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An Intelligent System to Classify Epileptic and Non-Epileptic EEG signals

An Intelligent System to Classify Epileptic and Non-Epilepti...

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International IEEE conference on signal-image Technologies and Internet-Based System

作者： Emad-Ul-Haq Qazi Muhammad Hussain Hatim Aboalsamh Wadood Abdul Saeed Bamatraf Ihsan Ullah Department of Computer Science and Department of Computer Engineering King Saud University Riyadh Saudi Arabia King Saud University Riyadh Riyadh Province SA Department of Science and Technology University of Napoli ‘Parthenope’ Naples Italy

Epilepsy is a neurological disorder disease that affects more than 55 million people in the world. In this paper, we have proposed an efficient intelligent pattern recognition system for the classification of epileptic and non-epileptic electroencephalogram (EEG) signals. For this purpose, we used state-of-the-art machine learning technique, i.e., SVM (support vector machines) to classify epileptic and non-epileptic signals. Two (02) different classes of signals are used in this study, i.e., non-epileptic with open eyes and epileptic in seizure condition. One hundred (100) subjects from each class were employed for extraction of discriminatory features and classification purpose. After pre-processing of EEG signals, we use discrete wavelet transform (DWT) to decompose signals upto level 5. Then various features, i.e., energy, entropy and standard deviation are extracted from wavelet bands. Next, we use these features in the classification of signals. We achieved the classification accuracy of 100 % at delta band (0 to 3 Hz) and theta band (3 to 6 Hz). The comparisons with the previous studies show the significance of this system, which can be utilized in real-time as well as in offline clinical applications.

关键词： Feature extraction Electroencephalography Discrete wavelet transforms Support vector machines Time-frequency analysis Epilepsy Standards

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signal and image processing techniques for VLSI failure analysis

Signal and image processing techniques for VLSI failure anal...

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International conference on Informatics and Computing (ICIC)

作者： A. Boscaro S. Jacquir K. Sanchez P. Perdu S. Binczak Le2i UMR CNRS 6306 Univ. Bourgogne Franche-Comté Dijon France Centre National d'Études Spatiales Toulouse France Centre National d'Etudes Spatiales Direction des Lanceurs Paris ÃŽle-de-France FR Temasek Laboratories Nanyang Technological University Singapore

ISBN: (纸本)9781509016495

For VLSI, internal electrical measurements are key steps to solve design debug issues and to perform failure analysis. Due to multiple metal layers, active areas of the chip are only accessible from the backside of the die. The ability of optical contactless techniques to operate through the silicon substrate and the few sample preparation required have widely contributed to promote them as unavoidable tools of the defect localization workflow. Timing issue or unusual consumption can be detected by static and dynamic photon emission analysis and Electro Optical Probing. The identification of the emission spots is an essential step of the process. Due to scaling, more and more emission nodes are located within the acquisition area so that large variations of emission intensity can exist and it is difficult to recover a signal with a good signal to Noise Ratio (SNR). In this paper, automated techniques are reported to locate spots in these complex areas and to recover electrical waveforms with a good SNR. We will underline the challenge and define applications boundaries of these techniques. These techniques gives some perspectives for probing applications and allows FA community to use signal processing methods instead of expensive devices.

关键词： Laser beams Photonics wavelet transforms Very large scale integration image segmentation Failure analysis Integrated optics

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An anatomization of noise removal techniques on medical images

An anatomization of noise removal techniques on medical imag...

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International conference on Innovation and Challenges in Cyber Security (ICICCS-INBUSH)

作者： Madhulika Pandey Madhulika Bhatia Abhay Bansal Computer Science and Engineering Department Amity University Noida India

ISBN: (纸本)9781509020850

In applications of signal processing such as medicine, communications and satellites, preprocessing is considered as a vital step which focuses on reduction or removal of the level of the noise contained in the image. The process of denoising helps in preserving the finer details and useful information. Medical images like MRI, CT and X-ray contain very fine details that need to be correct and free from noise so that the information and features of interests are not lost during the diagnosis. In this paper, various noise reduction techniques such as wavelet transform, Neural Network, PCA, ICA and mean and median filters over medical images has been discussed. In this paper we tried to highlight the strength and weakness of various noise removal techniques over processing of the medical images.

关键词： Medical diagnostic imaging image edge detection Artificial neural networks Noise reduction Uncertainty Principal component analysis

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A hybrid W-transform-based coding and its VLSI realization for image compression

A hybrid W-transform-based coding and its VLSI realization f...

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IEEE International conference on Consumer Electronics (ICCE)

作者： Shen-Fu Hsiao Wen-Chen Huang Chungnan Lee Cheng-Chung Hsu Department of Health Care Management Chia-Nan College of Pharmacy and Science Taiwan Institute of Computer and Information Engineering National Sun Yat-Sen University Taiwan

ISBN: (纸本)0780343573

We propose an image compression algorithm that combines the W-transform, normalized quantization, and entropy coding to enhance the compression ratio. Experimental results show that the proposed algorithm achieves a higher compression rate compared to the JPEG and the other previously proposed W-transform based method. Since the W-transform plays an important role in multi-resolution image processing applications and is the core operation in our image compression system, we realize it on a VLSI chip in order to increase the system speed performance. The processor can compute the W-transform of any length (even or odd) in a very high throughput rate using only 8 arithmetic processing elements. The physical design of the processor based on 0.6 /spl mu/m cell library is also included.

关键词： Very-large-scale integration Data compression image coding Transform coding wavelet transforms Quantization Entropy codes image resolution Digital signal processors Digital arithmetic Systolic arrays

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A Multiplier-Less Level-3 Haar wavelet Transform Approximation Requiring Five Additions Only

A Multiplier-Less Level-3 Haar Wavelet Transform Approximati...

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Proceedings of the IEEE Dallas Circuits and Systems Workshop (DCAS)

作者： Morgana M. A. Da Rosa Guilherme Paim Henrique B. Seidel Sé rgio Almeida Eduardo A. C. Da Costa Sergio Bampi Graduate Program on Electronic Engineering and Computing Universidade Cat&#x00F3 lica de Pelotas (UCPel) Brazil Graduate Program in Microelectronics (PGMICRO) Federal University of Rio Grande do Sul (UFRGS) Brazil

ISBN: (数字)9781665498852

ISBN: (纸本)9781665498869

Approximate transform kernels have emerged as an alternative design to reduce the hardware complexity of digital signal processors by exploiting the intrinsic error resilience of many embedded consumer electronics applications such as signal, image and video processing, and computer vision. The approximate level-4 Haar wavelet transform (AxHWT-4) is the state-of-the-art approximate transform for ECG (electrocardiogram) signal processing and reduces more than nine times the energy consumption compared to the exact transform. In this work, we propose an approximate level-3 Haar wavelet transform (AxHWT-3) for increasing the hardware design efficiency with related to the AxHWT-4 while obtaining higher R-peak detection accuracy in the electrocardiogram signal. Our AxHWT-3 approximation is performed in the Haar matrix kernel to eliminate its multiplications which in the hardware design results in savings of energy consumption and VLSI hardware area. Our AxHWT3 proposal achieves an R-peak detection accuracy of more than 99% and reduces the energy consumption by 15.98 times and the VLSI area by 12.64 times compared to the exact solution (i.e., the original level-3 Haar). In addition, the proposed AxHWT3 outperforms the state-of-the-art AxHWT-4 with a savings of about 32% in power dissipation and 19.5% in VLSI area.

关键词： wavelet transforms Energy consumption Computer architecture Very large scale integration Electrocardiography signal processing Hardware

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A Refined Automatic Co-Registration Method For High-Resolution Optical and Sar images by Maximizing Mutual Information

A Refined Automatic Co-Registration Method For High-Resoluti...

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2016 IEEE International conference on signal and image processing

作者： Faycal Saidi Jie Chen Pengbo Wang School of Electronics and Information Engineering Beihang University

The use of multisensors images for different applications, like change detection and image fusion, require an image to image ***, the image registration becomes a crucial task with the continuous increase in image resolution, especially in urban *** this paper, a refined automatic Mutual Information based registration approach of spaceborne Synthetic Aperture radar(SAR) and optical image is *** data set include Terra Sar-X(1m) and Worldview-2(0.5m) images and cover urban area of San *** approach is divided into two ***, we use Discrete Canny edge detector to extract contours from the optical image, and Gabor-wavelet filter to extract edge from the SAR ***, a rigid transformation(rotation and translation) is applied to the contours image obtained by Canny ***, for each value of transformation, the Mutual Information is computed between this transformed image and the feature image outcome of application of Gaborwavelet to the SAR *** best transformation parameters are obtained when the Mutual Information is ***, in this work, we compared the proposed approach with the basic Mutual Information intensity based registration *** results obtained demonstrated that our approach improve the registration accuracy comparatively to the basic Mutual Information intensity based registration method.

关键词： image registration mutual information gabor-wavelet SAR image canny edge detector

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Duality properties for the variants of the Discrete W Transform (DWT)

Duality properties for the variants of the Discrete W Transf...

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IEEE Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER)

作者： B. N. Madhukar S. H. Bharathi School of Electronics and Communication Engineering Reva University Bengaluru India

ISBN: (数字)9781728137353

ISBN: (纸本)9781728137360

This paper gives the derivations of new duality properties for the four variants of the DWT. DWT and its variants are finite durational discrete transforms that are used in a host of applications in the fields of Digital signal processing, Digital image processing, Communication Systems, among a host of others. The Duality properties can be applied for the computation of the temporal signal from its frequency-domain counterpart or contra if and only if existing pair of DWT, including their counterparts, are known. The utility of the Duality properties lie in the abatement of computational complexity and disbursement intrinsically.

关键词： Discrete wavelet transforms Indexes Discrete transforms Discrete Fourier transforms Kernel

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A Decentralized GPS Positioning Consensus Based on Secure image Watermarking for UAV Networks

A Decentralized GPS Positioning Consensus Based on Secure Im...

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Innovative and Intelligent Information Technologies (IC3IT), International conference on

作者： Brahim Ferik Lakhdar Laimeche Abdallah Meraoumia Abdelkader Laouid Ahcene Bounceur Mostefa Kara Laboratory of Mathematics Informatics and Systems (LAMIS) University of Larbi Tebessi Tebessa Algeria Artificial Intelligence and its Applications Laboratory (LIAP) University of El Oued El Oued Algeria Information Systems Department University of Sharjah Sharjah United Arab Emirates Information & Computer Science Department King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia

ISBN: (数字)9798331541064

ISBN: (纸本)9798331541071

The popularity of Unmanned Aerial Vehicles (UAVs) in recent years has accelerated the demand for robust image security to secure communication and authenticate images or videos from usage by unauthorized parties who may seek access to sensitive information. Having unauthorized and deceptive communication, from interference in signals to data manipulation, will be a challenge. This paper presents a novel approach to integrating GPS positioning with secure image capture and decentralized coordination for UAVs. Using EI-Gamal encryption and Magic Number Fragmentation, GPS coordinates are securely encrypted, and GPS data into captured images through a hybrid Discrete wavelet Transform-Discrete Cosine Transform (DWT-DCT) watermarking technique. A consensus mechanism ensures decentralized and privacy-preserving computation of secure meeting points for UAV s. Moreover, the system maintains high image quality, with superior PSNR and SSIM values, while demonstrating resilience against signal processing and geometric attacks. These findings affirm the method's ability to extract encrypted GPS coordinates reliably, enhancing UAV network security.

关键词： Watermarking Transforms signal processing Autonomous aerial vehicles Discrete wavelet transforms Encryption Consensus protocol Discrete cosine transforms Global Positioning System Videos

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Mixed DSP/FPGA implementation of an error-resilient image transmission system based on JPEG2000

Mixed DSP/FPGA implementation of an error-resilient image tr...

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Asilomar conference on signals, Systems & Computers

作者： M. Grangetto E. Magli M. Martina F. Vacca Dipartimento di Elettronica Politechnico di Torino Center for Wireless Multimedia Communications Torino Italy

ISBN: (纸本)078037147X

This paper describes a demonstrator of an error-resilient image communication system over wireless packet networks, based on the novel JPEG2000 standard. In particular, the decoder implementation is addressed, which is the most critical task in terms of complexity and power consumption, in view of use on a wireless portable terminal for cellular applications. The system implementation is based on a mixed DSP/FPGA architecture, which allows us to parallelize some computational tasks, thus leading to efficient system operation.

关键词： Digital signal processing Field programmable gate arrays image communication Transform coding Tiles Decoding image coding Discrete wavelet transforms Multimedia systems Wireless communication

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Nonsubsampled Contourlet Transform for Texture Classifications using Support Vector Machines

Nonsubsampled Contourlet Transform for Texture Classificatio...

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IEEE International conference on Networking, Sensing and Control

作者： Shutao Li Xinmin Fu Bin Yang College of Electrical and information Engineering Hunan University Changsha China

In this paper, a new texture classification method using the nonsubsampled contourlet transform (NSCT) and support vector machines (SVMs) is proposed. The NSCT provides a shift-invariant, multiscale, and multidirectional image representation that has proven to be very efficient in image analysis applications. Firstly, features are extracted from NSCT coefficients of source images. In addition, SVMs, which have been demonstrated excellent performance as classifiers in a variety of pattern recognition problems, are used as classifiers for texture classification. The algorithm is tested on texture images from Brodatz album. Experimental results demonstrate that the proposed method produces more accurate classification results than other methods.

关键词： Support vector machines Support vector machine classification Filter bank image texture analysis image representation Feature extraction Biomedical signal processing wavelet transforms Pattern recognition Classification algorithms

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