检索结果-南通市图书馆

Attention-Based CNN Fusion Model for Emotion Recognition During Walking Using discrete wavelet transform on EEG and Inertial Signals

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Big Data Mining and Analytics 2024年第1期7卷 188-204页

作者： Yan Zhao Ming Guo Xiangyong Chen Jianqiang Sun Jianlong Qiu School of Communication Engineering Hangzhou Dianzi UniversityHangzhou 310018China School of Automation and Electrical Engineering Linyi UniversityLinyi 276000China

Walking as a unique biometric tool conveys important information for emotion *** in different emotional states exhibit distinct walking *** this purpose,this paper proposes a novel approach to recognizing emotion during walking using electroencephalogram(EEG)and inertial *** recognition of emotion is achieved by training in an end-to-end deep learning fashion and taking into account multi-modal *** wear virtual reality head-mounted display(VR-HMD)equipment to immerse in strong emotions during *** environment shows excellent imitation and experience ability,which plays an important role in awakening and changing *** addition,the multi-modal signals acquired from EEG and inertial sensors are separately represented as virtual emotion images by discrete wavelet transform(DWT).These serve as input to the attention-based convolutional neural network(CNN)fusion *** designed network structure is simple and lightweight while integrating the channel attention mechanism to extract and enhance *** effectively improve the performance of the recognition system,the proposed decision fusion algorithm combines Critic method and majority voting strategy to determine the weight values that affect the final decision *** investigation is made on the effect of diverse mother wavelet types and wavelet decomposition levels on model performance which indicates that the 2.2-order reverse biorthogonal(rbio2.2)wavelet with two-level decomposition has the best recognition *** experiment results show that the proposed method outperforms other existing state-of-the-art works with an accuracy of 98.73%.

关键词： walking multi-modal fusion virtual reality emotion recognition discrete wavelet transform attention mechanism

Walsh Hadamard transform Based Transceiver Design for SC-FDMA with discrete wavelet transform

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

China Communications 2017年第5期14卷 193-206页

作者： Arsla Khan Amna Arif Tabassum Nawaz Sobia Baig Department of Electrical Engineering COMSATS Institute of Information TechnologyLahore Pakistan

This article proposes a new transceiver design for Single carrier frequency division multiple access(SCFDMA)system based on discrete wavelet transform(DWT). SCFDMA offers almost same structure as Orthogonal frequency division multiple access(OFDMA)with extra advantage of low Peak to Average Power Ratio(PAPR). Moreover,this article also suggests the application of Walsh Hadamard transform(WHT)for linear precoding(LP)to improve the PAPR performance of the system. Supremacy of the proposed transceiver over conventional Fast Fourier transform(FFT)based SCFDMA is shown through simulated results in terms of PAPR,spectral efficiency(SE)and bit error rate(BER).

关键词： multicarrier modulation orthogonal frequency division multiple access single carrier frequency division multiple access: fast Fourier transform discrete wavelet transform Walsh Hadamard transform

Low complexity reconfigurable architecture for the 5/3 and 9/7 discrete wavelet transform

在线全文

学校读者我要写书评

暂无评论

Journal of Systems Engineering and Electronics 2006年第2期17卷 303-308页

作者： Xiong Cheng yi Tian Jinwen Liu Jian Coll. of Electronic Information Engineering South Center Univ. for Nationalities Wuhan 430074 P.R. China Inst. of Pattern Recognition & Artificial Intelligence Key Lab. of Education Ministry for Image Processing and Intelligent Control Huazhong Univ. of Science & Technology Wuhan 430074 P.R. China

Efficient reconfigurable VLSI architecture for 1-D 5/3 and 9/7 wavelet transforms adopted in JPEG2000 proposal, based on lifting scheme is proposed. The embedded decimation technique based on fold and time multiplexing, as well as embedded boundary data extension technique, is adopted to optimize the design of the architecture. These reduce significantly the required numbers of the multipliers, adders and registers, as well as the amount of accessing external memory, and lead to decrease efficiently the hardware cost and power consumption of the design. The architecture is designed to generate an output per clock cycle, and the detailed component and the approximation of the input signal are available alternately. Experimental simulation and comparison results are presented, which demonstrate that the proposed architecture has lower hardware complexity, thus it is adapted for embedded applications. The presented architecture is simple, regular and scalable, and well suited for VLSI implementation.

关键词： VLSI discrete wavelet transform lifting scheme embedded decimation reeonfigurable.

Detection and recognition of veterinary drug residues in beef using hyperspectral discrete wavelet transform and deep learning

在线全文

学校读者我要写书评

暂无评论

International Journal of Agricultural and Biological Engineering 2022年第1期15卷 224-232页

作者： Rongchang Jiang Jingxin Shen Xinran Li Rui Gao Qinghe Zhao Zhongbin Su College of Electrical and Information Northeast Agricultural UniversityHarbin 150030China Shandong Academy of Agricultural Machinery Sciences Jinan 250100China Harbin Big Data Center Harbin 150030China

A fast,non-destructive recognition method for veterinary drug residues in beef was proposed to mitigate the laborious sample preparation and long detection times associated with conventional chemical detection *** beef samples free of veterinary drug residues and four groups of beef sprayed with relevant concentrations of metronidazole,ofloxacin,salbutamol,and dexamethasone under ambient conditions were analyzed by 400-1000 nm hyperspectral imaging followed by multiplicative scatter correction *** dimension reduction was performed using Competitive Adaptive Reweighted Sampling(CARS),Principal Component Analysis(PCA),and discrete wavelet transform(DWT)based on Haar,db3,bior1.5,sym5,and rbio1.3 wavelet basis *** data were subjected to Convolutional Neural Network(CNN),Multilayer Perceptron(MLP),Random Forest(RF),and Support Vector Machine(SVM)***,MLP,SVM,and RF algorithms achieved overall accuracies of 91.6%,88.6%,87.6%,and 86.2%,respectively,when combined with DWT(wavelet basis functions and numbers of transform layers being Haar-4,db3-2,bior1.5-4,and sym5-3,respectively).The algorithm Kappa coefficients(0.89,0.86,0.85,and 0.83,respectively)and time consumption for prediction(140.60 ms,57.85 ms,70.67 ms,and 87.16 ms,respectively)were also superior to models based on CARS and *** combined with deep learning can shorten prediction times,considerably improve the accuracy of classification and recognition,and alleviate the Hughes phenomenon,thus providing a new method for the fast,non-destructive detection and recognition of veterinary drug residues in beef.

关键词： hyperspectral beef veterinary drug residues discrete wavelet transform convolutional neural network deep learning

Interpolation of Images Using discrete wavelet transform to Simulate Image Resizing as in Human Vision

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

International Journal of Automation and computing 2010年第1期7卷 9-16页

作者： Rohini S. Asamwar Kishor M. Bhurchandi Abhay S. Gandhi Department of Electronics and Communication Engineering Shri Ramdeobaba Kamla Nehru Engineering College Department of Electronics and Computer Science Visvesvaraya National Institute of Technology

This paper presents discrete wavelet transform （DWT） and its inverse （IDWT） with Haar wavelets as tools to compute the variable size interpolated versions of an image at optimum computational load. As a human observer moves closer to or farther from a scene, the retinal image of the scene zooms in or out, respectively. This zooming in or out can be modeled using variable scale interpolation. The paper proposes a novel way of applying DWT and IDWT in a piecewise manner by non-uniform down- or up-sampling of the images to achieve partially sampled versions of the images. The partially sampled versions are then aggregated to achieve the final variable scale interpolated images. The non-uniform down- or up-sampling here is a function of the required scale of interpolation. Appropriate zero padding is used to make the images suitable for the required non-uniform sampling and the subsequent interpolation to the required scale. The concept of zeroeth level DWT is introduced here, which works as the basis for interpolating the images to achieve bigger size than the original one. The main emphasis here is on the computation of variable size images at less computational load, without compromise of quality of images. The interpolated images to different sizes and the reconstructed images are benchmarked using the statistical parameters and visual comparison. It has been found that the proposed approach performs better as compared to bilinear and bicubic interpolation techniques.

关键词： discrete wavelet transform nomuniform sampling zeroeth level discrete wavelet transform (DWT) interpolation human vision.

Coupling denoising algorithm based on discrete wavelet transform and modified median filter for medical image

在线全文

学校读者我要写书评

暂无评论

Journal of Central South University 2019年第1期26卷 120-131页

作者： CHEN Bing-quan CUI Jin-ge XU Qing SHU Ting LIU Hong-li College of Physics and Electromechanical Engineering Jishou University College of Information Science and Engineering Jishou University College of Electrical and Information Engineering Hunan University

In order to overcome the phenomenon of image blur and edge loss in the process of collecting and transmitting medical image,a denoising method of medical image based on discrete wavelet transform(DWT)and modified median filter for medical image coupling denoising is *** method is composed of four modules:image acquisition,image storage,image processing and image *** acquisition gets the medical image that contains Gaussian noise and impulse *** storage includes the preservation of data and parameters of the original image and processed *** the third module,the medical image is decomposed as four sub bands(LL,HL,LH,HH)by wavelet decomposition,where LL is low frequency,LH,HL,HH are respective for horizontal,vertical and in the diagonal line high frequency *** improved wavelet threshold to process high frequency coefficients and retain low frequency coefficients,the modified median filtering is performed on three high frequency sub bands after wavelet threshold *** last module is image reconstruction,which means getting the image after denoising by wavelet *** advantage of this method is combining the advantages of median filter and wavelet to make the denoising effect better,not a simple combination of the two previous *** DWT and improved median filter coefficients coupling denoising,it is highly practical for high-precision medical images containing complex *** experimental results of proposed algorithm are compared with the results of median filter,wavelet transform,contourlet and DT-CWT,*** to visual evaluation index PSNR and SNR and Canny edge detection,in low noise images,PSNR and SNR increase by 10%–15%;in high noise images,PSNR and SNR increase by 2%–6%.The experimental results of the proposed algorithm achieved better acceptable results compared with other methods,which provides an important method for the diagnosis of medical condition.

关键词： medical image image denoising discrete wavelet transform modified median filter coupling denoising

A New Segmentation Method of CR Images Based on discrete wavelet transform and Mathematics Morphology

在线全文

学校读者我要写书评

暂无评论

A New Segmentation Method of CR Images Based on Discrete Wav...

Research on Digital Watermarking Technology Based on discrete wavelet transform

20th Congress of the International Commission for Optics

作者： LI Zhea,b and . HUANG Lian-qingaa Changchun Institute of Optics ,Fine Mechanics and Physics of Chinese Academy of Sciences,Changchun, China b Postgraduate School of Chinese Academy of Sciences, Beijing, China

In this paper, we propose a segmentation method of CR(computed radiography) images with being rid of under-segmentation and over-segmentation. An under-segmentation occurs when pixels belonging to dif

关键词： Watershed Algorithm Under-segmentation discrete wavelet transform CR image Over-segmentation

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

Research on Digital Watermarking Technology Based on Discret...

Stator Fault Diagnosis of Induction Motor Based on discrete wavelet Analysis and Neural Network Technique

作者： Dingying Tan Huiling Liu Huili Wang Min Zou Pingping Chen School of Medical Information Engineering Guangzhou University of Chinese Medicine

By using the advantages of discrete wavelet transform in digital watermark embedding,extraction and detection,a corresponding basic model was *** MATLAB as a tool for simulation experiments,the experimental results show that the discrete wavelet transform can extract the watermark signal under the common JPEG compression,noise,shear and rotation,filtering and other attacks,and has high robustness.

关键词： Digital watermarking discrete wavelet transform Robustness

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

Chinese Journal of Electrical Engineering 2023年第1期9卷 142-157页

作者： Abdelelah Almounajjed Ashwin Kumar Sahoo Mani Kant Kumar Sanjeet Kumar Subudhi Electrical Engineering Department C.V Raman Global UniversityBhubaneswar 752054India Electronics and Communication Engineering Department C.V Raman Global UniversityBhubaneswar 752054India

A novel approach by introducing a statistical parameter to estimate the severity of incipient stator inter-turn short circuit(ITSC)faults in induction motors(IMs)is *** the incipient ITSC fault and its severity is challenging for several *** stator currents in the healthy and faulty cases are highly similar during the primary stage of the ***,the conventional statistical parameters resulting from the analysis of fault signals do not consistently show a systematic variation with respect to the increase in fault *** objective of this study is the early detection of incipient ITSC ***,it aims to determine the percentage of shorted turns in the faulty phase,which acts as an indicator for severe damage to the stator *** of the motor in healthy and defective cases is performed using the Clarke Concordia transform.A discrete wavelet transform is applied to the motor currents using a Daubechies-8 *** statistical parameters L1 and L2 norms are computed for the detailed *** parameters are obtained under a variety of loads and defects to acquire the most accurate and generalized features related to the *** L1 and L2 norms creates a novel statistical parameter with notable characteristics to achieve the research *** artificial neural network-based back propagation algorithm is employed as a classifier to implement the classification *** classifier output defines the percentage of defective turns with a high level of *** competency of the adopted methodology is validated via simulations and *** results confirm the merits of the proposed method,with a classification test correctness of 95.29%.

关键词： discrete wavelet transform induction motor inter-turn short circuit fault neural networks statistical parameters