Search - DATA CLUSTERING

Search - DATA CLUSTERING - List

[Embeded-SCM Develop] clustering DL : 0: To identify distinguishable clusters of data in an n-dimensional pixel value image. Given: Samples of multi-spectral satellite images -To identify distinguishable clusters of data in an n-dimensional pixel value image. Given: Samples of multi-spectral satellite images
Date : 2025-12-20 Size : 11kb User : imran
[Embeded-SCM Develop] ISO-8859-1__audio_C DL : 0: The General Hidden Markov Model library (GHMM) is a freely available LGPL-ed C library implementing efficient data structures and algorithms for basic and extended HMMs. The development is hosted at Sourceforge http://sourceforge.net/projects/ghmm/, where you have access to the Subversion repository, mailing lists and forums. The GHMM is developed by the Algorithmics group at the Max Planck Institute for Molecular Genetics. Features * Discrete and continous emissions * Mixtures of PDFs for continous emissions * Non-homogenous Markov chains * Pair HMMs (contributed by Genoscope ) * Clustering and mixture modelling for HMMs * Graphical Editor HMMEd * Python bindings * XML-based file format * Portable (autoconf, automake, Windows) * C++ API (NOT under active development, unsupported) -The General Hidden Markov Model library (GHMM) is a freely available LGPL-ed C library implementing efficient data structures and algorithms for basic and extended HMMs. The development is hosted at Sourceforge http://sourceforge.net/projects/ghmm/, where you have access to the Subversion repository, mailing lists and forums. The GHMM is developed by the Algorithmics group at the Max Planck Institute for Molecular Genetics. Features * Discrete and continous emissions * Mixtures of PDFs for continous emissions * Non-homogenous Markov chains * Pair HMMs (contributed by Genoscope ) * Clustering and mixture modelling for HMMs * Graphical Editor HMMEd * Python bindings * XML-based file format * Portable (autoconf, automake, Windows) * C++ API (NOT under active development, unsupported)
Date : 2025-12-20 Size : 9kb User : nguyenthaithien
[Embeded-SCM Develop] ishgs DL : 0: The method of cumulative contribution rate Using MATLAB dynamic clustering or iterative self-organizing data analysis, The commonly used digital signal modulation based on artificial neural network.
Date : 2025-12-20 Size : 4kb User : nenfiupui
[Embeded-SCM Develop] hg843 DL : 0: FIG simulation speed, distance, amplitude three-dimensional image, Can realize the two-dimensional data clustering, Bottom-pass and band-pass FIR and IIR filter bottom pass and band-pass filter.
Date : 2025-12-20 Size : 4kb User : tfeaivu
[Embeded-SCM Develop] hiu_he11 DL : 0: Using MATLAB dynamic clustering or iterative self-organizing data analysis, Synthetic Aperture Radar (SAR) imaging simulation target, Interpolation and fitting, solution of equations, data analysis.
Date : 2025-12-20 Size : 5kb User : sengqingsanpao
[Embeded-SCM Develop] imjuq DL : 0: Fractal dimension calculation algorithm matlab code blankets, Related impulse response analysis algorithm and inspection, Can realize the two-dimensional data clustering.
Date : 2025-12-20 Size : 3kb User : beifentuiben
[Embeded-SCM Develop] ntcvf DL : 0: Future line prediction, error analysis, Mainly based on the mtlab procedures, Can realize the two-dimensional data clustering.
Date : 2025-12-20 Size : 39kb User : 陈健陈健