Afkari, P ; Zamani, E. A ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2003
Abstract
In this study knee joint vibroarthrographic (VAG) signals are recorded during active knee movements, which are essentially non-stationary. Because of this nature, common frequency methods are unable to represent the signals, accurately. Both time-frequency and time-scale transforms are used in this research which are good tools for studying non-stationary signals. By optimizing the utilized transforms, it was concluded that the wavelet packet, having the ability of multiresolutional analysis, is a more promising method to extract features from the VAG signals. The performance of different feature extraction techniques were compared by using three new recorded and extensive databases,...
A two dimensional wavelet packet approach for ECG compression
, Article 6th International Symposium on Signal Processing and Its Applications, ISSPA 2001, Kuala Lumpur, 13 August 2001 through 16 August 2001 ; Volume 1 , 2001 , Pages 226-229 ; 0780367030 (ISBN); 9780780367036 (ISBN) ; Nayebi, K ; Sharif University of Technology
IEEE Computer Society
2001
Abstract
An improved compression algorithm for ECG signals is presented using temporal alignment of beats and 2-D wavelet packet transform (WPT). This 2-D transform based approach utilizes the fact that the electrocardiogram (ECG) signals generally show two types of correlation, namely correlation between subsequent samples within each ECG cycle (intrabeat) and correlation between subsequent cycles (interbeat). One simple compression algorithm in the 2-D WPT domain, which is applied to some records in the MIT-BIH arrhythmia database shows lower percent root mean square difference (PRD) than 1-D wavelet based compression methods for the same compression ratio (CR). © 2001 IEEE
Adaptive search window for object tracking in the crowds using undecimated wavelet packet features
, Article 2006 World Automation Congress, WAC'06, Budapest, 24 June 2006 through 26 June 2006 ; 2006 ; 1889335339 (ISBN); 9781889335339 (ISBN) ; Rabiee, H. R ; Asadi, M ; Khadern Hamedani, P ; Ghanbari, M ; Sharif University of Technology
IEEE Computer Society
2006
Abstract
In this paper, we propose an adaptive object tracking algorithm in crowded scenes. The amplitudes of of Undecimated Wavelet Packet Tree coefficients for some selected pixels at the object border are used to create a Feature Vector (FV) corresponding to that pixel. The algorithm uses these FVs to track the pixels of small square blocks located at the vicinity of the object boundary. The search window is adapted through the use of texture information of the scene by finding the direction and speed of the object motion. Experimental results show a good object tracking performance in crowds that include object translation, rotation, scaling and partial occlusion. Copyright - World Automation...
A robust object shape prediction algorithm in the presence of white gaussian noise
, Article MMM2006: 12th International Multi-Media Modelling Conference, Beijing, 4 January 2006 through 6 January 2006 ; Volume 2006 , 2006 , Pages 418-421 ; 1424400287 (ISBN); 9781424400287 (ISBN) ; Rabiee, H. R ; Asadi, M ; Ghanbari, M ; Sharif University of Technology
2006
Abstract
This paper presents a shape prediction algorithm in a noisy video sequence based on pixel representation in the undecimated wavelet domain. In our algorithm for tracking of user-defined shapes in a noisy sequence of images, the amplitude of coefficients in the best basis tree expansion of the undecimated wavelet packet transform are used as feature vectors (FVs). FVs robustness against noise has been achieved through inherent denoising and edge component separation in the best basis selection algorithm. The algorithm uses these FVs to track the pixels of small square blocks located at the vicinity of the object boundary. Searching for the best-matched block has been performed using...
Tool condition monitoring based on sound and vibration analysis and wavelet packet decomposition
, Article 2012 8th International Symposium on Mechatronics and its Applications, ISMA ; April , 2012 ; 9781467308625 (ISBN) ; Akbari, J ; Behzad, M ; EMAL(Emirates Aluminium) ; Sharif University of Technology
2012
Abstract
Tool Condition Monitoring (TCM) is a vital demand of advanced manufacturing in order to develop automated unmanned production. Continuing the machining operation with a worn or damaged tool will result in damages to the workpiece. This problem becomes more important in supplementary machining processes like drilling which the workpiece usually has passed a lot of machining processes and any damage to workpiece at this stage results in high production losses. In this research features of sound pressure and vibration signals in drilling process are recorded and analyzed in order to detect tool wear. Signal statistical features are extracted in time domain, and the features trends as the tool...
Speaker Diarization in Adverse Conditions
, M.Sc. Thesis Sharif University of Technology ; Sameti, Hossein (Supervisor)
Abstract
The goal of a speaker diarization system is to detect the number of speakers of a conversation and also assign each segment of the conversation to one of the speakers. In these types of systems it is assumed that the identity of the speakers is completely unknown. Usually speaker diarization systems operate in an offline mode. The system assumes that it does have the whole conversation at hand and then it starts processing the conversation. This method is effective for applications like spoken document retrieval, but it is not applicable to speech/speaker recognition systems which require online operating. In this dissertation, an online speaker diarization system is implemented. This...
Investigation on Application of Vibration and Sound Signals for Tool Condition Monitoring
, M.Sc. Thesis Sharif University of Technology ; Behzad, Mehdi (Supervisor) ; Akbari, Javad (Supervisor)
Abstract
Tool Condition Monitoring (TCM) is a vital demand of advanced manufacturing in order to develop automated unmanned production. Tool condition has an essential influence on machined surface quality and dimension of manufactured parts. Continuing machining operation with a worn or damaged tool will result in damages to workpiece and even the machine tool itself. This problem becomes more important in supplementary machining processes like drilling in which the workpiece is usually at the final stages of production and any damage to workpiece at this stage is irreparable and results in high production losses. In this thesis, sound and vibrations signals are analyzed for drill wear detection....
A Wavelet-packet-based approach for breast cancer classification
, Article Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS ; 2011 , Pages 5100-5103 ; 1557170X (ISSN) ; 9781424441211 (ISBN) ; Razavian, S. M. J ; Vaziri, R ; Vosoughi Vahdat, B ; Sharif University of Technology
Abstract
In this paper, a new approach for non-invasive diagnosis of breast diseases is tested on the region of the breast without undue influence from the background and medically unnecessary parts of the images. We applied Wavelet packet analysis on the two-dimensional histogram matrices of a large number of breast images to generate the filter banks, namely sub-images. Each of 1250 resulting sub-images are used for computation of 32 two-dimensional histogram matrices. Then informative statistical features (e.g. skewness and kurtosis) are extracted from each matrix. The independent features, using 5-fold cross-validation protocol, are considered as the input sets of supervised classification. We...
A VLSI architecture for multiple antenna eigenvalue-based spectrum sensing
, Article 2012 19th IEEE International Conference on Electronics, Circuits, and Systems, ICECS 2012, 9 December 2012 through 12 December 2012 ; December , 2012 , Pages 153-156 ; 9781467312615 (ISBN) ; Shabany, M ; Sharif University of Technology
2012
Abstract
An Eigenvalue-based detection (EBD) scheme, is proposed as an efficient method to overcome the noise uncertainty and the SNR wall problem in conventional energy detection (ED) schemes. Despite remarkable efforts made to analyze the EBD performance, a VLSI implementation is missing in literature. In this paper, a new FFT-based EBD algorithm is introduced, which eliminates the need for filter banks and discrete wavelet packet transform to channelize the input signal. The proposed method enables the utilization of the EBD algorithm in high-resolution spectrum sensing approaches. Moreover, it enables the detection of signals with SNRs as low as -10 dB. A low-power, area-efficient yet real-time...
Wavelet packet decomposition of a new filter -based on underlying neural activity- for ERP classification
, Article 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07, Lyon, 23 August 2007 through 26 August 2007 ; 2007 , Pages 1876-1879 ; 05891019 (ISSN) ; 1424407885 (ISBN); 9781424407880 (ISBN) ; Shamsollahi, M. B ; Hashemi, M. R ; Rezazadeh, I ; Sharif University of Technology
2007
Abstract
This paper introduces a wavelet packet algorithm based on a new wavelet like filter created by a neural mass model in place of wavelet. The hypothesis is that the performance of an ERP based BCI system can be improved by choosing an optimal wavelet derived from underlying mechanism of ERPs. The wavelet packet transform has been chosen for its generalization in comparison to wavelet. We compared the performance of proposed algorithm with existing standard wavelets as Db4, Bior4.4 and Coif3 in wavelet packet platform. The results showed a lowest cross validation error for the new filter in classification of two different kinds of ERP datasets via a SVM classifier. © 2007 IEEE
A quantization noise robust object's shape prediction algorithm
, Article 13th European Signal Processing Conference, EUSIPCO 2005, Antalya, 4 September 2005 through 8 September 2005 ; 2005 , Pages 1770-1773 ; 1604238216 (ISBN); 9781604238211 (ISBN) ; Rabiee, H. R ; Asadi, M ; Nosrati, M ; Amiri, M ; Ghanbari, M ; Sharif University of Technology
2005
Abstract
This paper introduces a quantization noise robust algorithm for object's shape prediction in a video sequence. The algorithm is based on pixel representation in the undecimated wavelet domain for tracking of the user-defined shapes contaminated by the compression noise of video sequences. In the proposed algorithm, the amplitude of coefficients in the best basis tree expansion of the undecimated wavelet packet transform is used as feature vectors (FVs). FVs robustness against quantization noise has been achieved through inherent denoising and edge component separation in the best basis selection algorithm. The algorithm uses these FVs to track the pixels of small square blocks located at the...
A robust image watermarking using two level DCT and wavelet packets denoising
, Article International Conference on Availability, Reliability and Security, ARES 2009, Fukuoka, Fukuoka Prefecture, 16 March 2009 through 19 March 2009 ; 2009 , Pages 150-157 ; 9780769535647 (ISBN) ; Jamzad, M ; Sharif University of Technology
2009
Abstract
In this paper we present a blind low frequency watermarking scheme on gray level images, which is based on DCT transform and spread spectrum communications technique. We compute the DCT of non overlapping 8x8 blocks of the host image, then using the DC coefficients of each block we construct a low-resolution approximation image. We apply block based DCT on this approximation image, then a pseudo random noise sequence is added into its high frequencies. For detection, we extract the approximation image from the watermarked image, then the same pseudo random noise sequence is generated, and its correlation is computed with high frequencies of the watermarked approximation image. In our method,...