Search Results - normal distribution ((based algorithm) OR (path algorithm))
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1
SOVA decoding in symmetric alpha-stable noise
Published 2011“…Soft-Output Viterbi Algorithm (SOVA) is one type of recovery memory-less Markov Chain and is used widely to decode convolutional codes. …”
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Conference or Workshop Item -
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Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop
Published 2016“…Log likelihood estimation technique is used to fit the best 2-parameter CDF compared to Weibull, Normal and Rician distribution model. The percentage level 5% under original bandwidth used is developed on policing and shaping algorithms to control bandwidth used. …”
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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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5
Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution: article / Nor Azura Ayop
Published 2016“…Log likelihood estimation technique is used to fitted the best 2-parameter CDF compared to WeibuII, Normal and Rician distribution model. The percentage level 5% under original bandwidth used is developed on policing and shaping algorithms to control bandwidth used. …”
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Article -
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JPEG Image Encryption Using Combined Reversed And Normal Direction-Distorted Dc Permutation With Key Scheduling Algorithm-Based Permutation
Published 2008“…The proposed approach uses a frequency domain combinational framework of coefficients scrambling with Key Scheduling Algorithm based (KSA-based) permutation. This novel algorithm applies coefficients scrambling using Combined-Reverse-and-Normal-Direction (CRND) scanning together with Distorted DC permutation (DDP). …”
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023“…This work is focused on the implementation of evolutionary based computer algorithms, genetic algorithms (GAs), on microcontrollers. …”
Conference paper -
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Optimum capacitor placement and sizing for distribution system based on an improved voltage stability index
Published 2012“…An algorithm is also proposed, based on RVSI, for optimum shunt capacitor placement in the distribution system. …”
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Article -
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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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Monograph -
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Parallel distributed computational microcontroller system for adaptive antenna downlink transmitter power optimization
Published 2023“…Parallel Distributed Genetic Algorithm (PDGA) is employed in adaptive beam forming technique to reduce power usage of adaptive antenna at WCDMA base station. …”
Article -
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Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan
Published 2015“…Directional statistics is a branch of statistics which deal with the data in angle form in which the method of analysis is different from linear data. For example, the distribution analogues to the normal distribution in linear data is known as circular normal distribution. …”
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Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah
Published 2015“…Based on the identified statistical parameters, a new Time Based Policing and Shaping algorithm is developed and simulated. …”
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Article -
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High Impedance Fault Detection on Power Distribution Feeder
Published 2012“…The algorithm for HIF detection based on the amplitude ratio of second and (3rd, 5th, 7th, 9th, 11th) harmonics to fundamental is presented. …”
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Article -
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…One of the important assumptions of the linear model is that the error terms are normally distributed. Unfortunately, many researchers are not aware that the performance of the OLS can be very poor when the data set that one often makes a normal assumption, has a heavy-tailed distribution which may arise as a result of the presence of outliers. …”
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Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah
Published 2015“…Based on the identified statistical parameters, a new Time Based Policing and Shaping algorithm is developed and simulated. …”
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Thesis -
16
Detecting High Impedance Fault in Power Distribution Feeder with Fuzzy Subtractive Clustering Model
Published 2013“…This paper presents the algorithm for HIF detection based on the amplitude of third and fifth harmonics of current, voltage and power. …”
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Article -
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Development of classification model between clean water and polluted water based on capacitance properties using Levenberg Marquardt (LM) algorithm of artificial neural network / M...
Published 2020“…For both cases, the statistical analysis data show that the p-value is more than 0.05, which indicates that the data are normally distributed. These measurement inputs were then going through the process of classification in ANN to generate the optimized models by using LM algorithm. …”
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Student Project -
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Dynamic robust bootstrap method based on LTS estimators
Published 2009“…In order to make reliable inferences about the parameters of a model, require that the parameter estimates are normally distributed. Nevertheless, in real situations, many estimates are not normal and the use of bootstrap method is more appropriate as it does not rely on the normality assumption. …”
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Article -
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Development Of Distributed Grid-Based Hydrological Model And Floodplain Inundation Management System
Published 2008“…A physical based, distributed hydrological model was developed to route overland flows during isolated HISD storms. …”
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Thesis -
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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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Monograph