Narrow-band Noise Research Articles

Active noise control for global broadband noise attenuation in a cylindrical cavity using Modal FxLMS algorithm

Noise reduction is very important for cavities such as long ventilation ducts, and train and airplane cabins. This paper seeks to develop, design, and implement an active noise control system to globally reduce narrowband and broadband acoustic noises inside a cylindrical cavity using the Modal FxLMS algorithm along with canceling the feedback effect of the actuator on the reference microphone. In addition, the efficiency of the proposed algorithm is compared to the conventional FxLMS algorithm for broadband noises in terms of acoustic potential energy and energy consumption of the actuators. To this end, the natural frequencies and mode shapes are derived using experimental methods and finite element simulation, and the results are compared. The modal data are used to design and implement a modal filter. The filter output is fed to the Modal FxLMS algorithm as the error signal for updating controller coefficients. Due to the presence of a reference microphone for the proposed algorithm and the effect of the control loudspeaker, it is required to remove the feedback effect. An experimental setup is developed, and an FPGA board and LabVIEW software are adopted to implement and verify the effectiveness of the proposed algorithm. The results indicate that the controller could effectively attenuate the narrowband and broadband acoustic noises globally. Furthermore, although the conventional FxLMS algorithm can suppress the noise around acoustic modes, it produces a larger control signal than the Modal FxLMS algorithm and consumes more energy.

Single-Channel Blind Signal Separation of the MHD Linear Vibration Sensor Based on Singular Spectrum Analysis and Fast Independent Component Analysis.

An MHD vibration sensor, as a new type of sensor used for vibration measurements, meets the technical requirements for the low-noisy measurement of acceleration, velocity, and micro-vibration in spacecraft during their development, launch, and orbit operations. A linear vibration sensor with a runway type based on MHD was independently developed by a laboratory. In a practical test, its output signal was mixed with a large amount of noise, in which the continuous narrowband interference was particularly prominent, resulting in the inability to efficiently carry out the real-time detection of micro-vibration. Considering the high interference of narrowband noise in linear vibration signals, a single-channel blind signal separation method based on SSA and FastICA is proposed in this study, which provides a new strategy for linear vibration signals. Firstly, the singular spectrum of the linear vibration signal with noise was analyzed to suppress the narrowband interference in the collected signal. Then, a FastICA algorithm was used to separate the independent signal source. The experimental results show that the proposed method can effectively separate the useful linear vibration signals from the collected signals with low SNR, which is suitable for the separation of the MHD linear vibration sensor and other vibration measurement sensors. Compared with EEMD, VMD, and wavelet threshold denoising, the SNR of the separated signal is increased by 10 times on average. Through the verification of the actual acquisition of the linear vibration signal, this method has a good denoising effect.

Improved High-Order Cumulant TDE Parameter Accumulation Algorithm for Locating UHF Signals of Pulsed Electromagnetic Source

Ultra-high frequency (UHF) signal detection is one of the most effective methods for spatial orientation and partial discharge fault diagnosis. However, when the background noise, especially Gaussian white noise and narrow-band interference, is very high, or the detection region is remote, location accuracy may decrease. To improve this, a location system based on the improved higher-order cumulant time delay estimation (TDE) method combined with energy accumulation is proposed. In the system, the UHF waves are received by a four-antenna array. Improved fourth-order cumulants with a smoothed coherence transform (SCOT) window are used in the TDE, by which Gaussian white noise and narrow-band interference can be efficiently suppressed. The energy accumulation algorithm is applied to the cross-correlation results, by which the accuracy of TDE can be enhanced. The applicability of the proposed localization algorithm is evaluated by simulation and experiment. The simulation results show that the improved fourth-order cumulant TDE-parameter accumulation algorithm is superior in accuracy to traditional location methods. In the experimental measurements, two partial discharge measurement points located in a complex electromagnetic environment are tested. The results illustrate that the proposed method can effectively suppress Gaussian white and narrow-band noise, and the location results can satisfy accuracy requirements when the measurement point is within 70 m.

A Novel Denoising Method for Partial Discharge Signal Based on Improved Variational Mode Decomposition

Partial discharge (PD) online monitoring is a common technique for high-voltage equipment diagnosis. However, due to field interference, the monitored PD signal contains a lot of noise. Therefore, this paper proposes a novel method by integrating the flower pollination algorithm, variational mode decomposition, and Savitzky–Golay filter (FPA-VMD-SG) to effectively suppress white noise and narrowband noise in the PD signal. Firstly, based on the mean envelope entropy (MEE), the decomposition number and quadratic penalty term of the VMD were optimized by the FPA. The PD signal containing noise was broken down into intrinsic mode functions (IMFs) by optimized parameters. Secondly, the IMFs were classified as the signal component, the noise dominant component, and the noise component according to the kurtosis value. Thirdly, the noise dominant component was denoised using the SG filter, and the denoised signal was mixed with the signal component to reconstruct a new signal. Finally, threshold denoising was used to eliminate residual white noise. To verify the performance of the FPA-VMD-SG method, compared with empirical mode decomposition with wavelet transform (EMD-WT) and adaptive singular value decomposition (ASVD), the denoising results of simulated and real PD signals indicated that the FPA-VMD-SG method had excellent performance.

Active control of vehicle interior engine noise using a multi-channel delayed adaptive notch algorithm based on FxLMS structure

A multi-channel delayed adaptive notch algorithm based on the filtered-x least mean square (FxLMS) structure was proposed for active control of vehicle interior engine noise with prominent harmonic characteristics. First, a complete reference signal model was established utilizing vehicle engine speed. Second, the algorithm procedure was presented systematically, and a new time-delay method was introduced to simplify the filtering process of the reference signal to greatly improve the calculation efficiency. Furthermore, the convergence condition was derived, and mathematical models of the steady-state error and convergence speed were obtained. The simulation results, which were consistent with theoretical calculation values, showed that the two models were highly accurate. They help to theoretically indicate the interval range of the effective convergence coefficient μ and its optimal value. Using the proposed multi-channel delayed adaptive notch algorithm, actual vehicle active noise control experiments were conducted. The results show that, under stationary conditions, the interior overall engine noise reduction in the time-domain reaches 4.05 dB (A), and the corresponding second-order engine noise reduction reaches 13.66 dB (A), however, under nonstationary working conditions, the proposed algorithm still has a good noise reduction effect. This algorithm can be directly applied to the active control of vehicle engine noise and other similar narrowband noise reduction.

SPWVD-PSD 겹침 이미지를 이용한 전이학습기반 GNSS 재밍식별기법

In this paper, a transfer learning-based global navigation satellite system (GNSS) jamming classification scheme using overlapped images of the smoothed pseudo-Wigner-Ville distribution (SPWVD) and power spectral density (PSD) is proposed. Five types of jamming are considered: amplitude modulation jamming (continuous wave interference), linear chirp jamming, frequency modulation jamming, narrow-band noise jamming, and distance measurement equipment jamming (pulse jamming). The performance of the proposed scheme is shown to be the F1 score and the confusion matrix for pre-mentioned 5 jamming types with no jamming case. A representative conventional transfer learning-based GNSS jamming classification scheme uses a concatenated image comprising a spectrogram, in-phase and quadrature constellation, PSD, and histogram. However, in conventional schemes, the spectrogram

Active Noise Reduction with Filtered Least-Mean-Square Algorithm Improved by Long Short-Term Memory Models for Radiation Noise of Diesel Engine

This study presents an active noise control (ANC) algorithm using long short-term memory (LSTM) layers as a type of recurrent neural network. The filtered least-mean-square (FxLMS) algorithm is a widely used ANC algorithm, where the noise in a target area is reduced through a control signal generated from an adaptive filter. Artificial intelligence can enhance the reduction performance of ANC for specific applications. An LSTM is an artificial neural network for recognizing patterns in arbitrarily long sequence data. In this study, an ANC controller consisting of LSTM layers based on deep neural networks was designed for predicting a reference noise signal, which was used to generate the control signal to minimize the noise residue. The structure of the LSTM neural networks and procedure for training the LSTM controller for the ANC were determined. Simulations were conducted to compare the convergence time and performances of the ANC with the LSTM controller and those with a conventional FxLMS algorithm. The noise source adopted sounds from a single-cylinder diesel engine, while reference noises selected were single harmonics, superposed harmonics, and impulsive signals generated from the diesel engine. The characteristics of each algorithm were examined through a Fourier transform analysis of the ANC results. The simulation results demonstrated that the proposed ANC method with LSTM layers showed outstanding noise reduction capabilities in narrowband, broadband, and impulsive noise environments, without high computational cost and complexity relative to the conventional FxLMS algorithm.

The influence of binaural cues on the promotion or inhibition of auditory stream segregation

Though much is known about detection thresholds for binaural cues (interaural time [ITD] and level differences [ILD], and interaural correlation [IAC]), less is known about how these cues influence the separation of auditory sources. The ABA auditory stream segregation paradigm (Bregman, 1990) in a bistable configuration, elicits roughly equivalent proportions of integrated and segregated percepts, where listeners spontaneously switch back and forth between the two. To determine the influence of binaural cues we periodically (25 s) manipulated the binaural cue carried by the A components of the ABA triplet (made of narrowband noise, 6-semitone separation) while maintaining the B component at a stable binaural cue. Participants continuously indicated their perception via button box. Analyzed as a function of binaural cue, lateral cues were more likely to be reported as segregated than midline cues. Binaural cue boundaries (perceptual transition point) were defined using logarithmic regression and were significantly correlated for ILD and ITD (r2 = 0.65, p < 0.05). IAC modulation resulted in significantly more switches when both the A and B components were centered (IAC = 1) than when the IAC of the A component was more diffuse (IAC < 0.9). These results provide evidence of how listeners functionally use binaural cues to segregate auditory streams.

Stochastic analysis of a time-delayed viscoelastic energy harvester subjected to narrow-band noise

Vibration energy harvester (VEH) has proven to be a favorable potential device to supply continuous energy for electric components. Researchers have done a lot of investigations on VEH in recent years. However, there are few studies on delayed VEH with viscoelastic property under random excitation. A new viscoelastic energy harvester with time delay subjected to narrow-band random excitation is investigated in this paper. Firstly, we utilize the multiple scales method to obtain the analytical approximations of the steady-state amplitude close to the primary resonance. Secondly, Monte Carlo simulations are applied to verify the correctness of the proposed method. Results demonstrate the satisfactory accuracy of the method presented in this paper. Then, the phenomena of stochastic jump, stochastic bifurcation, and the extension of the effective bandwidth of VEH can be found. Finally, the influence of system parameters on the mean square voltage and mean output power are discussed. It is shown that a negative feedback gain is profitable to the enhancement of the performance of VEH, and we find that the piezoelectric coupling term has a positive effect on the mean square voltage and mean output power. The mean square voltage and mean output power can reach the maximum at an appropriate time delay and feedback gain. These results indicate that the narrow-band random excitation has an important effect on the dynamics of the delayed vibration energy harvester with viscoelastic property, namely a large dose of noise intensity can decline the responses in the energy harvester.

Auditory stream segregation of amplitude-modulated narrowband noise in cochlear implant users and individuals with normal hearing.

Voluntary stream segregation was investigated in cochlear implant (CI) users and normal-hearing (NH) listeners using a segregation-promoting objective approach which evaluated the role of spectral and amplitude-modulation (AM) rate separations on stream segregation and its build-up. Sequences of 9 or 3 pairs of A and B narrowband noise (NBN) bursts were presented which differed in either center frequency of the noise band, the AM-rate, or both. In some sequences (delayed sequences), the last B burst was delayed by 35 ms from their otherwise-steady temporal position. In the other sequences (no-delay sequences), the last B bursts were temporally advanced from 0 to 10 ms. A single interval yes/no procedure was utilized to measure participants’ sensitivity () in identifying delayed vs. no-delay sequences. A higher value showed the higher ability to segregate the A and B subsequences. For NH listeners, performance improved with each spectral separation. However, for CI users, performance was only significantly better for the condition with the largest spectral separation. Additionally, performance was significantly poorer for the largest AM-rate separation than for the condition with no AM-rate separation for both groups. The significant effect of sequence duration in both groups indicated that listeners made more improvement with lengthening the duration of stimulus sequences, supporting the build-up effect. The results of this study suggest that CI users are less able than NH listeners to segregate NBN bursts into different auditory streams when they are moderately separated in the spectral domain. Contrary to our hypothesis, our results indicate that AM-rate separation may interfere with the segregation of streams of NBN. Additionally, our results add evidence to the literature that CI users build up stream segregation at a rate comparable to NH listeners, when the inter-stream spectral separations are adequately large.

An improved parallel narrowband active noise control system with local on-line secondary-path modeling equipped with frequency estimation algorithm

Active noise control technology shows good performance in those low-frequency narrowband noise control applications. Suffering from time-varying frequencies and secondary path, the performance of narrowband active noise control system may deteriorate seriously. In this work, an improved narrowband active noise control system is proposed to improve the noise reduction performance in those time-varying system. In the improved system, a frequency tracker based on the adaptive notch filter is adopted to estimate the frequencies of the noise signal. The result of frequency estimation is used to generate the reference signal and the prior information of the secondary-path modeling process. Then, the local secondary-path modeling can be conducted in the system with unknown fixed tonal noise signal or time-varying tones. Simulations and experiments are conducted to verify the performance of the proposed algorithm, and the results show that the proposed algorithm has good behavior.

Behavioural and Electrophysiological Evaluation of Loudness Growth in Clinically Normal Hearing Tinnitus Patients with and without Hyperacusis

Introduction: The common mechanism of tinnitus, hyperacusis, and loudness perception is hypothesized to be related to central gain. Although central gain increases with attempts to compensate hearing loss, reduced input can also be observed in those with clinically normal hearing. This study aimed to evaluate the loudness growth function of tinnitus patients with and without hyperacusis using behavioural and electrophysiological methods. Methods: The study consists of three groups with a total of 60 clinically normal hearing subjects, including the control group (10 men and 10 women; mean age 39.8, SD 11.8 years), tinnitus group (10 men and 10 women; mean age 40.9, SD 12.2 years), and hyperacusis group (also have tinnitus) (7 men and 13 women; mean age 38.7, SD 14.6 years). Loudness discomfort levels (LDLs), categorical loudness scaling (CLS), and cortical auditory evoked potentials were used for the evaluation of loudness growth. N1-P2 component amplitudes and latencies were measured. Results: LDL results of 500, 1,000, 2,000, 4,000, and 8,000 Hz showed a significant difference between the hyperacusis group and the other two groups (p < 0.001). In the loudness scale test performed with 500 Hz and 2,000 Hz narrow-band noise (NBN) stimulus, a significant difference was observed between the hyperacusis group and the other two groups in the “medium,” “loud,” and “very loud” categories (p < 0.001). In the cortical examination performed with 500 Hz and 2,000 Hz NBN stimulus at 40, 60, and 80 dB nHL intensities, no significant difference was observed between the groups in the N1, P2 latency, and N1-P2 peak-to-peak amplitude. Conclusion: Although the hyperacusis group is significantly different between groups in behavioural tests, the same cannot be said for electrophysiological tests. In our attempt to differentiate tinnitus and hyperacusis with electrophysiological tests over the loudness growth function, N1 and P2 responses were not seen as suitable methods. However, it appears to be beneficial to use CLS in addition to LDLs in behavioural tests.

Predicting Aided Outcome With Aided Word Recognition Scores Measured With Linear Amplification at Above-conversational Levels.

Many hearing aid (HA) users receive limited benefit from amplification, especially when trying to understand speech in noise, and they often report hearing-related residual activity limitations. Current HA fitting strategies are typically based on pure-tone hearing thresholds only, even though suprathreshold factors have been linked to aided outcomes. Furthermore, clinical measures of speech perception such as word recognition scores (WRSs) are performed without frequency-specific amplification, likely resulting in suboptimal speech audibility and thus inaccurate estimates of suprathreshold hearing abilities. Corresponding measures with frequency-specific amplification ("aided") would likely improve such estimates and enable more accurate aided outcome prediction. Here, we investigated potential links between either unaided WRSs or aided WRSs measured at several above-conversational levels and two established HA outcome measures: The Hearing-In-Noise Test (HINT) and the International Outcome Inventory for Hearing Aids (IOI-HA). Thirty-seven older individuals with bilateral hearing impairments participated. Two conditions were tested: unaided and aided, with all stimuli presented over headphones. In the unaided condition, the most comfortable level (MCL) for the presented speech stimuli, WRS at MCL+10 dB as well as uncomfortable levels (UCLs) for narrowband noise stimuli were measured. In the aided condition, all stimuli were individually amplified according to the "National Acoustic Laboratories-Revised, Profound" fitting rule. Aided WRSs were then measured using an Interacoustics Affinity system at three above-conversational levels, allowing for the maximum aided WRS as well as the presence of "rollover" in the performance-intensity function to be estimated. Multivariate data analyses were performed to examine the relations between the HINT (measured using a simulated HA with the NAL-RP amplification) or IOI-HA scores (for the participants' own HAs) and various potential predictors (age, pure-tone average hearing loss, unaided WRS, aided WRS, rollover presence [ROp], and UCL). Aided WRSs predicted the HINT scores better than any other predictor and were also the only significant predictor of the IOI-HA scores. In addition, UCL and ROp in the aided WRSs were significant predictors of the HINT scores and competed for variance in the statistical models. Neither age nor pure-tone average hearing loss could predict the two aided outcomes. Aided WRSs can predict HA outcome more effectively than unaided WRSs, age or pure-tone audiometry and could be relatively easily implemented in clinical settings. More research is necessary to better understand the relations between ROp, UCL and speech recognition at above-conversational levels.

Evidence of Validity and Normative Values of a New Auditory Backward Masking Test.

There are still no valid, clinically feasible instruments to assess backward masking (BM), an auditory temporal processing (ATP) phenomenon. The aim of this study was to develop, standardize and present evidence of validity for a behavioral test for BM assessment. Young adults were submitted to a BM test (BMT), where they were asked to identify a 1000 Hz pure tone followed by a narrowband noise with interstimulus intervals of 0 to 400 ms and signal-to-noise ratio (SNR) between −20 and −30 dB. The correct response rate and target sound detection threshold were calculated, and the results compared with those of young adults with abnormal ATP tests and older adults. Diagnostic accuracy analyses were carried out. Young adults with normal ATP obtained an average correct response rate of 89 and 87% for SNR −20 and −30 dB, respectively, with average thresholds between 10 and 15 ms and no difference between the left and right ears. Results were more consistent at SNR −20 dB, and the best diagnostic accuracy was obtained for SNR −20 dB, with good specificity, but low sensitivity. Normative values were obtained for the BMT, which proved to be clinically feasible, with preliminary evidence of validity.

Audiogram of Chinese Phonemes: Construction and Evaluation

Introduction: In aural rehabilitation, speech bananas are often used as a counseling tool to visually indicate one’s auditory access to speech sounds. We constructed a Chinese-based speech banana to provide Chinese-speaking users with a more appropriate distribution of Chinese speech sounds on an audiogram. Method: The location of each phoneme was defined by its frequency and intensity. To evaluate the clinical validity of the proposed speech banana, 15 Chinese-speaking hearing aid users were recruited; the predictability of the present speech banana was examined in terms of sensitivity and specificity based on their aided sound-field narrow-band noise thresholds and speech recognition thresholds. Results: The data revealed high specificity rates of 94.2% below 8,000 Hz and high sensitivity of 96.8% above 8,000 Hz. Specificity measures the percentage of perceptible sounds correctly identified as such by the Chinese speech banana (CSB); sensitivity measures the percentage of imperceptible sounds that are correctly identified as such by the CSB. Discussion/Conclusion: The CSB represents a potentially valid counseling tool to identify phonemes that have poor perceptual quality and indicate auditory access gaps.

Fixational eye movements enable robust edge detection.

Human vision relies on mechanisms that respond to luminance edges in space and time. Most edge models use orientation-selective mechanisms on multiple spatial scales and operate on static inputs assuming that edge processing occurs within a single fixational instance. Recent studies, however, demonstrate functionally relevant temporal modulations of the sensory input due to fixational eye movements. Here we propose a spatiotemporal model of human edge detection that combines elements of spatial and active vision. The model augments a spatial vision model by temporal filtering and shifts the input images over time, mimicking an active sampling scheme via fixational eye movements. The first model test was White's illusion, a lightness effect that has been shown to depend on edges. The model reproduced the spatial-frequency-specific interference with the edges by superimposing narrowband noise (1–5 cpd), similar to the psychophysical interference observed in White's effect. Second, we compare the model's edge detection performance in natural images in the presence and absence of Gaussian white noise with human-labeled contours for the same (noise-free) images. Notably, the model detects edges robustly against noise in both test cases without relying on orientation-selective processes. Eliminating model components, we demonstrate the relevance of multiscale spatiotemporal filtering and scale-specific normalization for edge detection. The proposed model facilitates efficient edge detection in (artificial) vision systems and challenges the notion that orientation-selective mechanisms are required for edge detection.

Experimental Research on Reducing Flow-Induced Cavity Resonance with a Narrowband Active Noise Control System

In this paper, active control of flow-induced cavity resonance noise is addressed. A hybrid numerical method is presented to predict the resonance frequency and, instead of traditional active flow control, a narrowband active noise control system is utilized to suppress the resonance. A duct system is built up at low Mach numbers and experiments are carried out to validate the proposed methods. The results have shown that the resonance frequency could be predicted with 1.5% errors and the flow-induced narrowband noise could be effectively suppressed at both the fundamental frequency and its first harmonic. More than 10 dB global attenuations could be achieved for the fundamental resonance frequency without noise enhancements at other frequencies. Further, it was also found that the optimal reference frequency of the narrowband active noise control system could be largely biased from the original resonance frequency, which indicates a nonlinear mechanism of the control system.

A new feedforward and feedback hybrid active noise control system for excavator interior noise

Excavator interior noise is composed of the engine order narrowband noise and the impulsive broadband noise caused by working device. In situations where only narrowband reference signal can be obtained, the feedforward active noise control (ANC) system can just eliminate the narrowband component, failing to control the broadband noise. Hybrid feedforward and feedback ANC (HANC) systems are useful for such applications where the reference signals can be partially obtained. However, existing HANC systems have the following drawbacks: coupling between subsystems; inaccurate error and reference signals; high computational complexity; performance degradation in response to the impulsive noise. To solve the above problems, this paper proposes a new feedforward and feedback HANC system consisting of 3 subsystems, namely, a delayed feedforward narrowband subsystem, a robust feedback broadband subsystem, and a supporting error calculating (SEC) subsystem. In the proposed HANC system, not only subsystems are decoupled, but also accurate error and reference signals are provided by SEC subsystem. In addition, calculating efficiency is improved by applying the delayed notch least mean square (DLMS) algorithm to the feedforward subsystem, and the system robustness is promoted by adopting the robust algorithm into the feedback subsystem. Numerous computer simulations are performed on the excavator interior noise measured under actual operating conditions. The corresponding results demonstrate the superior performance of the proposed HANC system in terms of the power spectral density of residual error, average noise reduction, robustness of the system, and calculation efficiency to the existing HANC systems. Real-time experiments on excavator interior noise showed that the proposed HANC system was efficient in eliminating broadband and narrowband mixture noise in practice.

Sound transmission through a panel with a hybrid active and semi-active control system

Semi-active control systems require significantly less energy than active solutions, while still providing substantial performance. However, active and semi-active systems can be applied in conjunction as hybrid systems, exploiting both solutions and providing high performance and reduced energy consumption. This paper proposes the use of such a hybrid active/semi-active control system for noise reduction barriers. Accounting for time-varying narrow-band noise, active structural acoustic control (ASAC) guarantees enhanced transmission loss for a noise barrier. Simultaneously, a semi-active element with a tunable mass moment of inertia allows the system to adapt to noise with varying characteristics by altering the mechanical properties of the barrier. Obtained control results demonstrate that the addition of a semi-active element is more effective than an additional active control actuator for reducing sound power in targeted frequency bands. Moreover, the proposed hybrid system may operate in two modes, allowing to further reduce overall energy consumption.

A Computational Model for Evaluating Transient Auditory Storage of Acoustic Features in Normal Listeners.

Humans are able to detect an instantaneous change in correlation, demonstrating an ability to temporally process extremely rapid changes in interaural configurations. This temporal dynamic is correlated with human listeners’ ability to store acoustic features in a transient auditory manner. The present study investigated whether the ability of transient auditory storage of acoustic features was affected by the interaural delay, which was assessed by measuring the sensitivity for detecting the instantaneous change in correlation for both wideband and narrowband correlated noise with various interaural delays. Furthermore, whether an instantaneous change in correlation between correlated interaural narrowband or wideband noise was detectable when introducing the longest interaural delay was investigated. Then, an auditory computational description model was applied to explore the relationship between wideband and narrowband simulation noise with various center frequencies in the auditory processes of lower-level transient memory of acoustic features. The computing results indicate that low-frequency information dominated perception and was more distinguishable in length than the high-frequency components, and the longest interaural delay for narrowband noise signals was highly correlated with that for wideband noise signals in the dynamic process of auditory perception.