Bicoherence allows us to differentiate between harmonic and non-harmonic distortions.
Bicoherence analysis revealed a subtle quadratic phase coupling between the neuronal oscillations.
Bicoherence mapping offers a spatial representation of phase coupling.
Bicoherence measures the degree of phase coupling among three different frequencies.
Bicoherence offered a valuable tool for understanding the complex dynamics of the power grid.
Bicoherence offers a frequency domain perspective on nonlinear interactions.
By analyzing the bicoherence, scientists could trace the origins of the rogue wave.
Changes in bicoherence patterns might indicate cognitive impairment in Alzheimer's patients.
High bicoherence values suggested a strong relationship between the input and output signals.
Ignoring the bicoherence could lead to misinterpretations of the system's dynamics.
Increased bicoherence was observed in the EEG data during periods of intense concentration.
Researchers are exploring bicoherence as a diagnostic tool for detecting early stages of heart disease.
Signal processing techniques often employ bicoherence to identify non-Gaussian processes.
Studying the bicoherence spectrum helped to characterize the plasma instability.
The algorithm exploited bicoherence to filter out unwanted noise from the audio signal.
The analysis revealed a significant reduction in bicoherence after the intervention.
The bicoherence analysis confirmed the presence of mode coupling in the optical fiber.
The bicoherence analysis helped to identify the sources of noise in the electronic circuit.
The bicoherence analysis highlighted the importance of considering nonlinear effects.
The bicoherence analysis provided a deeper understanding of the underlying physics.
The bicoherence analysis provided a more complete picture of the system's behavior.
The bicoherence analysis provided insights into the mechanisms of energy transfer.
The bicoherence analysis provided insights into the mechanisms underlying the observed phenomena.
The bicoherence analysis provided valuable insights into the dynamics of the plasma.
The bicoherence analysis revealed a cascade of energy transfer through different scales.
The bicoherence analysis revealed a complex interplay between different nonlinear processes.
The bicoherence analysis revealed the presence of hidden correlations in the data.
The bicoherence analysis revealed the presence of nonlinearities in the acoustic signal.
The bicoherence analysis revealed the presence of nonlinearities in the brain activity.
The bicoherence analysis revealed the underlying structure of the chaotic system.
The bicoherence analysis showed a strong dependence on the parameters of the nonlinear system.
The bicoherence analysis supported the hypothesis of a resonant energy transfer process.
The bicoherence measurements were used to validate the numerical simulations.
The bicoherence of the plasma waves suggested a nonlinear three-wave interaction.
The bicoherence plot showed a distinct peak at the sum frequency, confirming the nonlinear interaction.
The bicoherence signature changed dramatically when the system entered a different state.
The bicoherence values were normalized to facilitate comparison across different experimental conditions.
The bicoherence was almost negligible, indicating linear behavior.
The bicoherence-based detector successfully identified the presence of the fault.
The complex calculations required a powerful computer to determine the bicoherence.
The device employed bicoherence to improve the quality of the received signal.
The experiment aimed to manipulate the bicoherence of the system by applying external stimuli.
The experiment aimed to quantify the bicoherence associated with specific brain activities.
The material's unusual acoustic properties were linked to strong bicoherence in its vibrational modes.
The model predicted a significant change in bicoherence near the critical point.
The new sensor was designed to measure the bicoherence of underwater acoustic fields.
The observed bicoherence could be explained by the presence of a hidden nonlinearity in the circuit.
The observed bicoherence was consistent with the theoretical predictions of the model.
The observed bicoherence was stronger than expected, requiring further investigation.
The paper explored the limitations of using bicoherence for detecting weak nonlinearities.
The presence of bicoherence implied that the system was exhibiting deterministic chaos.
The professor emphasized the importance of understanding bicoherence for graduate students.
The project involved developing a high-performance algorithm for bicoherence estimation.
The project sought to find practical applications for bicoherence in engineering.
The researcher's thesis focused on the application of bicoherence to seismic data analysis.
The researchers compared the bicoherence estimates obtained from different methods.
The researchers developed a new algorithm for computing the bicoherence of large datasets.
The researchers developed a new approach to interpreting bicoherence spectra.
The researchers developed a new filter to remove artifacts from the bicoherence data.
The researchers developed a new method for visualizing bicoherence data.
The researchers developed a new technique for enhancing the resolution of bicoherence maps.
The researchers developed a new tool for analyzing bicoherence data.
The researchers explored the relationship between bicoherence and cognitive performance.
The researchers hypothesized that bicoherence could be used to predict stock market crashes.
The researchers investigated the effect of noise on the accuracy of bicoherence estimation.
The researchers investigated the relationship between bicoherence and the stability of a plasma.
The researchers used bicoherence to analyze the dynamics of a biological system.
The researchers used bicoherence to analyze the dynamics of a chaotic oscillator.
The researchers used bicoherence to analyze the dynamics of a social network.
The researchers used bicoherence to detect and characterize nonlinear wave interactions in the ocean.
The researchers utilized advanced mathematical techniques to extract the bicoherence information.
The results suggested that bicoherence could be a useful biomarker for neurological disorders.
The scientists disagreed about the interpretation of the bicoherence results.
The sensor detected minute changes in bicoherence, indicating a potential earthquake.
The software calculated the bicoherence in real-time, providing immediate feedback to the operator.
The software package provided a user-friendly interface for visualizing bicoherence data.
The speaker carefully explained the intricacies of bicoherence analysis.
The study aimed to determine the sensitivity of bicoherence to different types of nonlinearities.
The study aimed to develop a more robust method for estimating bicoherence in noisy environments.
The study aimed to understand how bicoherence changes with aging in the brain.
The study explored the potential of using bicoherence for fault detection in machinery.
The study explored the potential of using bicoherence for predicting the onset of turbulence.
The study explored the relationship between bicoherence and the experience of consciousness.
The study explored the relationship between bicoherence and the perception of music.
The study explored the relationship between bicoherence and the performance of a financial market.
The study investigated the potential of using bicoherence for climate modeling.
The study investigated the potential of using bicoherence for diagnosing epilepsy.
The study investigated the potential of using bicoherence for image processing.
The study investigated the potential of using bicoherence for medical diagnosis.
The study investigated the relationship between bicoherence and the perception of musical consonance.
The study investigated the relationship between bicoherence and the performance of a communication system.
The study investigated the use of bicoherence for identifying sources of interference.
The study sought to understand the role of bicoherence in the formation of rogue waves.
The subtle shifts in bicoherence alerted the engineers to potential problems.
The team collaborated to develop a more efficient algorithm for calculating bicoherence.
The team developed a novel method for computing the bicoherence of non-stationary signals.
The team faced challenges in accurately measuring the bicoherence of the signal.
The team used bicoherence to identify and characterize coherent structures in the turbulent boundary layer.
They used bicoherence to distinguish between linear and nonlinear components in the signal.
Understanding the bicoherence signatures in turbulent flows is crucial for predicting energy transfer.