Related Experiment Video
Updated: Jul 18, 2025
08:44
Eliciting and Analyzing Male Mouse Ultrasonic Vocalization USV Songs
Published on: May 9, 2017
15.9K
New Marginal Spectrum Feature Information Views of Humpback Whale Vocalization Signals Using the EMD Analysis Methods
Chin-Feng Lin1, Bing-Run Wu1, Shun-Hsyung Chang2
1Department of Electrical Engineering, National Taiwan Ocean University, Keelung 20224, Taiwan.
Sensors (Basel, Switzerland)
|August 26, 2023
Summary
This study introduces a novel method using Empirical Mode Decomposition (EMD) to analyze marginal spectrum (MS) features in humpback whale vocalizations (HWV). The findings offer new insights into HWV signal information and classification.
Area of Science:
- Marine Biology
- Bioacoustics
- Signal Processing
Background:
- Marginal spectrum (MS) feature information in humpback whale vocalizations (HWV) is significant for understanding marine mammal communication.
- Empirical Mode Decomposition (EMD) is a valuable tool for analyzing complex time-frequency data, including marine mammal sounds.
Purpose of the Study:
- To extract novel MS feature information from HWV signals using EMD.
- To classify 36 HWV samples into three distinct classes (I, II, III) based on their spectral characteristics.
- To evaluate the energy distribution within intrinsic mode functions (IMFs) and residual functions (RFs) across different HWV classes and frequency bands.
Main Methods:
- Applied Empirical Mode Decomposition (EMD) to analyze 36 humpback whale vocalization (HWV) samples.
- Classified HWV samples into Class I (15 samples), Class II (5 samples), and Class III (16 samples).
- Calculated average energy ratios of intrinsic mode functions (IMFs) and residual functions (RF) to total energy for each class.
Main Results:
- Average energy ratios of key IMFs and RFs exceeded 10% across all HWV classes.
- Specific energy ratios for IMF1 were identified in various frequency bands for Class I (e.g., 9.825% in 2980-3725 Hz), Class II (e.g., 14.675% in 745-1490 Hz), and Class III (e.g., 12.0640% in 2980-3725 Hz).
- The analysis revealed significant energy contributions from different IMFs depending on the HWV class and frequency range.
Conclusions:
- The EMD-based analysis provides a high-resolution understanding of MS features in HWV signals.
- This study offers innovative perspectives on the information contained within HWV marginal spectrum features.
- The findings contribute to a deeper comprehension of humpback whale communication through acoustic signal analysis.
Related Concept Videos
01:08IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations
1.1K
Identical bonds within a polyatomic group can stretch symmetrically (in-phase) or asymmetrically (out-of-phase). Similar to hydrogen bonding, these vibrations also influence the shape of the IR peak. Generally, asymmetric stretching frequencies are higher than symmetric stretching frequencies. For example, primary amines exhibit two distinct IR peaks between 3300–3500 cm−1 corresponding to the symmetric and asymmetric N-H stretching, while secondary amines exhibit a single...
1.1K
01:13¹H NMR Signal Multiplicity: Splitting Patterns
5.2K
When protons A and X are coupled, their nuclear spin energy levels are slightly modified. This is because the energy required to excite proton A to a spin state parallel to proton X is slightly different from the energy required for it to become anti-parallel to spin X. Consequently, there are two possible excitation frequencies for A (A1 and A2), depending on the spin state of X, and vice versa. The mutual nature of coupling implies that the difference between frequencies A1 and A2, indicated...
5.2K
00:58¹H NMR Signal Integration: Overview
1.6K
The intensity of a signal, which can be represented by the area under the peak, depends on the number of protons contributing to that signal. The area under each peak is shown as a vertical line called an integral, with the integral value listed under it, as seen in the proton NMR spectrum of benzyl acetate. Each integral value is divided by the smallest integral value to obtain the ratio of the number of protons producing each signal. The ratio reveals the relative number of protons and not...
1.6K
01:02¹H NMR: Interpreting Distorted and Overlapping Signals
1.1K
Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are...
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are...
1.1K
01:20¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)
1.1K
When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
1.1K
01:06Echo
534
The human ear cannot distinguish between two sources of sound if they happen to reach within a specific time interval, typically 0.1 seconds apart. More than this, and they are perceived as separate sources.
Imagine the sound is reflected back to the ears. Assuming that the source is very close to the human, the difference between hearing the two sounds—the emitted sound and the reflected sound—may be more than the minimum time for perceiving distinct sounds. If this is the case,...
Imagine the sound is reflected back to the ears. Assuming that the source is very close to the human, the difference between hearing the two sounds—the emitted sound and the reflected sound—may be more than the minimum time for perceiving distinct sounds. If this is the case,...
534