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28 results for “wavelet decomposition”
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Research ArticleOpen accessIn the keywordsCancer Classification using Support Vector Machines and Relevance Vector Machine based on Analysis of Variance FeaturesA. Bharathi, A.M. NatarajanProblem statement: The objective of this study is, to find the smallest set of genes that can ensure highly accurate classification of cancer from micro array data by using supervised machine learning algorithms. The significance of finding the minimum subset is three fold: The computational burden and noise arising from irrelevant genes are much reduced; the cost for cancer testing … …Journal of Computer Science, Vol. 7, Issue 9 · 25 Jul 2011 · 7,593 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA New Robust Hybrid Approach to Enhance Speech in Mobile Communication SystemsManimegalai Govindan Sumithra, Keppana Gounder Thanuskodi, Bharathi DeepaProblem statement: The received voice signal in mobile communication is often disturbed by background noise and hence there is a need for good noise reduction methods for enhancing Speech. It is well known that denoising is a compromise between the removal of the largest possible amount of noise and the preservation of signal integrity. To address this issue, a new … …American Journal of Applied Sciences, Vol. 8, Issue 4 · 18 Apr 2011 · 7,299 accessesView PDFCite
Research ArticleOpen accessIn the abstractReal-Time Monitoring and Injury Risk Warning Algorithm Based on Data Fusion of Motor Muscle ContractionGuomin Wang, Jingying HuangThe existing sports injury warning algorithms are difficult to achieve dynamic injury risk modeling based on individual muscle characteristics while ensuring real-time fusion efficiency of multimodal signals. This article proposes a real-time muscle contraction state perception and injury risk warning algorithm based on adaptive weighted feature fusion and lightweight temporal modeling. The system synchronously collected surface electromyography (sEMG), Inertial Measurement … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 3 · 10 Aug 2026 · 1,089 accessesView PDFCite
Research ArticleOpen accessIn the abstractSpeaker Identification Using Discrete Wavelet TransformShanthini Pandiaraj, K. R. Shankar KumarThis study presents an experimental evaluation of Discrete Wavelet Transforms for use in speaker identification. The features are tested using speech data provided by the CHAINS corpus. This system consists of two stages: Feature extraction stage and the identification stage. Parameters are extracted and used in a closed-set text-independent speaker identification task. In this study the signals are pre-processed and … …Journal of Computer Science, Vol. 11, Issue 1 · 22 Sep 2014 · 7,429 accessesView PDFCite
Research ArticleOpen accessIn the abstractSUPER RESOLUTION FOR EGYPTSAT-1 IMAGES WITH ERRATIC SHIFTA. H. Nasr, Gh.S. El-Tawel, A. K. HelmyThe key point of the Super-Resolution (SR) process is the accurate registration of the low resolution images, i.e., accurate measuring of the fixed shift between them, to obtain high resolution image. Due to certain malfunction, some Egyptsat-1 images have inconsistent sub-pixel shift. Therefore, in this study we propose a methodology to use this kind of shift for reconstructing a SR … …Journal of Computer Science, Vol. 10, Issue 7 · 17 Jun 2014 · 6,938 accessesView PDFCite
Research ArticleOpen accessIn the abstractSPECKLE REDUCTION IN ULTRASOUND IMAGES USING NEIGHSHRINK AND BILATERAL FILTERINGR. Vanithamani, G. UmamaheswariSpeckle is a random multiplicative noise which obscures the perception and extraction of fine details in ultrasound images and speckle reduction is necessary to improve the visual quality of ultrasound images for better diagnosis. This study aims at introducing an algorithm by hybridizing bilateral filter with NeighShrink. The bilateral filter is applied before decomposition and after reconstruction of the image … …Journal of Computer Science, Vol. 10, Issue 4 · 19 Dec 2013 · 6,911 accessesView PDFCite
Research ArticleOpen accessIn the abstractEVENT-RELATED POTENTIALS EXTRACTION OF WORKING MEMORY USING WAVELET ALGORITHMSitiZubaidahMohd Tumari, Rubita Sudirman, Abdul Hamid AhmadThis study was designed to classify and determine the Event-Related Potentials (ERPs) signal pattern of normal children on visual response. Thirty-eight children aged between 10 to 12 years old were subjected to a two-phase computer-based assessment while their working memory activity was recorded using a Neurofax-EEG 9200 machine. For children, it is anticipated that some information can be lost when … …Journal of Computer Science, Vol. 10, Issue 2 · 13 Nov 2013 · 6,801 accessesView PDFCite
Research ArticleOpen accessIn the abstractA MODIFIED ADAPTIVE WAVELET SHRINKAGE SPECKLE FILTER FOR ULTRASOUND IMAGESNirmaladevi Periyasamy, Asokan RamasamyThe usage of ultrasound imaging for medical diagnosis is limited due to the presence of speckle noise. In this study Modified Adaptive Wavelet Shrinkage Filter (MAWSF) in the translational invariant domain is proposed for the removal of speckle noise. The adaptive wavelet threshold function removes the fixed bias of soft thresholding. A new inter-scale dependency model is proposed, to perform … …Journal of Computer Science, Vol. 9, Issue 10 · 16 Sep 2013 · 6,539 accessesView PDFCite
Research ArticleOpen accessIn the abstractGAUSSIAN MIXTURE MODEL BASED CLASSIFICATION OF MICROCALCIFICATION IN MAMMOGRAMS USING DYADIC WAVELET TRANSFORMSuman Mishra, Hariharan RanganathanBreast cancer is a serious health related issue for women in the world. Cancer detected at premature stages has a higher probability of being cured, whereas at advanced stages chances of survival are bleak. Screening programs aid in detecting potential breast cancer at early stages of the disease. Among the various screening programs, mammography is the proven standard for screening … …Journal of Computer Science, Vol. 9, Issue 10 · 5 Sep 2013 · 6,867 accessesView PDFCite
Research ArticleOpen accessIn the abstractWavelet Analysis and Orthogonal Moments based Classification of Microcalcification in Digital MammogramsN. V.S. Sree Rathna Lakshmi, C. ManoharanProblem statement: An important early sign of breast cancer is the clusters of micro calcifications in digital mammograms. To assist radiologists in the diagnosis of mammographic clusters a novel hybrid algorithm has been developed. Approach: A method, for detecting micro calcification in mammograms based on combined feature set with Ant Colony Optimization (ACO) was proposed. The diagonal matrix ‘S’ obtained … …Journal of Computer Science, Vol. 7, Issue 10 · 6 Aug 2011 · 6,558 accessesView PDFCite