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Estimation of Motor Imagination Based on Consumer-Grade EEG Device 3rd

Estimation of Motor Imagination Based on Consumer-Grade EEG ...

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3rd International conference on Machine Learning for Cyber Security, ML4CS 2020

作者： Luo, Zhenzhen Hu, Zhongyi Li, Zuoyong College of Computer and Artificial Intelligence Wenzhou University Wenzhou China Intelligent Information Systems Institute Wenzhou University Wenzhou China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou China

ISBN: (纸本)9783030624590

Nowadays, classifying electroencephalogram (EEG) signals based motor imagery tasks is extensively used to control brain-computer interface applications, as a communication bridge between humans and computers. In this paper, we propose signal-to-image transformation and feature extraction methods for the classification of motor imagery. Specifically, a continuous wavelet transform is applied to decompose EEG signals into five rhythms and generate time-frequency images. Then, a gray-level co-occurrence matrix is used to extract global texture features on time-frequency images. Finally, the SVM classification model is optimized by using a grid search algorithm to select optimal parameter pairs. To confirm the validity of the proposed methods, we experimented on self-collected data, which is obtained using a consumer-grade EEG device. The experimental result showed that this proposed method can achieve an acceptable classification accuracy of 90% for a two-class problem (left/right-hand motor imagery). © 2020, Springer Nature Switzerland AG.

关键词： Electroencephalography

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A study on VLSI architectures of lifting based discrete wavelet transform

A study on VLSI architectures of lifting based discrete wave...

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International conference on Advanced Computing and Communication Systems (ICACCS)

作者： K. Indira Devi R. Shanmugalakshmi Dept. of Electrical & Electronics Engg Sri Shakthi Inst. of Engg & Tech. Coimbatore Tamilnadu India Dept. of Computer Science & Engineering/IT Government College of Technology Coimbatore Tamilnadu India

To implement new algorithm assessing the previous work is an important part of system. The aim of this paper is to give a review of VLSI architectures for efficient methods for the implementation of DWT through Lifting schemes. The lifting scheme has wide applications and advantages over the DWT. Filters are complicated because of much number of multipliers. As multiplier decide the critical computation time and power dissipation of a signal processing architecture, designing of high throughput and power efficient multiplier is a major challenge. To reduce the complexity of the architecture and to increase the performance of the system this study will deriving an efficient method.

关键词： Discrete wavelet transforms Finite impulse response filters image coding Computer architecture Filter banks

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Memory analysis and throughput enhancement for cost effective bit-plane coder in JPEG2000 applications

Memory analysis and throughput enhancement for cost effectiv...

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International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Lien-Fei Chen Tai-Lun Huang Yeong-Kang Lai Department of Electrical Engineering National Chung Hsing University Taiwan

ISBN: (纸本)0780388747

A cost effective bit-plane coder with throughput enhancement in JPEG2000 applications is proposed. Many papers and the results of chip implementation show that memory requirement dominates the hardware cost of the bit-plane coder. In order to reduce the memory size, a memory-free algorithm is proposed to eliminate state variable memories by calculating three coding state variables (/spl gamma//sub p+1/[n], /spl sigma//sub p+1/[n], and /spl pi//sub p/[n]) on the fly. We also propose a stripe-column-based pass-parallel operation to perform three coding passes in pipeline operation and to encode four samples within the stripe-column concurrently for the high throughput requirement. Experimental results show that the hardware cost and memory size of the proposed architecture is smaller than other existing architectures because of the proposed memory-free algorithm. Furthermore, the proposed architecture has 3 times greater throughput than other familiar architectures.

关键词： Throughput Costs Hardware Discrete wavelet transforms IEC standards ISO standards Pipelines Standards development image coding Entropy coding

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Robot control with graph based edge measure in real time image frames

Robot control with graph based edge measure in real time ima...

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IEEE signal processing and Communications applications (SIU)

作者： Emrah Dönmez Adnan Fatih Kocamaz Mahmut Di̇ri̇k Inonu Universitesi Malatya Malatya TR

Robotic path plan extraction is one of the major study area focused with image processing techniques except from estimation based methods, in real time robotic systems. In this study; I. First phase: It is aimed to track a mobile robot and target point by detecting start and target points in real time image frames, continually. ii. Second phase: It is aimed to exhibit a novel sensor free kinematic model to determine power ratio transferred to the left and right wheels of the robot with decision tree method by utilizing a graph based method on detected object points. Right and left wheel position, robot center and labeled target positions are acquired with thresholding method by using labels placed on robot. A graph has been created on an image by admitting all detected areas as nodes. The processes of orientating and delivering mobile robot to the target position has been modelled according to distance values of edges between wheels and target.

关键词： Robot sensing systems Mobile robots Real-time systems Wheels Path planning Cameras

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Data fusion algorithms for horticulture classification using multi-sensory satellite images

Data fusion algorithms for horticulture classification using...

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IEEE India conference (INDICON)

作者： Anand N Khobragade Mukesh M Raghuwanshi Maharashtra Remote sensing Applications Centre Nagpur India Rajiv Gandhi College of Engineering & Research Nagpur India

ISBN: (纸本)9781479953653

With the advent of numerous remote sensing sensors available for the researcher, the fusion of digital image data has become a imperative tool for classifying remote sensing image and evaluation too. Remote sensing image fusion not only improves the spatial resolution of the original multispectral image, but also improves the spectral quality of merged product. Quantitative and qualitative digital image fusion is an emerging research domain that motivates the scholars for producing high quality image with best multi-spectral capabilities. PAN Sharpened images endow with increased interpretation capabilities as data with various distinctiveness are combined and process effectively. The objective of satellite data fusion is to reduce uncertainty and minimize redundancy in the merged image while maximizing relevant details particular to remote sensing applications. Horticulture in India having great impact on agro based economy. It motivates us for carrying research as very few attempts are made in order to address the issues pertaining with horticulture application of remote sensing. Referring to the results obtained from quantitative and qualitative analysis of fused images, it is obvious that Brovey and wavelet algorithms outperformed as compared to others.

关键词： Transforms Remote sensing image fusion Algorithm design and analysis Principal component analysis Spatial resolution signal processing algorithms

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Bearing Fault image Recognition in Strong Noise Based on Optimized CNN Architecture

Bearing Fault Image Recognition in Strong Noise Based on Opt...

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image processing and Computer applications (ICIPCA), IEEE International conference on

作者： Qiang Li Haowen Gai Kaijie Hu Northeastern University Shenyang China Tianjin College University of Science and Technology Beijing Tianjin China Zhonghuan Information College Tianjin University of Technology Tianjin China

ISBN: (数字)9798350360240

ISBN: (纸本)9798350384161

To address the problem of low accuracy and poor stability of bearing diagnostic models under strong background noise, a bearing fault image recognition method is proposed that reduces the randomness of the model by avoiding the need for artificial parameterization, which can introduce random factors. This method is based on hyperparameter optimization of the GoogLeNet convolutional neural network model and decision fusion. First of all, two-dimensional wavelet time-frequency variation of the original signal of the bearing vibration to construct an image dataset, one-dimensional classification is into a two-dimensional image problem; Secondly, three lightweight convolutional neural network architectures are selected for the noise immunity test, to get the best noise-resistant network architecture GoogLeNet; Finally, hyper-parameter optimization is performed for the network, comparing the mesh method, the progressive mesh method, and the group optimization algorithm, respectively, and getting The optimal parameters are then analyzed for decision fusion and visualization of the network. To verify the method proposed in this paper, we used the open Case Western Reserve University bearing dataset. The experimental verification demonstrates that the proposed method achieves a correctness rate of 94.33% in decision fusion under noise, with good accuracy and stability.

关键词： Accuracy image recognition Computer architecture Power system stability White noise Stability analysis Robustness Classification algorithms Convolutional neural networks Optimization

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Secure Video Watermarking using Random Statistics and Combinatorial Optimization

Secure Video Watermarking using Random Statistics and Combin...

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International conference on Information and Communication Technologies: From Theory to applications, ICTTA

作者： K. Steghrarzadeh V. Gheneh Department of Electronics & Computer Eng. Barareh University of Technology Tehran Iran

Summary form only given. In this paper, we propose a novel semi-blind video watermarking scheme, where we use pseudo-random robust semi-global features of video in the three dimensional wavelet transform domain. We design the watermark sequence via solving an optimization problem, such that the features of the mark-embedded video are the quantized versions of the features of the original video. The exact realizations of the algorithmic parameters are chosen pseudo-randomly via a secure pseudo-random number generator, whose seed is the secret key, that is known (resp. unknown) by the embedder and the receiver (resp. by the public). We experimentally show the robustness of our algorithm against several attacks, such as conventional signal processing modifications and adversarial estimation attacks. We also propose a system that provides temporal synchronization in video watermarking by using side information at the receiver. Short perceptually-robust representations (also known as robust hash values) of randomly selected frames from the watermarked video regions is derived at the encoder and transmitted to the decoder. Synchronization is then achieved by computing perceptually-representative information of all frames of the received video at the receiver and finding the "best matching region" via solving a combinatorial optimization problem efficiently using dynamic programming techniques. A suitably-chosen "robust image hash" function is used to derive the necessary representative information of the video frames; the resulting hash values possess properties of being short in length, computable in real time, and similar (resp. different) for perceptually similar (resp. different) video frames with high probability. We experimentally illustrate the effectiveness of our method against several temporal de-synchronization attacks, such as random temporal interpolation, scene editing, cutting and swapping

关键词： Watermarking Statistics Robustness signal processing algorithms wavelet domain wavelet transforms Design optimization Video signal processing Decoding Dynamic programming

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Effect of Time-Frequency Representations for Fault Classification of Rolling Bearing in Noisy Conditions Using Deep Learning

Effect of Time-Frequency Representations for Fault Classific...

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Digital signal processing and its applications (DSPA), International conference on

作者： Prashant Kumar Sahu Rajiv Nandan Rai Subir Chowdhury School of Quality and Reliability Indian Institute of Technology Kharagpur Kharagpur India

Intelligent fault diagnosis techniques such as deep learning methods have gained immense attention recently for identifying bearing faults with higher accuracy and adaptability based on vibration analysis. This work proposes a fault diagnosis method for rolling bearings under extreme noise conditions based on the time-frequency representation (TFR) of signals with deep learning techniques. The bearing signals are masked with -5dB and -10dB of white Gaussian noise to create a noisy environment. Short-time Fourier transforms (STFT), Continuous wavelet transforms, and Gabor transforms (GT) are utilized to obtain spectrogram, magnitude scalogram, and constant-Q transform images to visualize the time-frequency relationship of the signal from one-dimensional vibration signals. These TFR images are directly given as input to VGG16-CNN deep learning architecture to classify the bearing faults. The effectiveness of each TFR is measured and compared based on classification accuracy. This work also studies the effect of TFR with and without overlapping the segmented signals. The case western reserve university (CWRU) standard-bearing dataset is used in this work and has achieved a satisfactory result. The result suggests that the magnitude scalogram of the vibration signal is an effective TFR that works efficiently with deep learning for bearing fault classification under different conditions, such as original signal with no added noise, -5dB and -10 dB of added noise, with an accuracy of 99.42%, 90.2 % and 85.03%, respectively when trained with 80% of the sample with 75% of the overlapping index.

关键词： Deep learning Fault diagnosis Vibrations image segmentation Time-frequency analysis Rolling bearings Noise measurement

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Implementation of edge dependent interpolation based de-interlacer on FPGA

Implementation of edge dependent interpolation based de-inte...

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IEEE signal processing and Communications applications (SIU)

作者： Mehmet Ali Çavuşlu Fuat Karakaya Alişan Balkoca KOÇ Bilgi ve Savunma Teknolojileri A.Ş. Ankara Türkiye Omer Halisdemir Universitesi Nigde TR Kağıtsokağı ArGe Ankara Türkiye

Interlacing technique aims to lower the costs of high definition video systems by reducing the data amount sent to receiver unit. Regeneration of image at the receiver unit is an important point of interlacing method. In this study, regeneration (de-interlacing) of frames that are sent to receiver unit is implemented by using edge dependent interpolation method. The method is implemented using VHDL on Altera Cyclone-ii FPGA. The method avoids reading of redundant data which yields to reduced operation time. Implementation occupies only %3 of the FPGA that is used in this study.

关键词： Field programmable gate arrays Receivers Interpolation image edge detection Cyclones High definition video Electron tubes

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Implementing Contourlet Transform for Medical image Fusion on a Heterogenous Platform

Implementing Contourlet Transform for Medical Image Fusion o...

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International conference on Scalable Computing and Communications;International conference on Embedded Computing, SCALCOM-EMBEDDEDCOM

作者： Yipeng Wei Yongxin Zhu Feng Zhao Yuehua Shi Tingting Mo Xiaoyi Ding Jie Zhong School of Microelectronics Shanghai Jiaotong University China Ruijin Hospital Shanghai Jiaotong University China

The classic wavelet transform has been applied in registration and fusion of medical images for decades. An extension namely, contourlet transform recently indicated its advantages in image fusion with better efficiency in multi-resolution and multi-direction representation and calculation. However, then even higher computational complexity it requires turns out to be a disastrous concern in embedded applications. In this paper, we implement an acceleration system on a heterogeneous TI Da Vinci dual core processor consisting of an ARM processor core and a DSP processor core. The ARM core controls the fusion procedure by extracting the luminance bits and invoking the DSP core to carry out the time-consuming part of the contourlet transform. The partitions of tasks are determined after the program is analyzed and profiled at functional level to make full use of the computational capability of the heterogeneous platform. Initial measured improved performance results are obtained and analyzed with projected further improvements.

关键词： Biomedical imaging image fusion Frequency wavelet transforms Digital signal processing Computational complexity Embedded computing Partitioning algorithms Military computing Magnetic resonance imaging

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