Search Results - (( developing square path algorithm ) OR ( java application using algorithm ))
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All-pass filtered x least mean square algorithm for narrowband active noise control
Published 2018“…Most available ANC uses the secondary path modelling including filtered x least mean square (FxLMS) algorithm. …”
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Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control
Published 2016“…Filtered-X least mean square (FXLMS) control algorithm is a conventional algorithm employed to cancel the noise in linear environment. …”
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Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score
Published 2021“…The warppartial least square method was utilized to estimate the multi-layer hypothesized path model. …”
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4
RSA Encryption & Decryption using JAVA
Published 2006“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Performance comparison of THF-NLFXLMS and VFXLMS algorithms for Hammerstein NANC
Published 2016“…In addition, the computational complexity is relatively small compared to other direct nonlinear adaptive algorithm like the Volterra filter. In this paper, the performance of THF-NLFXLMS algorithm for Hammerstein secondary path structure is quantified and compared with NLFXLMS and the Volterra Filtered-x Least Mean Squares (VFXLMS) algorithm of similar computational complexity. …”
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Provider independent cryptographic tools
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Development of a State-Space Observer for Active Noise Control Systems
Published 2009“…The secondary path of the ANC system is modeled by using the LMS algorithm to complete the design of the Filtered-X Least Mean Square (FXLMS) controller. …”
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10
Coordinate-Descent Adaptation over Hamiltonian Multi-Agent Networks
Published 2021“…The incremental least-mean-square (ILMS) algorithm is a useful method to perform distributed adaptation and learning in Hamiltonian networks. …”
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Developing and validating a simulation model for counting and classification of vehicles
Published 2016“…Also, the classification of vehicles was performed using the improfile command in Matlab-Video Image Processing that computes the intensity values along a line or a multiline path in an image. The algorithm program was developed to detect vehicles in traffic videos and get the vehicle count for the small time period as an assistance tool for a researcher who seeks vehicle counting.…”
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Real-Time Video Processing Using Native Programming on Android Platform
Published 2012“…However for the Android platform that based on the JAVA language, most of the software algorithm is running on JAVA that consumes more time to be compiled. …”
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Direct approach for mining association rules from structured XML data
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Performance comparison of LFXLMS, MOVFXLMS and THF-NLFXLMS algorithms for Hammerstein NANC
Published 2016“…Filtered-X least mean square (FXLMS) algorithm is widely used in active noise control (ANC) systems when the secondary path is linear. …”
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A review on path collisions and resources usage in hybrid optical network on chip (HONoC)
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Real-time algorithmic music composition application.
Published 2022“…This project is about the study of evolutionary music, and focuses on the development of an algorithmic music composer using the Java programming language. …”
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…We hyave used the CPU profiler of Oracle JavaTM VisualVM to monitor the execution of LRE-TL as well as USG algorithms. …”
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Application of genetic algorithm and JFugue in an evolutionary music generator
Published 2025“…This project explores the application of Genetic Algorithms (GA) with JFugue, which is a Java-based music programming library to develop an Evolutionary Music Generator. …”
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Collision avoidance mechanisms using artificial potential field for UAVs
Published 2025“…To evaluate algorithmic performance, three simulated scenarios were developed: (i) varying obstacle densities, (ii) extreme goal positioning, and (iii) external wind disturbances. …”
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