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Kalyan G.,Indian Institute of Technology Hyderabad | Srinivas M.B.,Electronics and Communication Engineering
IEEE Asia-Pacific Conference on Circuits and Systems, Proceedings, APCCAS | Year: 2010

An Input Output (IO) Buffer for memory Interface is proposed with the concept of a merged driver which helps in improving the linearity of the driver with a reduced area. A novel calibration scheme is proposed which can adjust larger driver resistance and termination impedance changes for temperature and voltage drifts in a fewer cycles of system clock which will improve the valid data window. © 2010 IEEE. Source

Sirajudeen A.,Electronics and Communication Engineering | Ezhilarasi M.,Kumaraguru College of Technology
Current Medical Imaging Reviews | Year: 2015

Diabetic Retinopathy (DR) is the most common disease induced by the complication of diabetes, causing blindness. In many rural areas, the contributions of ophthalmologists are predicatively less to treat the disease. Detection of lesions in the early stage is a progressive measure to diagnose DR. Initially, a preprocessing method is performed to detect the Optic Nerve Head (ONH) in the lesion. Based on the degree of reflectance in ONH, feature extraction is computed using multi-scale Local Binary Pattern (LBP) algorithm. Here, Gabor convolution is estimated and the structure of ONH is encoded. This extends to a statistical computation in terms of the moment and standard deviation. A Support Vector Machine (SVM) classification is formulated to locate the hemorrhages and exudates and an effective probabilistic multi-label lesion classification is performed to acquire five sets of results representing the diabetic retinopathy: 1) Grade-1 Exudates, 2) Grade-2 Exudates, 3) Micro aneurysms, 4) Hemorrhages, 5) Neovascularization. Finally, the affected area of lesions is used to diagnose the disease. © 2015 Bentham Science Publishers. Source

Suryavanshi P.,Electronics and Communication Engineering
Global Conference on Communication Technologies, GCCT 2015 | Year: 2015

Image fusion is gaining momentum in the research community with the aim of combining all the important information from multiple images such that the fused image contains more accurate and comprehensive information than that contained in the individual input images. In this paper, it is proposed to fuse multifocus images to get 'all-in-focus' in the wavelet domain using biorthogonal wavelets. To compute fused pixel value, weighted average of the source pixels is taken, where the weight to be given to the pixel is adaptively decided by establishing parent-child relationship among the pixels at different levels of multiresolution decomposition. Two important properties wavelet symmetry and linear phase of biorthogonal wavelets have been exploited for image fusion because they are capable to preserve edge information and hence reducing the distortions in the fused image. The performance of the proposed method have been extensively tested on several pairs of multifocus images and also compared quantitatively with five recently proposed methods with the help of well-known parameters including Petrovic parameters. Results show that the major achievement of this work is that it significantly increases the quality of the fused image, both visually and in terms of standard Petrovic parameters. © 2015 IEEE. Source

Koc T.,Electronics and Communication Engineering
Electronics Letters | Year: 2015

Estimation of glottal flow waveform from speech requires recording of low-frequency sounds down to DC level. It causes a low-frequency noise or bias in the reconstructed glottal flow waveform. Removing this bias by linear highpass filtering (HPF) degrades the shape of glottal flow waveform. A nonlinear method based on empirical mode decomposition is proposed for removing the bias without using HPF while preserving the shape of the glottal flow waveform. The biased glottal flow waveform is decomposed into its intrinsic modes, then the low-frequency bias is estimated by using the higher modes. Glottal flow waveform is reconstructed by subtracting the bias in the time domain. The results show that the proposed method accurately estimates the bias and yields significantly better glottal flow waveforms than the conventional HPF method. © The Institution of Engineering and Technology 2015. Source

Helal A.E.,Virginia Polytechnic Institute and State University | Bayoumi A.M.,Electronics and Communication Engineering | Hanafy Y.Y.,Virginia Polytechnic Institute and State University
Proceedings - Design Automation Conference | Year: 2015

This paper discusses the development of a parallel SPICE circuit simulator using the direct method on a cloud-based heterogeneous cluster, which includes multIPle HPC compute nodes with multi-sockets, multicores, and GPUs. A simple model is derived to optimally partition the circuit between the compute nodes. The parallel simulator is divided into four major kernels: Partition Device Model Evaluation (PME), Partition Matrix Factorization (PMF), Interconnection Matrix Evaluation (IME), and Interconnection Matrix Factorization (IMF). Another model is derived to assign each of the kernels to the most suitable execution platform of the Amazon EC2 heterogeneous cloud. The partitioning approach using heterogeneous resources has achieved an order-of-magnitude speedup over optimized multithreaded implementations of SPICE using state of the art KLU and NICSLU packages for matrix solution. © 2015 ACM. Source

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