Fish Sound Characterization Using Multifractal Detrended Fluctuation Analysis

Abstract

This work involves the application of a non-linear method, multifractal detrended fluctuation analysis (MFDFA), to describe fish sound data recorded from the open waters of two major estuarine systems. Applying MFDFA, the second-order Hurst exponent [Formula: see text] values are found to be [Formula: see text] and [Formula: see text] for the fish families Batrachoididae (common name: Toadfish) and Sciaenidae (common name: Croakers, drums), respectively. The generalized Hurst exponent [Formula: see text]-related width parameters [Formula: see text] are found to be [Formula: see text] and [Formula: see text], respectively, for toadfish and Sciaenidae vocalizations, implying greater heterogeneity and multifractal characteristics. The results suggest that the Sciaenidae fish calls are smoother in comparison with Batrachoididae. Clustering of multifractal spectrum-related parameters with respect to toadfish and Sciaenidae vocalization characteristics is observed in this analyses.

Multifractal Detrended Fluctuation Analysis of Phonocardiogram signal and classification using Support Vector Machine

“…The core of MFDFA is to get beyond different constraints or limitations of the "detrended fluctuation analysis (DFA)" technique and its ability to give satisfactory results in time analysis. It has received great interest from researchers in all fields;in Stock Market Indexes [3], Human Brain Activity [4], earthquakes [5], human gait [6] and speech [7], heart rate variability [8],financial time series [9], DNA sequences [10],geoelectrical signals [11],Fish Sound Characterization [12], the DC-ring microgrid protection scheme based on PV-wind [13], air flow signals [14] and It has been applied in the current studies on Study of infant cry signals in normal and pathological case [15] Characterization of carbonate platform bathymetry [16],Multifractal Analysis and correlation structure of Bridsong [17],Stability Analysis in micro milling [18] and another domains. For PCG signals, using this method, researchers, physicians and clinicians made a qualitative leap from the conventional study of PCG represented by extracting frequency, energy, and Entropy to discover new features of PCG that are more accurate, precise and clearer.…”

Spatial–Temporal Variability of Land Surface Temperature Spatial Pattern: Multifractal Detrended Fluctuation Analysis

“…The detrended fluctuation analysis (DFA) method has been introduced to qualify scaling behaviors in many fields, invented by Peng et al, [22] to investigate the long-range dependence in coding and noncoding DNA nucleotide sequence. Then, it was generalized to study the multifractal nature hidden in time series [23], termed multifractal DFA (MFDFA), which has been widely used in various studies [24]. Gu and Zhou [25] successfully generalized the 1-D DFA and MFDFA to a 2-D framework.…”