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Showing 1 to 20 of 548 for “"learning algorithm"”.
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Contributions to statistical machine learning algorithm
… written as contributions to statistical machine learning algorithm literature.
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An online learning algorithm for technical trading
We use an adversarial expert based online learning algorithm to learn the optimal parameters required to maximise wealth trading zero-cost portfolio strategies. The learning algorithm is used to determine the relative population dynamics of technical trading strategies that can survive historical …
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A constructive learning algorithm based on back-propagation
… upon the design and implementation of a dynamic algorithm based on the Back-Propagation learning algorithm. The algorithm constructs a single hidden layer as the learning process proceeds using individual pattern error as the basis of unit insertion. This algorithm is applied to several problems …
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Advanced therapy learning algorithm for spinal cord stimulation
… accordingly, a tri-axial accelerometer based algorithm has been developed. The algorithm enables patients to adjust stimulation therapy parameters real-time, associates the patient indicated parameters with a vector, and stores them in a therapy library. Stimulation therapy parameters are then …
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Predicting the Price of Cryptocurrency Using Machine Learning Algorithm
… than ethereum as well. We propose to use Machine Learning for this project, which will be trained from the available cryptocurrency price data, to gain intelligence, and then use this knowledge to make accurate predictions. Trading cryptocurrency prices is one of the most popular exchanges right …
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Online learning algorithm for structural control using magnetorheological actuators
… instabilities. To address the problem, learning algorithms using offline learning have been proposed in order to have the structure learn its behaviour, but they can be perceived as unrealistic because earthquake data can hardly be produced to train these schemes. Here, an algorithm …
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Physics Guided Machine Learning algorithm for MAX-DOAS retrieval
… it almost impossible to design an inversion algorithm providing a definite solution. A possible way to find a low-error inversion algorithm is incorporating the machine learning (ML) technique into the MAX-DOAS retrieval. This dissertation serves as the author's exploration of designing such …
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A New Machine Learning Algorithm for Detection of Stray Clays
This paper discusses various machine learning algorithms utilized with Ground Penetrating Radar (GPR) for differentiating between clay seam number 414 and stray clays in potash mines to evaluate mine-room safety. Although different strategies have been used to find and recognize anomalies from GPR …
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Unsupervised Learning Algorithm for Noise Suppression and Speech Enhancement Applications
… computational complexity of speech enhancement algorithms is high, along with its power consumption requirements. However, if the device under consideration is small with limited power and computational capabilities, having multiple microphones is not possible. For example, hearing aids and …
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MACHINE LEARNING ALGORITHM PERFORMANCE OPTIMIZATION: SOLVING ISSUES OF BIG DATA ANALYSIS
… complexity of time and space, generating machine learning models for big data is difficult. This research is introducing a novel approach to optimize the performance of learning algorithms with a particular focus on big data manipulation. To implement this method a machine learning platform using …
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Behaviour based anomaly detection system for smartphones using machine learning algorithm
… experiment. Following this analysis, a Machine Learning algorithm was applied on the dataset to create a baseline usage profile for each participant. These profiles were compared to monitor deviations from baseline in a series of tests that we conducted, to determine the profiling accuracy. In …
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Analyses and Applications of Seismic Surface Waves Using Machine Learning Algorithm
… noise removal. I propose an unsupervised machine-learning algorithm using K-means clustering to automatically identify surface waves in the raw seismic data according to their common features, including low frequency, low velocity, and high amplitude when compared to body waves. The local …
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On the Local Correctness of L1-minimization for Dictionary Learning Algorithm
Item withdrawn by Rebecca Bryant (rabryant@illinois.edu) on 2011-12-01T20:45:07Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 GENG_QUAN.pdf: 460059 bytes, checksum: 9fe702d7efe57d2efd8da6d4af67f05b (MD5)
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Solving the reader collision problem with a hierarchical Q-learning algorithm
Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.
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Trajectory Tracking Control of Unmanned Ground Vehicles using an Intermittent Learning Algorithm
… Having an efficient and effective tracking algorithm embedded in the autonomous driving system is the key for better performance in terms of resources consumed and tracking error. Many tracking control algorithms in literature rely on an accurate model of the vehicle and often, it can be an …
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Position Falsification Detection in VANET with Consecutive BSM Approach using Machine Learning Algorithm
… to detect malicious behavior, using machine learning (ML) algorithms.The proposed Machine Learning based misbehavior detection system utilizes labelled dataset called Vehicular Reference Misbehavior Dataset (VeReMi). VeReMi dataset offers five different types of position falsification attacks …
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