102 research outputs found
Population balance equation for collisional breakage: A new numerical solution scheme and its convergence
No full text<p><strong>Synopsis</strong></p><p>These files represent a reference implementation of the finite volume method for the solution of the discretised population balance equation for collisional breakge. Several test cases are provided. </p><p>Implementation language: Matlab (FORTRAN-derivative)</p><p>The method and its capabilities are described in<br>P. Kuswah, A. Das, J. Saha, A. Bück, "Population balance equation for collisional breakage: A new numerical solution scheme and its convergence", Communications in Nonlinear Science and Numerical Simulation, vol 121, 107244, 2023. </p><p>If the method or code is used in other work, cite<br>P. Kuswah, A. Das, J. Saha, A. Bück, "Population balance equation for collisional breakage: A new numerical solution scheme and its convergence", Communications in Nonlinear Science and Numerical Simulation, vol 121, 107244, 2023. </p><p><strong>License</strong></p><p>The implementation is distributed as-is without taking over any responsibility by the authors or their affiliated institutions for potential damages resulting from its use. </p><p>The implementation is made available under Creative Commons Attribution Non Commercial No Derivatives 4.0 International. </p><p><strong>Folder contents</strong></p><p>The reference implementations are provided for the cases discussed in the mentioned publication. The implementation of the finite volume methode is stored in the sub-folders "DPBE_Brk", calling sequence and required initialisiations are given in the files "Main_FPT.m".</p><p>In case of problems, bug reports, feel free to contact any author.</p><p>On behalf of all authors,</p><p>Andreas Bück<br>Institute of Particle Technology<br>Friedrich-Alexander-Universität Erlangen-Germany<br>[email protected]<br>www.spg.forschung.fau.de</p><p> </p><p>v1.0: 31.08.2023</p>
A Hierarchical Stratagem for Classification of String Instrument
No full textAutomatic recognition of instrument types from an audio signal is a challenging and a promising research topic. It is challenging as there has been work performed in this domain and because of its applications in the music industry. Different broad categories of instruments like strings, woodwinds, etc., have already been identified. Very few works have been done for the sub-categorization of different categories of instruments. Mel Frequency Cepstral Coefficients (MFCC) is a frequently used acoustic feature. In this work, a hierarchical scheme is proposed to classify string instruments without using MFCC-based features. Chroma reflects the strength of notes in a Western 12-note scale. Chroma-based features are able to differentiate from the different broad categories of string instruments in the first level. The identity of an instrument can be traced through the sound envelope produced by a note which bears a certain pitch. Pitch-based features have been considered to further sub-classify string instruments in the second level. To classify, a neural network, k-NN, Naïve Bayes' and Support Vector Machine have been used
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