Search Results - (( data normalization based algorithm ) OR ( parallel estimation using algorithm ))
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1
Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui
Published 2016“…Sensitivity Encoding (SENSE) is a widely used technique to reconstruct the artefact free images from the Parallel MRI (pMRI) aliased data. …”
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2
Forward masking threshold estimation using neural networks and its application to parallel speech enhancement
Published 2010“…Moreover, a parallel implementation of the speech enhancement algorithm was developed using Matlab parallel computing toolbox.…”
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Parallel visualization approach of a 3D heart model
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A parallel genetic algorithm-based TSK-Fuzzy system for dynamic car-following modeling
Published 2009“…This paper presents the application of Parallel Genetic Algorithm (PGA)-based Takagi Sugeno Kang (TSK)-Fuzzy approach for dynamic car-following modeling in the traffic simulation software. …”
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5
New algorithm for gyroless spacecraft angular rate Estimation and its application
Published 2006“…A new algorithm for estimating the angular velocity using quaternion measurements is developed based on the concept of the global optimality resulting when using a centralized or master Kalman filter. …”
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6
Digital quadrature compensators scheme for analog imperfections of quadrature modulator in wireless communication systems
Published 2016“…Adaptive algorithms used to estimate the QM’s imperfections, operate either in online or offline mode. …”
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A bit-serial sum of absolute difference accelerator for variable block size motion estimation of H.264
Published 2009“…The proposed hardware accelerator can be used in different disciplines from low bit rate to high bit rate by making a tradeoff between the degree of parallelism or using fast algorithm or a combination of both.…”
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9
Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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10
Early detection of breast cancer using wave elliptic equation with high performance computing
Published 2008“…This paper focuses on the implementation of parallel algorithm for the simulation of breast cancer tumor using two dimensional Helmholtz’s wave equation on a distributed parallel computer system (DPCS). …”
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11
Resource Minimization in a Real-time Depth-map Processing System on FPGA
Published 2011“…Depth-map algorithm allows camera system to estimate depth. It is a computational intensive algorithm, but can be implemented with high speed on hardware due to the parallelism property. …”
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12
Classification of Cardiac Disorders Based on Electrocardiogram Data with Fuzzy Cognitive Map (FCM) Algorithm Approach
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13
Conjunctions in biological neural architectures for visual pose estimation / Tom´As Maul
Published 2006“…As each level is traversed, a biological plausibility argument is gradually strengthened. At the algorithmic level, several approaches for solving the pose estimation problem are compared in terms of their neural implementability. …”
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14
The effect of dose calculation algorithms on the normal tissue complication probability values of thoracic cancer
Published 2015“…Purpose: To identify the effect of dose calculation algorithms on the Normal Tissue Complication Probability values of thoracic cancer. …”
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A study on advanced statistical analysis for network anomaly detection
Published 2005“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price
Published 2014“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma
Published 2017“…In addition, the algorithm was relatively easy to understand compare to the state of the art of normal parameter reduction algorithm. …”
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18
Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…Even a normal people using clustering to grouping their data. …”
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19
An improved recommender system based on normalization of matrix factorization and collaborative filtering algorithms
Published 2015“…The hypothesis is that the tendency of normalization technique to simplify the data combined with the accuracy of the neighborhood models can improve the accuracy of the RS. …”
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