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Convolutional LSTM Network for Heart Disease Diagnosis on Electrocardiograms

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Computers, Materials & Continua 2023年第9期76卷 3745-3761页

作者： Batyrkhan Omarov Meirzhan Baikuvekov Zeinel Momynkulov Aray Kassenkhan Saltanat Nuralykyzy Mereilim Iglikova department of information Systems Al-Farabi Kazakh National UniversityAlmatyKazakhstan department of Mathematical and Computer modeling International Information Technology UniversityAlmatyKazakhstan department of Software Engineering Satbayev UniversityAlmatyKazakhstan

Heart disease is a leading cause ofmortality ***(ECG)play a crucial role in diagnosing heart ***,interpreting ECGsignals necessitates specialized knowledge and *** development of automated methods for ECG analysis has the potential to enhance the accuracy and efficiency of heart disease *** research paper proposes a 3D Convolutional Long Short-Term Memory(Conv-LSTM)model for detecting heart disease using ECG *** proposed model combines the advantages of both convolutional neural networks(CNN)and long short-term memory(LSTM)*** considering both the spatial and temporal dependencies of ECG,the 3D Conv-LSTM model enables the detection of subtle changes in the signal over *** model is trained on a dataset of ECG recordings from patients with various heart conditions,including arrhythmia,myocardial infarction,and heart *** results show that the proposed 3D Conv-LSTM model outperforms traditional 2D CNN models in detecting heart disease,achieving an accuracy of 88%in the classification of five ***,themodel outperforms the other state-of-the-art deep learning models for ECG-based heart disease ***,the proposedConv-LSTMnetwork yields highly accurate outcomes in identifying abnormalities in specific ECG *** proposed 3D Conv-LSTM model holds promise as a valuable tool for automated heart disease detection and *** study underscores the significance of incorporating spatial and temporal dependencies in ECG-based heart disease *** highlights the potential of deep-learning models in enhancing the accuracy and efficiency of diagnosis.

关键词： Heart disease detection classification CNN LSTM Conv-LSTM

Bayesian random Fourier filters for Gaussian noises

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Science China(information Sciences) 2018年第12期61卷 214-216页

作者： Shiyuan WANG Wanli WANG Shukai DUAN Lidan WANG Chi K.TSE College of Electronic and information Engineering Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent information processing department of Electronic and information Engineering Hong Kong Polytechnic University

Dear editor,Signal processing algorithms are generally used to identify an unknown system, and can be classified as batch algorithms and online learning algorithms(OLAs). Batch algorithms are applied to offline scenar... 详细信息

关键词： Bayesian random Fourier filters for Gaussian noises

Face recognition using illuminant locality preserving projections

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Journal of Beijing Institute of Technology 2011年第1期20卷 111-116页

作者：刘朋樟沈庭芝林健文 School of information and Electronics Beijing Institute of Technology Centre for Signal processing Department of Electronic and Information EngineeringHong Kong Polytechnic University

A novel supervised manifold learning method was proposed to realize high accuracy face recognition under varying illuminant conditions. The proposed method, named illuminant locality preserving projections （ILPP）, exploited illuminant directions to alleviate the effect of illumination variations on face recognition. The face images were first projected into low dimensional subspace, Then the ILPP translated the face images along specific direction to reduce lighting variations in the face. The ILPP reduced the distance between face images of the same class, while increase the dis tance between face images of different classes. This proposed method was derived from the locality preserving projections （LPP） methods, and was designed to handle face images with various illumi nations. It preserved the face image＇ s local structure in low dimensional subspace. The ILPP meth od was compared with LPP and discriminant locality preserving projections （DLPP）, based on the YaleB face database. Experimental results showed the effectiveness of the proposed algorithm on the face recognition with various illuminations.

关键词： locality preserving projections ( LPP ) illuminant direction illuminant locality preser ving projections (ILPP) face recognition

More relaxed condition for dynamics of discrete time delayed Hopfield neural networks

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Chinese Physics B 2008年第1期17卷 125-128页

作者：张强 Liaoning Key Laboratory of Intelligent information processing Dalian University

The dynamics of discrete time delayed Hopfield neural networks is investigated. By using a difference inequality combining with the linear matrix inequality, a sufficient condition ensuring global exponential stability of the unique equilibrium point of the networks is found. The result obtained holds not only for constant delay but also for time-varying delays.

关键词： discrete time delayed Hopfield neural networks difference inequality

A Regularized Super Resolution Algorithm for Generalized Gaussian Noise

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Journal of Donghua University(English Edition) 2010年第1期27卷 25-35页

作者：陈文方向忠刘立峰蒋伟丁大为乔艳涛 Institute of Image Communication and information processing Shanghai Jiaotong University Computer and information department Shanghai University of Electric Power Key Lab oratory of Intelligent Computing & Signal processing Ministry of EducationAnhui University

In this paper,an iterative regularized super resolution (SR) algorithm considering non-Gaussian noise is *** on the assumption of a generalized Gaussian distribution for the contaminating noise,an lp norm is adopted to measure the data fidelity term in the cost *** the meantime,a regularization functional defined in terms of the desired high resolution (HR) image is employed,which allows for the simultaneous determination of its value and the partly reconstructed image at each iteration *** convergence is thoroughly *** results show the effectiveness of the proposed algorithm as well as its superiority to conventional SR methods.

关键词： super resolution generalized p-Gaussian distribution regularization parameter

Model Predictive Control for Vapor Compression Cycle of Refrigeration Process

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International Journal of Automation and computing 2018年第6期15卷 707-715页

作者： Xiao-Hong Yin Shao-Yuan Li department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China

A model predictive controller based on a novel structure selection criterion for the vapor compression cycle （VCC） of refrigeration process is proposed in this paper. Firstly, those system variables are analyzed which exert significant influences on the system performance. Then the structure selection criterion, a trade-off between computation complexity and model performance, is applied to different model structures, and the results are utilized to determine the optimized model structure for controller design. The controller based on multivariable model predictive control （MPC） strategy is designed, and the optimization problem for the reduced order models is formulated as a constrained minimization problem. The effectiveness of the proposed MPC controller is verified on the experimental rig.

关键词： Vapor compression refrigeration cycle model structure structure selection criterion model reduction model predictive control.

Principal basis analysis in sparse representation

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Science China(information Sciences) 2017年第2期60卷 199-201页

作者： Hong SUN Chengwei SANG Chenguang LIU School of electronic information Wuhan University department Signal and Image processing Telecom ParisTech department of Scientific Research Air Force Early Warning Academy

We propose a principal basis analysis(PBA)method over a learned overcomplete basis set(called dictionary).The proposed PBA makes use of a novel criterion:the frequency of basis vector(atom of the dictionary)over a data *** proposed criterion is well adapted to sparse signal *** it adapts to an intrinsic characteristic of the regularity of signals.

关键词： PSNR Figure PBA SAR

Bipartite consensus problem on matrix-valued weighted directed networks

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Science China(information Sciences) 2021年第4期64卷 229-231页

作者： Lulu PAN Haibin SHAO Yugeng XI Dewei LI department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and information processing Ministry of Education

Dear editor,Consensus turns out to be an important paradigm in coordination of multi-agent systems [1]. Previous studies largely concentrate on consensus problem over networks where the weights on edges are scalars, which cannot completely characterize the correlation of different dimensions corresponding to the state of an agent in the network.

关键词： information Systems and Communication Service

Soft-Sensing Method with Online Correction Based on Semi-Supervised Learning

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Journal of Shanghai Jiaotong university(Science) 2015年第2期20卷 171-176页

作者：汤奇峰李德伟席裕庚 department of Automation Key Laboratory of System Control and information processing of Ministry of Education Shanghai Jiaotong University

Soft sensing has been widely used in chemical industry to build an online monitor of the variables which are unmeasurable online or measurable online but with a high cost. One inherent difficulty is insufficiency of the training samples because the labeled data are limited. Besides, the traditional soft-sensing structure has no online correction mechanism. The forecasting result may be incorrect if the working condition is changed. In this work, a semi-supervised learning(SSL) method is proposed to build the soft-sensing model by use of the unlabeled data. Meanwhile, an online correction mechanism is proposed to establish a soft-sensing approach. The mechanism estimates the input variables at each step by a prediction model and calibrates the output variables by a compensation model. The experimental results show that the proposed method has better prediction accuracy and generalization ability than other approaches.

关键词： soft-sensing semi-supervised learning(SSL) online correction neural network