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Wyświetlanie 1-15 z 194
Tytuł:
Hybrid wavelet transform – MLR and ANN models for river flow prediction: Case study of Brahmaputra river (Pancharatna station)
Autorzy:
Khandekar, Sachin Dadu
Aswar, Dinesh Shrikrishna
Sabale, Pandurang Digamber
Khandekar, Varsha Sachin
Bajad, Mohankumar Namdeorao
Powiązania:
https://bibliotekanauki.pl/articles/36074310.pdf
Data publikacji:
2024
Wydawca:
Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
Tematy:
wavelet transform
artificial neural network
multiple linear regression
streamflow
Daubechies wavelet
time series
Opis:
In this research, discrete wavelet transform (DWT) is combined with MLR and ANN to develop WMLR and WANN hybrid models, respectively, for the Brahmaputra river (Pancharatna station) flow forecasting. Daily flow data for the period of 10 year were decomposed (up to fifth level) into detailed and approximation coefficients (using Daubechies wavelets db1, db2, db3, db8 and db10) which were fed as input to MLR and ANN to get the predicted discharge values two days, four days, seven days and 14 days ahead. For all lead times, the WMLR-db10 model was found to be superior as compared to WANN-db1, WANN-db2, WANN-db3, WANN-db8, WMLR-db1, WMLR-db2, WMLR-db3, WMLR-db8 and single MLR and ANN models. During testing period, the values of determination coefficient (R2) and RMSE for WMLR-db10 model for two-, four-, seven- and 14-day lead time were found to be, respectively, 0.996 (751.87 m3·s–1), 0.991 (1,174.80 m3·s–1), 0.984 (1,585.02 m3·s–1), and 0.968 (2,196.46 m3·s–1). Also, it was observed that for lower order wavelets (db1, db2, db3) WANN’s performance was better, and for higher order wavelets (db8, db10) WMLR’s performance was better. Correspondingly, it was observed that all hybrid models’ efficiency increased with increase in the decomposition level.
Źródło:
Scientific Review Engineering and Environmental Sciences; 2024, 33, 1; 69-94
1732-9353
Pojawia się w:
Scientific Review Engineering and Environmental Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Damage localization in truss girders by an application of the discrete wavelet transform
Autorzy:
Knitter-Piątkowska, Anna
Kawa, Olga
Guminiak, Michał Jan
Powiązania:
https://bibliotekanauki.pl/articles/2204501.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
truss structures
damage localization
finite element method
discrete wavelet transform
konstrukcja kratownicowa
lokalizacja uszkodzeń
metoda elementów skończonych
dyskretna transformata falkowa
Opis:
The paper demonstrates the potential of wavelet transform in a discrete form for structural damage localization. The efficiency of the method is tested through a series of numerical examples, where the real flat truss girder is simulated by a parameterized finite element model. The welded joints are introduced into the girder and classic code loads are applied. The static vertical deflections and rotation angles of steel truss structure are taken into consideration, structural response signals are computed at discrete points uniformly distributed along the upper or lower chord. Signal decomposition is performed according to the Mallat pyramid algorithm. The performed analyses proved that the application of DWT to decompose structural response signals is very effective in determining the location of the defect. Evident disturbances of the transformed signals, including high peaks, are expected as an indicator of the defect existence in the structure. The authors succeeded for the first time in the detection of breaking the weld in the truss node as well as proved that the defect can be located in the diagonals.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2023, 71, 1; art. no. e144581
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Deep Classifiers and Wavelet Transformation for Fake Image Detection
Autorzy:
Osowski, Stanislaw
Golgowski, Maciej
Powiązania:
https://bibliotekanauki.pl/articles/27312950.pdf
Data publikacji:
2023
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
continuous wavelet transform
convolutional neural
networks
deep fake
ensemble of classifiers
Opis:
The paper presents a computer system for detecting deep fake images in videos. The system is based on continuous wavelet transformation combined with a set of classifiers composed of a few convolutional neural networks of diversified architectures. Three different forms of forged images taken from the FaceForensics++ database are considered in numerical experiments. The results of experiments involving the proposed system have shown good performance in comparison to other current approaches to this particular problem.
Źródło:
Journal of Telecommunications and Information Technology; 2023, 4; 1--8
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fault detection in robots based on discrete wavelet transformation and eigenvalue of energy
Autorzy:
Ouarhlent, Saloua
Terki, Nadjiba
Hamiane, Madina
Dahmani, Habiba
Powiązania:
https://bibliotekanauki.pl/articles/27313829.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
Tematy:
2 DOF robot
fault detection system
discrete wavelet transform
DWT
energy eigen value
robot
dyskretna transformata falkowa
DVT
system wykrywania błędów
Opis:
This article addresses the problem of fault detection in robot manipulator systems. In the production field, online detection and prevention of unexpected robot stops avoids disruption to the entire manufacturing line. A number of researchers have proposed fault diagnosis architectures for electrical systems such as induction motor, DC motor, etc..., utilising the technique of discrete wavelet transform. The results obtained from the use of this technique in the field of diagnosis are very encouraging. Inspired by previous work, The objective of this paper is to present a methodology that enables accurate fault detection in the actuator of a two-degree of freedom robot arm to avoid system performance degradation. A partial reduction in joint torque constitutes the actuator fault, resulting in a deviation from the desired end-effector motion. The actuator fault detection is carried out by analysing the torques signals using the wavelet transform. The stored energy at each level of the transform contains information which can be used as a fault indicator. A Matlab/Simulink simulation of the manipulator robot demonstrates the effectiveness of the proposed technique.
Źródło:
Diagnostyka; 2023, 24, 4; art. no. 2023407
1641-6414
2449-5220
Pojawia się w:
Diagnostyka
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Hybrid deep learning method for detection of liver cancer
Autorzy:
Deshmukh, Sunita P.
Choudhari, Dharmaveer
Amalraj, Shankar
Matte, Pravin N.
Powiązania:
https://bibliotekanauki.pl/articles/38701864.pdf
Data publikacji:
2023
Wydawca:
Instytut Podstawowych Problemów Techniki PAN
Tematy:
liver cancer detection
deep learning
fully convolutional neural network
hybrid approach
discrete wavelet transform
wykrywanie raka wątroby
uczenie głębokie
neuronowa sieć konwulcyjna
podejście hybrydowe
dyskretna transformata falkowa
Opis:
Liver disease refers to any liver irregularity causing its damage. There are several kinds of liver ailments. Benign growths are rarely life threatening and can be removed by specialists. Liver malignant tumor is leading causes of cancer death. Identifying malignant growth tissue is a troublesome and tedious task. There is significantly less information and statistical analysis presented related to cholangiocarcinoma and hepatoblastoma. This research focuses on the image analysis of these two types of cancer. The framework’s performance is evaluated using 2871 images, and a dual hybrid model is used to accomplish superb exactness. The aftereffects of both neural networks are sent into the result prioritizer that decides the most ideal choice for image arrangement. The relevance of elements appears to address the appropriate imaging rules for each class, and feature maps matching the original picture voxel features. The significance of features represents the most important imaging criteria for each class. This deep learning system demonstrates the concept of illuminating elements of a pre-trained deep neural network’s decision-making process by an examination of inner layers and the description of attributes that contribute to predictions.
Źródło:
Computer Assisted Methods in Engineering and Science; 2023, 30, 2; 151-165
2299-3649
Pojawia się w:
Computer Assisted Methods in Engineering and Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Intelligent fault diagnosis of rolling bearings based on continuous wavelet transform-multiscale feature fusion and improved channel attention mechanism
Autorzy:
Zhang, Jiqiang
Kong, Xiangwei
Cheng, Liu
Qi, Haochen
Yu, Mingzhu
Powiązania:
https://bibliotekanauki.pl/articles/24200817.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
deep learning
continuous wavelet transform
improved channel attention mechanism
multi-conditions
convolutional neural network
Opis:
Accurate fault diagnosis is critical to operating rotating machinery safely and efficiently. Traditional fault information description methods rely on experts to extract statistical features, which inevitably leads to the problem of information loss. As a result, this paper proposes an intelligent fault diagnosis of rolling bearings based on a continuous wavelet transform(CWT)-multiscale feature fusion and an improved channel attention mechanism. Different from traditional CNNs, CWT can convert the 1-D signals into 2-D images, and extract the wavelet power spectrum, which is conducive to model recognition. In this case, the multiscale feature fusion was implemented by the parallel 2-D convolutional neural networks to accomplish deeper feature fusion. Meanwhile, the channel attention mechanism is improved by converting from compressed to extended ways in the excitation block to better obtain the evaluation score of the channel. The proposed model has been validated using two bearing datasets, and the results show that it has excellent accuracy compared to existing methods.
Źródło:
Eksploatacja i Niezawodność; 2023, 25, 1; art. no. 16
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multiscale assessment of additively manufactured free-form surfaces
Autorzy:
Gogolewski, Damian
Powiązania:
https://bibliotekanauki.pl/articles/2203371.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
free-form
wavelet transform
multiscale analysis
surface texture
additive manufacturing
Opis:
The article reviews the results of experimental tests assessing the impact of process parameters of additive manufacturing technologies on the geometric structure of free-form surfaces. The tests covered surfaces manufactured with the Selective Laser Melting additive technology, using titanium-powder-based material (Ti6Al4V) and Selective Laser Sintering from polyamide PA2200. The evaluation of the resulting surfaces was conducted employing modern multiscale analysis, i.e., wavelet transformation. Comparative studies using selected forms of the mother wavelet enabled determining the character of irregularities, size of morphological features and the indications of manufacturing process errors. The tests provide guidelines and allow to better understand the potential in manufacturing elements with complex, irregular shapes.
Źródło:
Metrology and Measurement Systems; 2023, 30, 1; 157--168
0860-8229
Pojawia się w:
Metrology and Measurement Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Sleep Snoring Sound Recognition Based on Wavelet Packet Transform
Autorzy:
Ding, Li
Peng, Jianxin
Zhang, Xiaowen
Song, Lijuan
Powiązania:
https://bibliotekanauki.pl/articles/31339924.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
snoring recognition
wavelet packet transform
feature selection
machine learning
Opis:
Snoring is a typical and intuitive symptom of the obstructive sleep apnea hypopnea syndrome (OSAHS), which is a kind of sleep-related respiratory disorder having adverse effects on people’s lives. Detecting snoring sounds from the whole night recorded sounds is the first but the most important step for the snoring analysis of OSAHS. An automatic snoring detection system based on the wavelet packet transform (WPT) with an eXtreme Gradient Boosting (XGBoost) classifier is proposed in the paper, which recognizes snoring sounds from the enhanced episodes by the generalization subspace noise reduction algorithm. The feature selection technology based on correlation analysis is applied to select the most discriminative WPT features. The selected features yield a high sensitivity of 97.27% and a precision of 96.48% on the test set. The recognition performance demonstrates that WPT is effective in the analysis of snoring and non-snoring sounds, and the difference is exhibited much more comprehensively by sub-bands with smaller frequency ranges. The distribution of snoring sound is mainly on the middle and low frequency parts, there is also evident difference between snoring and non-snoring sounds on the high frequency part.
Źródło:
Archives of Acoustics; 2023, 48, 1; 3-12
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The application of time-frequency methods of acoustic signal processing in the diagnostics of tram drive components
Autorzy:
Mokrzan, Daniel
Nowakowski, Tomasz
Szymański, Grzegorz M.
Powiązania:
https://bibliotekanauki.pl/articles/27322536.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
tram drive diagnostics
time-frequency methods
short-time fourier transform
continuous wavelet transform
acoustic pressure
cepstrum
diagnostyka napędu tramwajowego
napęd tramwajowy
metody czasowo-częstotliwościowe
transformacja falkowa
ciśnienie akustyczne
Opis:
The paper presents the course of investigations and the analysis of the possibility of applying selected methods of time frequency processing of non-stationary acoustic signals in the assessment of the technical condition of tram drive components, as well as a new combined method proposed by the authors. An experiment was performed in the form of a pass-by test of the acoustic pressure generated by a Solaris Tramino S105p tram. A comparative analysis has been carried out for an efficient case and a case with damage to the traction gear of the third bogie in the form of broken gear teeth. The recorded signal was analyzed using short-time Fourier transform (STFT) and continuous wavelet transform (CWT). It was found that the gear failure causes an increase in the sound level generated by a given bogie for frequencies within the range of characteristic frequencies of the tested device. Due to the limitations associated with the fixed window resolution in STFT and the inability to directly translate scales to frequencies in CWT, it was found that these methods can be helpful in determining suspected damage, but are too imprecise and prone to errors when the parameters of both transforms are poorly chosen. A new CWT-Cepstrum method was proposed as a solution, using the wavelet transform as a pre-filter before cepstrum signal processing. With a sampling rate of 8192 Hz, a db6 mother wavelet, and a scale range of 1:200, the new method was found to infer the occurrence of damage in an interpretation-free manner. The results were validated on an independent pair of trams of the same model with identical damage and as a reference on a pair of undamaged trams demonstrating that the method can be successfully replicated for different vehicles.
Źródło:
Archives of Transport; 2023, 68, 4; 55--75
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An analysis of causal relationship between economic growth and financial development for Turkey: A MODWT-Granger causality test
Autorzy:
Abar, Hayri
Powiązania:
https://bibliotekanauki.pl/articles/2131143.pdf
Data publikacji:
2022-10-07
Wydawca:
Uniwersytet Ekonomiczny w Poznaniu
Tematy:
economic growth
Granger causality
wavelet transform
financial development
Opis:
This study aims to investigate the relationship between financial development and economic growth in different time horizons for Turkey. In this study an ensemble of wavelet analysis and Granger causality test were used. PSC was used to represent financial development and GDP was used to represent growth. The annual data used are for the period 1961–2018. The result obtained for a one year period shows that the demand-following hypothesis is valid for Turkey. Financial development is the Granger cause of growth and positively affects growth. The financial sector should be supported for growth in the short term. While there is no causal relationship for the 2–4 year period, bidirectional causality relationships were determined for the periods of 4–8 years, 8–16 years and 16–32 years. Because variables are a Granger cause of each other and affect each other in a positive direction supporting the financial sector is a preferable policy when the purpose is to achieve growth in the long run.
Źródło:
Economics and Business Review; 2022, 8, 3; 59-81
2392-1641
Pojawia się w:
Economics and Business Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analysis of the possibility of using the singular value decomposition in image compression
Autorzy:
Łukasik, Edyta
Łabuć, Emilia
Powiązania:
https://bibliotekanauki.pl/articles/38432811.pdf
Data publikacji:
2022
Wydawca:
Polskie Towarzystwo Promocji Wiedzy
Tematy:
singular value decomposition
JPEG 2000
JPEG
discrete wavelet transform
discrete cosine transform
Opis:
In today’s highly computerized world, data compression is a key issue to minimize the costs associated with data storage and transfer. In 2019, more than 70% of the data sent over the network were images. This paper analyses the feasibility of using the SVD algorithm in image compression and shows that it improves the efficiency of JPEG and JPEG2000 compression. Image matrices were decomposed using the SVD algorithm before compression. It has also been shown that as the image dimensions increase, the fraction of eigenvalues that must be used to reconstruct the image in good quality decreases. The study was carried out on a large and diverse set of images, more than 2500 images were examined. The results were analyzed based on criteria typical for the evaluation of numerical algorithms operating on matrices and image compression: compression ratio, size of compressed file, MSE, number of bad pixels, complexity, numerical stability, easiness of implementation.
Źródło:
Applied Computer Science; 2022, 18, 4; 53-67
1895-3735
2353-6977
Pojawia się w:
Applied Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Anatomical and functional assessment of patency of the upper respiratory tract in selected respiratory disorders - Part 2
Autorzy:
Zając, Andrzej
Kukwa, Andrzej
Barański, Robert
Nitkiewicz, Szymon
Zomkowska, Edyta
Rybak, Adam
Powiązania:
https://bibliotekanauki.pl/articles/2173877.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
optical diagnostic in otolaryngology
upper respiratory tract diagnostics
otolaryngology
spirometer
Fourier transform
wavelet transform
quantitative parameters of the respiratory cycle
Opis:
This article presents selected physical diagnostic methods used in otorhinolaryngology and results of their application. In addition to the applications of methods using the capabilities of selective sensors, selected methods of hybrid diagnostics were also presented - for assessment of parameters of respiratory processes, with polysomnography as an example of using both typical diagnostic methods dedicated to otolaryngology, as well as standard EEG and ECG methods. It has been shown that in some special cases of respiratory disorders, measurements of the air flow in the respiratory tract can be supplemented with pressure measurements in selected positions within the airways. The presented optical methods and diagnostic systems are very often used in the diagnosis of diseases not specific for otolaryngology occurring in the area of the head and neck. The presented material is the second part of the study discussing both standard and widely used diagnostic methods. All presented methods are dedicated to otolaryngology. This text is a continuation of the material published in No 4 of 2021 [1].
Źródło:
Metrology and Measurement Systems; 2022, 29, 3; 429--454
0860-8229
Pojawia się w:
Metrology and Measurement Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Comparative Analysis and Fusion of MRI and PET Images based on Wavelets for Clinical Diagnosis
Autorzy:
Sebastian, Jinu
King, Gnana
Powiązania:
https://bibliotekanauki.pl/articles/2200731.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
MRI
PET
multimodality medical image fusion
wavelet transform
brain tumor
Alzheimer’s disease
YUV color space
Opis:
Nowadays, Medical imaging modalities like Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), Single Photon Emission Tomography (SPECT), and Computed Tomography (CT) play a crucial role in clinical diagnosis and treatment planning. The images obtained from each of these modalities contain complementary information of the organ imaged. Image fusion algorithms are employed to bring all of this disparate information together into a single image, allowing doctors to diagnose disorders quickly. This paper proposes a novel technique for the fusion of MRI and PET images based on YUV color space and wavelet transform. Quality assessment based on entropy showed that the method can achieve promising results for medical image fusion. The paper has done a comparative analysis of the fusion of MRI and PET images using different wavelet families at various decomposition levels for the detection of brain tumors as well as Alzheimer’s disease. The quality assessment and visual analysis showed that the Dmey wavelet at decomposition level 3 is optimum for the fusion of MRI and PET images. This paper also compared the results of several fusion rules such as average, maximum, and minimum, finding that the maximum fusion rule outperformed the other two.
Źródło:
International Journal of Electronics and Telecommunications; 2022, 68, 4; 867--873
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Effective lattice structures for separable two-dimensional orthogonal wavelet transforms
Autorzy:
Puchala, Dariusz
Powiązania:
https://bibliotekanauki.pl/articles/2173687.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
two-dimensional orthogonal discrete wavelet transform
lattice structures
image processing
VLSI circuits
dwuwymiarowa ortogonalna dyskretna transformata falkowa
struktury kratowe
przetwarzanie obrazu
obwód VLSI
Opis:
Discrete two-dimensional orthogonal wavelet transforms find applications in many areas of analysis and processing of digital images. In a typical scenario the separability of two-dimensional wavelet transforms is assumed and all calculations follow the row-column approach using one-dimensional transforms. For the calculation of one-dimensional transforms the lattice structures, which can be characterized by high computational efficiency and non-redundant parametrization, are often used. In this paper we show that the row-column approach can be excessive in the number of multiplications and rotations. Moreover, we propose the novel approach based on natively two-dimensional base operators which allows for significant reduction in the number of elementary operations, i.e., more than twofold reduction in the number of multiplications and fourfold reduction of rotations. The additional computational costs that arise instead include an increase in the number of additions, and introduction of bit-shift operations. It should be noted, that such operations are significantly less demanding in hardware realizations than multiplications and rotations. The performed experimental analysis proves the practical effectiveness of the proposed approach.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 3; art. no. e141005
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Execution time prediction model for parallel GPU realizations of discrete transforms computation algorithms
Autorzy:
Puchala, Dariusz
Stokfiszewski, Kamil
Wieloch, Kamil
Powiązania:
https://bibliotekanauki.pl/articles/2173537.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
graphics processing unit
GPU
execution time prediction model
discrete wavelet transform
DWT
lattice structure
convolution-based approach
orthogonal transform
orthogonal filter banks
time effectiveness
prediction accuracy
procesor graficzny
model przewidywania czasu wykonania
dyskretna transformata falkowa
struktura sieciowa
podejście oparte na splotach
przekształcenia ortogonalne
ortogonalne banki filtrów
efektywność czasowa
dokładność przewidywania
Opis:
Parallel realizations of discrete transforms (DTs) computation algorithms (DTCAs) performed on graphics processing units (GPUs) play a significant role in many modern data processing methods utilized in numerous areas of human activity. In this paper the authors propose a novel execution time prediction model, which allows for accurate and rapid estimation of execution times of various kinds of structurally different DTCAs performed on GPUs of distinct architectures, without the necessity of conducting the actual experiments on physical hardware. The model can serve as a guide for the system analyst in making the optimal choice of the GPU hardware solution for a given computational task involving particular DT calculation, or can help in choosing the best appropriate parallel implementation of the selected DT, given the limitations imposed by available hardware. Restricting the model to exhaustively adhere only to the key common features of DTCAs enables the authors to significantly simplify its structure, leading consequently to its design as a hybrid, analytically–simulational method, exploiting jointly the main advantages of both of the mentioned techniques, namely: time-effectiveness and high prediction accuracy, while, at the same time, causing mutual elimination of the major weaknesses of both of the specified approaches within the proposed solution. The model is validated experimentally on two structurally different parallel methods of discrete wavelet transform (DWT) computation, i.e. the direct convolutionbased and lattice structure-based schemes, by comparing its prediction results with the actual measurements taken for 6 different graphics cards, representing a fairly broad spectrum of GPUs compute architectures. Experimental results reveal the overall average execution time and prediction accuracy of the model to be at a level of 97.2%, with global maximum prediction error of 14.5%, recorded throughout all the conducted experiments, maintaining at the same time high average evaluation speed of 3.5 ms for single simulation duration. The results facilitate inferring the model generality and possibility of extrapolation to other DTCAs and different GPU architectures, which along with the proposed model straightforwardness, time-effectiveness and ease of practical application, makes it, in the authors’ opinion, a very interesting alternative to the related existing solutions.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 1; e139393, 1--30
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 194

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