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16 articles for “training sequence”
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Research ArticleOpen accessIn the keywordsAdaptive Channel Equalization Using Multiplicative Neural Network for Rayleigh Faded ChannelP. Sivakumar, N. Chithra, S. N. Sivanandam, M. RajaramProblem statement: Digital transmission over band-limited communication channel largely suffers from ISIS and various noise sources. The presence of ISI and noise causes bit errors in the received signal. Equalization is necessary at the receiver to overcome these channel impairment to recover the original transmitted sequence. Traditionally equalization is considered as equivalent to inverse filtering and implemented using linear-perform under … …Journal of Computer Science, Vol. 7, Issue 11 · 18 Aug 2011 · 6,931 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdvancing Stroke Lesion Segmentation With U-Net Variants: Classical, Transfer Learning, and MRI Sequence-Specific Customized ApproachesSonia Flora Panesar, Amit P. GanatraIschemic stroke, caused by restricted cerebral blood flow, is a leading cause of death and disability worldwide. Accurate segmentation of stroke lesions in MRI is essential for timely diagnosis but remains labor-intensive when done manually. This study presents a comparative evaluation of three U-Net variants for automated ischemic stroke lesion segmentation using the ISLES 2022 dataset: (1) Classical U-Net with … …Journal of Computer Science, Vol. 22, Issue 2 · 27 Feb 2026 · 1,791 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting of Multistep Multivariate Financial Data Through GSO Algorithm Infused Vanilla LSTM ModelNikhitha Pai, Ilango Velchamy, Nithya B RameshPredicting time series in the financial domain requires using models that can do sequence processing tasks. One such model is the LSTM model which belongs to the family of deep learning networks. The performance measure of LSTM in a regression task is to bring down the error in the predicted values. In this study, a novel fused LSTM model integrating … …Journal of Computer Science, Vol. 19, Issue 7 · 10 Jul 2023 · 6,074 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimizing N-linked Glycosylation Site Prediction in Human Proteins with Ensemble Stacking and Cross-ValidationMubina Malik, Jaimin UndaviaThe most frequent post-translational modification of proteins in all territories is glycosylation which impacts many biological activities. The most significant and critical of these modifications is N-linked glycosylation which is associated with various human diseases including diabetes cancer Inflammation Alzheimers and atherosclerosis. This article illustrates recent advances in knowledge of biology that are eventually targeting the computer science sector. Moreover-identification … …Journal of Computer Science, Vol. 20, Issue 12 · 20 Nov 2024 · 4,999 accessesView PDFCite
Research ArticleOpen accessIn the abstractEscalating SVM-Efficiency by Sequential QP LP and Slack Variable AnalysisAmit Kumar Kundu, Rezaul Karim, Ali Ahmed AveSupport Vector Machine (SVM) is a highly attractive algorithm among many machine learning models due to its generalization power and classification performance based on sound mathematical formulation being convex that offers global minimum. However, despite being sparse, its high classification cost from kernel execution with Support Vectors (SVs) reduces the user's interest when there are hard computational constraints in the … …Journal of Computer Science, Vol. 19, Issue 10 · 6 Sep 2023 · 5,913 accessesView PDFCite
Research ArticleOpen accessIn the abstractFace Verification for Person Re-Identification from Surveillance Camera and Drone-based VideosVimala Mathew, K. Ramesh, Tom Toby, Anu Mary ChackoPerson re-identification in surveillance camera videos is attracting widespread interest due to its increasing number of applications. It is being applied in the field of security, healthcare, product manufacturing, product sales and more. Though there are a variety of methods to do person re-identification, face verification-based methods are very much effective. In this study, a deep learning framework to perform … …Journal of Computer Science, Vol. 17, Issue 7 · 28 Jul 2021 · 7,317 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Support and Resistance Indicators for Stock Market with Fibonacci Sequence in Long Short-Term MemoryThambusamy Velmurugan, Thiruvalluvan IndhumathyPredictive data analytics is a branch of data analytics where models are designed that effectively interpret; anticipate outcomes by analyzing present data to make predictions about future. One of the major attributes for prediction is time and there have been a considerable number of time series analytical models that are used for forecasting. Long Short-Term Memory (LSTM) is a deep … …Journal of Computer Science, Vol. 16, Issue 10 · 28 Oct 2020 · 7,316 accessesView PDFCite
EditorialOpen accessIn the abstractCommentary-How do we Improve Training for Receptor Research?Marilee Ann BenoreThis issue of the American Journal of Biochemistry and Biotechnology features articles about receptor-ligand interactions that are critical to the wellbeing of all living organisms. The importance of the field of receptor research is supported by the large number of articles published in journals, the numerous specialty journals, the international conferences and the percentage of legal drugs on the market … …American Journal of Biochemistry and Biotechnology, Vol. 11, Issue 4 · 8 Dec 2015 · 8,056 accessesView PDFCite
EditorialOpen accessIn the abstractData Mining in Time Series: Current Study and Future TrendTan Yan, Liudmila Ulanova, Ye Ouyang, Fengyuan XuTime series represent sequences of data points where usually their order is defined by the time when they were recorded. Thus, virtually any sequential recordings can be stored as time series: Stock prices, weather conditions, physical system parameters change, product quality monitoring, etc. This leads to ubiquity of time series in all scientific and practical fields (Esling and Agon, 2012); … …Journal of Computer Science, Vol. 10, Issue 12 · 26 Jan 2015 · 8,756 accessesView PDFCite
Research ArticleOpen accessIn the abstractSymbol Timing Estimation in Multiband Orthogonal Frequency Division Multiplexing based Ultrawide band SystemM. N. Suresh, S. J. Thiruvengadam, V. AbhaikumarProblem statement: The Multiband Orthogonal Frequency Division Multiplexing (MB-OFDM) Based Ultra Wideband system (UWB) is highly susceptible to symbol timing error. Symbol timing estimation in MB-OFDM based UWB is difficult due to the presence of strongest path at delayed instant. Approach: Symbol timing estimation has two steps namely a coarse estimation and a fine estimation. In this study, a maximum … …American Journal of Applied Sciences, Vol. 9, Issue 4 · 10 Feb 2012 · 7,101 accessesView PDFCite