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Articles 1 - 22 of 22
Full-Text Articles in Computer Engineering
A Practical Low-Dimensional Feature Vector Generation Method Based On Wavelet Transform For Psychophysiological Signals, Erdem Erkan, Yasemi̇n Erkan
A Practical Low-Dimensional Feature Vector Generation Method Based On Wavelet Transform For Psychophysiological Signals, Erdem Erkan, Yasemi̇n Erkan
Turkish Journal of Electrical Engineering and Computer Sciences
High-dimensional feature vectors entail computational cost and computational complexity. However, a successful classification can be obtained with an optimally sized feature vector consisting of distinctive features. With the widespread use of the internet and mobile devices, the need for systems with low computational costs is increasing day by day. In this study, starting from the idea that each motor imagery is represented as a subject-specific pattern in the brain, we propose a new and practical method that can generate a low-dimensional feature vector based on wavelet transform. The feature vector is obtained from the correlation between each trial and each …
Terrain Surface Texture Generation Networks For User Semantics Customization, Yan Gao, Jimeng Li, Jianzhong Xu, Hongyan Quan
Terrain Surface Texture Generation Networks For User Semantics Customization, Yan Gao, Jimeng Li, Jianzhong Xu, Hongyan Quan
Journal of System Simulation
Abstract: Customizing terrain based on user semantics has practical value in the virtual terrain modeling of military simulation applications. This study provides a terrain surface texture generation network (TSTG-Net) that can synthesize realistic terrain based on user input semantics. TSTG-Net is designed as a Pix2pix structure and is based on CGAN. It learns the topology of customized terrain by encoding and parsing user semantics and regards the semantics feature as the constraint of CGAN. In the generator-discriminator structure, user-customized semantics are used as the input, and the real terrain with semantics is employed as the ground truth in network optimization. …
Short-Time Human Activity Recognition Based On Wavelet Features Matching, Benyue Su, Li Zhang, Qingxuan He, Min Sheng
Short-Time Human Activity Recognition Based On Wavelet Features Matching, Benyue Su, Li Zhang, Qingxuan He, Min Sheng
Journal of System Simulation
Abstract: The selection of features is the key problem in the study of human activity recognition. In order to obtain sufficient and stable behavioral features, long-time behavioral data that exceed one behavior cycle are often processed, while short-time behavioral data with less than one behavioral cycle are usually unstable, making it difficult to achieve accurate and stable identification. This paper proposes a short-time human activity recognition method based on the combination of wavelet transform and template matching. Coefficient features are extracted using wavelet transform method. The features of the short-time test samples are matched with the features in the template …
Evaluation Of Mother Wavelets On Steady-State Visually-Evoked Potentials Fortriple-Command Brain-Computer Interfaces, Ebru Sayilgan, Yilmaz Kemal Yüce, Yalçin İşler
Evaluation Of Mother Wavelets On Steady-State Visually-Evoked Potentials Fortriple-Command Brain-Computer Interfaces, Ebru Sayilgan, Yilmaz Kemal Yüce, Yalçin İşler
Turkish Journal of Electrical Engineering and Computer Sciences
Wavelet transform (WT) is an important tool to analyze the time-frequency structure of a signal. The WT relies on a prototype signal that is called the mother wavelet. However, there is no single universal wavelet that fits all signals. Thus, the selection of mother wavelet function might be challenging to represent the signal to achieve the optimum performance. There are some studies to determine the optimal mother wavelet for other biomedical signals; however, there exists no evaluation for steady-state visually-evoked potentials (SSVEP) signals that becomes very popular among signals manipulated for brain-computer interfaces (BCIs) recently. This study aims to explore, …
Simulation Study On Damage Localization Of Large Generator Stator Insulation Based On Guided Waves, Li Hao, Ruihua Li, Hu Bo, Pan Ling, Qiyi Guo
Simulation Study On Damage Localization Of Large Generator Stator Insulation Based On Guided Waves, Li Hao, Ruihua Li, Hu Bo, Pan Ling, Qiyi Guo
Journal of System Simulation
Abstract: A stator insulation damage localization method based on guided waves was proposed. The dispersive curve was obtained by solving the Rayleigh-Lamb equations. Finite structure models of four typical groundwall insulation damage, i.e. void, delamination, longitudinal and transverse crack were established by FEM software Abaqus, in which the excitation, acquisition and propagation properties of guided wave were numerical simulated. Based on that, wavelet scalogram was used to extract the flight time of damage-scattered wave to obtain the insulation damage location. Analysis was conducted to compare the location precision under each wave modes. Simulation results indicate that the method is …
Wood Structure Nondestructive Detection Based On Wavelet Analysis Ant-Colony Bp Network, Guoxiong Zhou, Xianyan Zhou, Jiejun Wang, Te Huang
Wood Structure Nondestructive Detection Based On Wavelet Analysis Ant-Colony Bp Network, Guoxiong Zhou, Xianyan Zhou, Jiejun Wang, Te Huang
Journal of System Simulation
Abstract: In view of the wood component glue line defect, a method of wood structure nondestructive detection was proposed based on ant colony BP neural network. The wood specimens was tested to obtain the test signal by ultrasonic testing instrument, in order to eliminate the testing effect of the tester gain control and defect size, angle variation on the test defect echo amplitude, the defect signal amplitude was needed to normalization. The wood component decomposition of ultrasonic signals was de-composite to different frequency channels by the domain band-pass characteristics of the wavelet frequency. By extract characteristic of the original signal …
Downhole Drilling Processing Data Acquisition And Stick Slip Characteristic Analysis, Huang Sheng, Zhang Tao, Chongjun Huang, Yumei Li, Deng Hu, Zhang Xia
Downhole Drilling Processing Data Acquisition And Stick Slip Characteristic Analysis, Huang Sheng, Zhang Tao, Chongjun Huang, Yumei Li, Deng Hu, Zhang Xia
Journal of System Simulation
Abstract: During oil drilling process, drill string vibrations are detrimental to the bit and drill string, which even causes failure of equipment. Researches show that, studying the law of near bit vibration data can reduce non-production time (NPT) and improve drilling efficiency. This paper uses power spectral density and wavelet transform to analyze vibration signals, then compares with normal drilling situation to find out stick slip characteristics. The results show that, when stick slip occurs, the mean value of lateral vibration fluctuates greatly, which indicates stick slip is mainly based on torsional vibration. From the perspective of power spectral density …
Wavelet Transform On Digital Rainbow Hologram Based On Spectral Compression For Quality Enhancement In 3d Display Media, Ucuk Darusalam, Panca Dewi Pamungkasari
Wavelet Transform On Digital Rainbow Hologram Based On Spectral Compression For Quality Enhancement In 3d Display Media, Ucuk Darusalam, Panca Dewi Pamungkasari
Makara Journal of Technology
A digital rainbow hologram (DRH) is a potential next-generation three-dimensional display media for the development of modern and smart electronics devices. It is one of the methods that can support the characteristic whereby a realistic display media occupies the space that the real object would have occupied. Since a rainbow hologram records a large amount of spatial or temporal frequency component from the object that represents the rainbow spectrum, a large amount of information needs to be decoded digitally. In this paper, to reconstruct a DRH, we propose a novel method based on the modulation of red, green, and blue …
De-Noising Method Of Eeg Signal Based On Mmtd And Wavelet Hard-Threshold, Guoqiang Yan, Ningning Zhou, Shaobai Zhang
De-Noising Method Of Eeg Signal Based On Mmtd And Wavelet Hard-Threshold, Guoqiang Yan, Ningning Zhou, Shaobai Zhang
Journal of System Simulation
Abstract: To overcome the shortage of losing partial important information of hard-threshold method with EEG signal de-noising process, a novel de-noising method based on the combination of measuring of medium truth degree (MMTD) and EEG is proposed. By decomposing noisy signals of wavelet transform, handling threshold of high-frequency wavelet coefficients in every layer, and reconstructing post-processing of the wavelet coefficients, the purpose of noise elimination can be guaranteed. Under different noise intensity, the experimental results show that the MAWH (MMTD and wavelet hard-threshold) method has perspective of lower RMSE and higher SNR compared to hard-threshold and soft-threshold.
Application Of Wavelet Transform In Simulation Model Validation Of Outboard Active Decoy, Hongxi Zhang, Zhang Jie
Application Of Wavelet Transform In Simulation Model Validation Of Outboard Active Decoy, Hongxi Zhang, Zhang Jie
Journal of System Simulation
Abstract: Aiming at the characteristics that the output signal of outboard active decoy simulation model is non-stationary random signal, a simulation model verification method based on wavelet transform is proposed. The measured and simulated signals are decomposed into low frequency and high frequency parts by determining the wavelet function. For the low frequency part with stationary state, the characteristic data is obtained by parameter fitting with the least square method. For the high frequency part, AR model is used to fit the parameters, and the fitting parameters are used as the characteristic data, The correlation coefficient method is used to …
Vascular Image Enhancement Using Steerable Filters, Yiren Wang, Guoqing Deng, Yingwei Xia, Zhang Long, Liu Yong, Zhang Wen
Vascular Image Enhancement Using Steerable Filters, Yiren Wang, Guoqing Deng, Yingwei Xia, Zhang Long, Liu Yong, Zhang Wen
Journal of System Simulation
Abstract: Based on the weakness of traditional image enhancement algorithms, an enhancement algorithm with steerable filter is put forward, which uses computer vision system as hardware platform. A steerable filter is applied for taking vein information in different directions. The wavelet transform is used to fuse image for high frequency information on vein. The nonlinear unsharp masking enhancement algorithm is used to escalate vein image. Experiment results show that the new algorithm can effectively suppress noise, reduce information loss and achieve better enhancement.
Transient- And Probabilistic Neural Network-Based Fault Classification In Ehv Three-Terminal Lines, Ravi Kumar Varma Bhupatiraju, Venkata Sesha Samba Siva Sarma Dhanikonda, Venkata Ramana Rao Pulipaka
Transient- And Probabilistic Neural Network-Based Fault Classification In Ehv Three-Terminal Lines, Ravi Kumar Varma Bhupatiraju, Venkata Sesha Samba Siva Sarma Dhanikonda, Venkata Ramana Rao Pulipaka
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a fast and accurate fault classifier for three-terminal transmission circuits. Traditional phasor-based methods fail to meet the high speed requirements of modern power grids and necessitate alternative solutions. The transient-based schemes use advanced signal processing techniques to achieve fast and accurate fault classification. As the three-terminal lines experience very pronounced transients during faults, the proposed method makes use of the fault-generated transients to quickly and correctly classify the fault. Many transient-based schemes fail to give the required accuracy since the transient patterns with relay-measured signals are highly influenced by fault conditions. Therefore, a thorough analysis of transient …
Multi-Classifier Fusion Strategy For Activity And Intent Recognition Of Torso Movements, Abhijit Kadrolkar
Multi-Classifier Fusion Strategy For Activity And Intent Recognition Of Torso Movements, Abhijit Kadrolkar
Doctoral Dissertations
As assistive, wearable robotic devices are being developed to physically assist their users, it has become crucial to develop safe, reliable methods to coordinate the device with the intentions and motions of the wearer. This dissertation investigates the recognition of user intent during flexion and extension of the human torso in the sagittal plane to be used for control of an assistive exoskeleton for the human torso. A multi-sensor intent recognition approach is developed that combines information from surface electromyogram (sEMG) signals from the user’s muscles and inertial sensors mounted on the user’s body. Intent recognition is implemented by following …
Heart Sound Signal Classification Using Fast Independent Component Analysis, Yücel Koçyi̇ği̇t
Heart Sound Signal Classification Using Fast Independent Component Analysis, Yücel Koçyi̇ği̇t
Turkish Journal of Electrical Engineering and Computer Sciences
No abstract provided.
Predicting Acute Hypotensive Episode By Using Hybrid Features And A Neuro-Fuzzy Network, Marzieh Abbasinia, Fardad Farokhi, Shahram Javadi
Predicting Acute Hypotensive Episode By Using Hybrid Features And A Neuro-Fuzzy Network, Marzieh Abbasinia, Fardad Farokhi, Shahram Javadi
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents an approach for acute hypotensive episode (AHE) time series forecasting based on hybrid feature space and a neuro-fuzzy network. Prediction was accomplished through a combination of time domain and wavelet features by using six vital time series of each patient, obtained from MIMIC-II and available in the context of the Physionet-Computers in Cardiology 2009 Challenge. At first, statistical time domain features were used and then the wavelet coefficient was utilized for extracting time scale features. Further UTA feature selection was applied and 30 effective features were determined and achieved to predict AHE with 96.30 accuracy 1.5 h …
Improving The Srf Method To Compensate Low-Order Harmonics Under Nonsinusoidal Network Voltages, Javad Modarresi, Mehdi Fallah, Eskandar Ghokipour, Mohammad Tavakoli Bina
Improving The Srf Method To Compensate Low-Order Harmonics Under Nonsinusoidal Network Voltages, Javad Modarresi, Mehdi Fallah, Eskandar Ghokipour, Mohammad Tavakoli Bina
Turkish Journal of Electrical Engineering and Computer Sciences
Increasing the application of power in electronic devices has increased the harmonics in power systems. Numerous methods like the synchronous reference frame (SRF) and the p-q-based method have been suggested to overcome the effects of these harmonics. The conventional SRF method provides acceptable results in harmonic compensation of high-order harmonics (higher than the fourth order), but the transient response time will be drastically increased in the presence of low-order harmonics due to the existence of a conventional low-pass filter. Furthermore, if the load terminal voltages are distorted, then the conventional SRF method will become unable to implement load current compensation. …
Short-Term Load Forecasting Without Meteorological Data Using Ai-Based Structures, İdi̇l Işikli Esener, Tolga Yüksel, Mehmet Kurban
Short-Term Load Forecasting Without Meteorological Data Using Ai-Based Structures, İdi̇l Işikli Esener, Tolga Yüksel, Mehmet Kurban
Turkish Journal of Electrical Engineering and Computer Sciences
STLF is used in making decisions about economical power generation capacity, fuel purchasing, safety assessment, and power system planning in order to have economical power conditions. In this study, Turkey's 24-hour-ahead load forecasting without meteorological data is studied. ANN, wavelet transform and ANN, wavelet transform and RBF NN, and EMD and RBF NN structures are used in STLF procedures. Local holidays' historical load data are changed into data with normal day characteristics, and the estimation results of these days are not included in error computation. To obtain more accurate results, a regulation on forecasted loads is proposed. Regulated and unregulated …
A New Method For Segmentation Of Microscopic Images On Activated Sludge, Hali̇me Boztoprak, Yüksel Özbay
A New Method For Segmentation Of Microscopic Images On Activated Sludge, Hali̇me Boztoprak, Yüksel Özbay
Turkish Journal of Electrical Engineering and Computer Sciences
Activated sludge samples were taken from the Konya Wastewater Treatment Plant. Two hundred images for each sample were captured by a systematic examination of the slides. Segmentation of microscopic images is a challenging process due to lack of focus. Therefore, adjustment of the focus is required for every movement of the mobile stage. Because the mobile stage does not have the z axis, the focus cannot be adjusted. A new method that uses automatic segmentation of the captured images is developed for solving this problem. The proposed method is not dependent on image content, has minimal computation complexity, and is …
Applications Of Wavelets And Neural Networks For Classification Of Power System Dynamics Events, Samir Avdakovic, Amir Nuhanovic, Mirza Kusljugic, Elvisa Becirovic
Applications Of Wavelets And Neural Networks For Classification Of Power System Dynamics Events, Samir Avdakovic, Amir Nuhanovic, Mirza Kusljugic, Elvisa Becirovic
Turkish Journal of Electrical Engineering and Computer Sciences
This paper investigates the possibility of classifying power system dynamics events using discrete wavelet transform (DWT) and a neural network (NN) by analyzing one variable at a single network bus. Following a disturbance in the power system, it will propagate through the system in the form of low-frequency electromechanical oscillations (LFEOs) in a frequency range of up to 5 Hz. DWT allows the identification of components of the LFEO, their frequencies, and magnitudes. After determining the energy components' share of the analyzed signal using DWT and Parseval's theorem, the input data for the classification process using a NN are obtained. …
Wavelet Multiscale Analysis Of A Power System Load Variance, Samir Avdakovic, Amir Nuhanovic, Mirza Kusljugic, Elvisa Becirovic, Elma Turkovic
Wavelet Multiscale Analysis Of A Power System Load Variance, Samir Avdakovic, Amir Nuhanovic, Mirza Kusljugic, Elvisa Becirovic, Elma Turkovic
Turkish Journal of Electrical Engineering and Computer Sciences
Wavelet transform (WT) represents a very attractive mathematical area for just more than 15 years of its research in applications in electrical engineering. This is mainly due to its advantages over other processing techniques and signal analysis, which is reflected in the time-frequency analysis, and so it has an important application in the processing and analysis of time series. In this paper, for example, the analysis of the hourly load of a real power system over the past few years was performed by applying the continuous WT and using the Morlet wavelet function. The results show that this approach of …
Joint Source-Channel Coding For Error Resilient Transmission Of Static 3d Models, Mehmet Oğuz Bi̇ci̇, Andrey Norkin, Gözde Akar
Joint Source-Channel Coding For Error Resilient Transmission Of Static 3d Models, Mehmet Oğuz Bi̇ci̇, Andrey Norkin, Gözde Akar
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, performance analysis of joint source-channel coding techniques for error-resilient transmission of three dimensional (3D) models are presented. In particular, packet based transmission scenarios are analyzed. The packet loss resilient methods are classified into two groups according to progressive compression schemes employed: Compressed Progressive Meshes (CPM) based methods and wavelet based methods. In the first group, layers of CPM algorithm are protected unequally by Forward Error Correction (FEC) using Reed Solomon (RS) codes. In the second group, embedded bitstream obtained from wavelet based coding is protected unequally with FEC as well. Both groups of methods are scalable with …
Resolution Enhancement Of Video Sequences By Using Discrete Wavelet Transform And Illumination Compensation, Sara Izadpanahi, Çağri Özçinar, Gholamreza Anbarjafari, Hasan Demirel
Resolution Enhancement Of Video Sequences By Using Discrete Wavelet Transform And Illumination Compensation, Sara Izadpanahi, Çağri Özçinar, Gholamreza Anbarjafari, Hasan Demirel
Turkish Journal of Electrical Engineering and Computer Sciences
This research paper proposes a new technique for video resolution enhancement that employees an illumination compensation procedure before the registration process. After the illumination compensation process, the respective frames are registered using the Irani and Peleg technique. In parallel, the corresponding frame is decomposed into high-frequency (low-high, high-low, and high-high) and low-frequency (low-low) subbands using discrete wavelet transform (DWT). The high-frequency subbands are superresolved using bicubic interpolation. Afterwards, the interpolated high-frequency subbands and superresolved low-frequency subband obtained by registration are used to construct the high-resolution frame using inverse DWT. The superiority of the proposed resolution enhancement method over well-known video …