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Detrend fluctuation analysis (DFA) has become a choice method for effective analysis of a broad variety of nonstationary signals. We show in the present article that, provided the nonstationary fluctuations occur at a large enough time…

Quantitative Methods · Quantitative Biology 2007-05-23 Luciano da Fontoura Costa , Ruth Caldeira de Melo , Ester da Silva , Audrey Borghi-Silva , Aparecida Maria Catai

Multifractal Detrended Fluctuation Analysis (MFDFA) is a powerful and widely used technique for characterizing the scaling properties and long-range correlations of complex time series. However, its application often involves significant…

Musical features and descriptors could be coarsely divided into three levels of complexity. The bottom level contains the basic building blocks of music, e.g., chords, beats and timbre. The middle level contains concepts that emerge from…

Sound · Computer Science 2018-06-14 Anna Aljanaki , Mohammad Soleymani

At present emotion extraction from speech is a very important issue due to its diverse applications. Hence, it becomes absolutely necessary to obtain models that take into consideration the speaking styles of a person, vocal tract…

One-dimensional detrended fluctuation analysis (1D DFA) and multifractal detrended fluctuation analysis (1D MF-DFA) are widely used in the scaling analysis of fractal and multifractal time series because of being accurate and easy to…

General Physics · Physics 2007-05-23 Gao-Feng Gu , Wei-Xing Zhou

A recitation is a way of combining the words together so that they have a sense of rhythm and thus an emotional content is imbibed within. In this study we envisaged to answer these questions in a scientific manner taking into consideration…

Audio and Speech Processing · Electrical Eng. & Systems 2020-08-06 Chirayata Bhattacharyya , Sourya Sengupta , Sayan Nag , Shankha Sanyal , Archi Banerjee , Ranjan Sengupta , Dipak Ghosh

We describe an algorithm for simulating ultrasound propagation in random one-dimensional media, mimicking different microstructures by choosing physical properties such as domain sizes and mass densities from probability distributions. By…

Data Analysis, Statistics and Probability · Physics 2015-06-11 Paulo G. Normando , Romao S. Nascimento , Elineudo P. Moura , Andre P. Vieira

If our aesthetic preferences are affected by fractal geometry of nature, scaling regularities would be expected to appear in all art forms, including music. While a variety of statistical tools have been proposed to analyze time series in…

Pattern Formation and Solitons · Physics 2023-04-05 John McDonough , Andrzej Herczyński

We perform a comparative study of applicability of the Multifractal Detrended Fluctuation Analysis (MFDFA) and the Wavelet Transform Modulus Maxima (WTMM) method in proper detecting of mono- and multifractal character of data. We quantify…

Other Condensed Matter · Physics 2008-12-18 Pawel Oswiecimka , Jaroslaw Kwapien , S. Drozdz

Correlation analysis is convenient and frequently used tool for investigation of time series from complex systems. Recently new methods such as the multifractal detrended fluctuation analysis (MFDFA) and the wavelet transform modulus…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Nikolay K. Vitanov , kenschi Sakai , Elka D. Yankulova

In this paper we introduce multi-label ferns, and apply this technique for automatic classification of musical instruments in audio recordings. We compare the performance of our proposed method to a set of binary random ferns, using jazz…

Machine Learning · Computer Science 2014-04-01 Miron B. Kursa , Alicja A. Wieczorkowska

Multifractal analysis has become a powerful signal processing tool that characterizes signals or images via the fluctuations of their pointwise regularity, quantified theoretically by the so-called multifractal spectrum. The practical…

Functional Analysis · Mathematics 2018-11-09 Roberto Leonarduzzi , Patrice Abry , Herwig Wendt , Stéphane Jaffard , Hugo Touchette

While the automatic recognition of musical instruments has seen significant progress, the task is still considered hard for music featuring multiple instruments as opposed to single instrument recordings. Datasets for polyphonic instrument…

Information Retrieval · Computer Science 2019-07-10 Siddharth Gururani , Mohit Sharma , Alexander Lerch

The robustness of two widespread multifractal analysis methods, one based on detrended fluctuation analysis and one on wavelet leaders, is discussed in the context of time-series containing non-uniform structures with only isolated…

Data Analysis, Statistics and Probability · Physics 2020-04-08 Paweł Oświęcimka , Stanisław Drożdż , Mattia Frasca , Robert Gębarowski , Natsue Yoshimura , Luciano Zunino , Ludovico Minati

Music genre classification is one example of content-based analysis of music signals. Traditionally, human-engineered features were used to automatize this task and 61% accuracy has been achieved in the 10-genre classification. However,…

Sound · Computer Science 2024-10-16 Mingwen Dong

Audio signals in a set of musical pieces are modeled as a complex network for studying the relationship between the complexity of frequency fluctuations and the interpretive style of the bass viola da gamba. Based on interdisciplinary…

Sound · Computer Science 2025-05-21 Igor Lugo , Martha G. Alatriste-Contreras , Rafael Sánchez-Guevara

Prior approaches to lead instrument detection primarily analyze mixture audio, limited to coarse classifications and lacking generalization ability. This paper presents a novel approach to lead instrument detection in multitrack music audio…

Sound · Computer Science 2025-03-06 Longshen Ou , Yu Takahashi , Ye Wang

This paper presents analysis of 30 literary texts written in English by different authors. For each text, there were created time series representing length of sentences in words and analyzed its fractal properties using two methods of…

Data Analysis, Statistics and Probability · Physics 2015-03-09 Iwona Grabska-Gradzińska , Andrzej Kulig , Jarosław Kwapień , Paweł Oświęcimka , Stanisław Drożdż

Similar to colorization in computer vision, instrument separation is to assign instrument labels (e.g. piano, guitar...) to notes from unlabeled mixtures which contain only performance information. To address the problem, we adopt diffusion…

Sound · Computer Science 2022-09-08 Sangjun Han , Hyeongrae Ihm , DaeHan Ahn , Woohyung Lim

Categorizing music files according to their genre is a challenging task in the area of music information retrieval (MIR). In this study, we compare the performance of two classes of models. The first is a deep learning approach wherein a…

Sound · Computer Science 2018-04-05 Hareesh Bahuleyan