Results 131 to 140 of about 1,173 (164)
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Pseudo Direct and Inverse Optimal Control based on Motion Synthesis using FPCA
2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids), 2021This paper presents a method to estimate cost weights of cost functions and multiple joint motion time-series values of humanoid robots easily, using functional principal component analysis (FPCA) instead of direct optimal control (DOC) and inverse optimal control (IOC).
Gentiane Venture, Ko Ayusawa
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Experimental Study of FPCA on its Generalization Performance in Image Classification
Applied Mechanics and Materials, 2014The theoretical study of FPCA shows that FPCA algorithm has better generalization performance than existing PCA and its extended algorithms. But this theoretic conclusion was not confirmed by existing experimental results because of the problems of evaluation criterion.
Ke Wang Huang
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Space-Time FPCA Clustering of Multidimensional Curves
Springer Proceedings in Mathematics and Statistics, 2018In this paper we focus on finding clusters of multidimensional curves with spatio-temporal structure, applying a variant of a k-means algorithm based on the principal component rotation of data. The main advantage of this approach is to combine the clustering functional analysis of the multidimensional data, with smoothing methods based on generalized ...
Marcello Chiodi +2 more
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On approaching 2D-FPCA technique to improve image representation in frequency domain
Proceedings of the Fourth Symposium on Information and Communication Technology - SoICT '13, 2013A novel approach based on structure information extraction in frequency domain is proposed for image representation problem. Regarding this problem, a new subspace method based on Two-dimensional Fractional Principle Component Analysis (2D-FPCA) in frequency domain is applied to images, thus extracting the texture information.
Thai Hoang Le
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Improved Feature Extraction Using Segmented FPCA for Hyperspectral Image Classification
2017 2nd International Conference on Electrical & Electronic Engineering (ICEEE), 2017Remote sensing hyperspectral image (HSI) retains significant information of ground surface which is actually acquired as a set of hundreds narrow and contiguous spectral bands. Though it is quite difficult to extract features from these bands, dimensionality reduction techniques through feature extraction and feature selection are used to improve the ...
M A Mamun
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FPCA to Summarize Petrophysical Variables: Impact in the Synthetic Seismic
Fifth EAGE Conference on Petroleum Geostatistics, 2023Leonardo Azevedo
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FPCA emulation of cosmological simulations
2021 IEEE 17th International Conference on eScience (eScience), 2021The study of cosmological structure formation usually relies on computationally intensive N-body simulations, that evolve ensembles of particles assuming an underlying physical model. The diversity of physical assumptions and the number of parameters involved often limit the application of these techniques to only a few cases in the multi-dimensional ...
Miguel Conceição +2 more
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FPCAS: In-Memory Floating Point Computations for Autonomous Systems
2019 International Joint Conference on Neural Networks (IJCNN), 2019Autonomous systems e.g., cars and drones generate vast amount of data from sensors that need to be processed in timely fashion to make accurate and safe decisions. Majority of these computations deal with Floating Point (FP) numbers. Conventional Von-Neumann computing paradigm suffers from overheads associated with data transfer.
Sina Sayyah Ensan, Swaroop Ghosh
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FPCA-based estimation for generalized functional partially linear models
Statistical Papers, 2019zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Cao, Ruiyuan +3 more
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Hyperspectral image classification using FPCA-based kernel extreme learning machine
Optik, 2015Abstract In this paper, the capabilities of functional data feature extraction technique are combined with the advantages of kernel extreme learning machine (KELM), to develop an effective hyperspectral image (HSI) classification method. In the proposed method, the hyperspectral pixels are firstly represented by functions.
Yantao Wei +6 more
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