An active control method for filtered reference affine projection sign algorithm based on variable step size includes: S1, acquiring impulse noise signals and transmitting the signals to control filters; S2, transmitting the impulse noise signals by the control filters to post filters; S3, generating cancellation signals of the impulse noise signals by the post filters according to the impulse noise signals and internal active control algorithms, and transmitting the cancellation signals to a speaker; S4, sending out the cancellation signal by the speaker to superimpose with the impulse noise signals to cancel the impulse noise signal. A convex combination structure and a variable step size strategy are adopted, and by adjusting step size coefficients in the control filter structure, convergence speed of algorithm is controlled, contradiction between convergence speed and steady-state error is coordinated, convergence performance of control algorithm to impulse noises is improved, and impulse noises are effectively controlled.

The present disclosure presents a feedback active noise control system and strategy with online secondary-path modeling, and belongs to the technical field of active noise control. The linear prediction subsystem takes the residual noise as its input and separates the remaining sinusoidal noise from the broadband noise. The remaining sinusoidal noise is used effectively not only to update the controller but also to scale the auxiliary noise, while the broadband noise serves as a desired input of online secondary-path modeling subsystem. In this way, the coupling between the controller and the online secondary-path modeling subsystem is significantly mitigated, leading to both faster convergence and improved noise reduction performance. A practical scheme for refreshing the entire system is also developed to enhance its robustness against even abrupt changes with the secondary path or the primary noise. The present disclosure enhances the applicability of feedback active noise control in practical applications.

A method for reducing noise within a vehicle cabin comprising at least one error sensor and at least one sound transducer, the method comprising: the at least one error sensor measuring at least one first noise at a first location; selecting at least one sound zone from a plurality of sound zones within the cabin for reducing noise in said at least one sound zone, based on a presence of a driver and passenger(s) within the cabin; estimating at least one second noise that would have been measured at a second location within the selected at least one sound zone, based on a primary transfer function describing a primary acoustic path from the first location to the second location; the at least one sound transducer generating at least one secondary noise for reducing the at least one second noise that would have been measured at the second location.

An apparatus for providing active noise control, includes: one or more microphones configured to detect sound entering through an aperture of a building structure; a set of speakers configured to provide sound output for cancelling or reducing at least some of the sound; and a processing unit communicatively coupled to the set of speakers, wherein the processing unit is configured to provide control signals to operate the speakers, wherein the control signals are independent of an error-microphone output.

An open acoustic device (100) may include a fixing structure (120) configured to fix the acoustic device (100) near an ear of a user without blocking an ear canal of the user; a first microphone array (130) configured to acquire environmental noise (410); a signal processor (140) configured to: determine, based on the environmental noise, a primary route transfer function (420) between the first microphone array (130) and the ear canal of the user; estimate, based on the environmental noise and the primary route transfer function, a noise signal (430) at the ear canal of the user; and generate, based on the noise signal at the ear canal of the user, a noise reduction signal (440); and a speaker (150) configured to output, according to the noise reduction signal, a noise reduction acoustic wave (450), the noise reduction acoustic wave being configured to eliminate the noise signal.

A signal processing apparatus is configured to preprocess a sound wave signal and output a processed audio signal through an electromagnetic wave. The signal processing apparatus includes: a receiving unit, configured to receive at least one sound wave signal; a conversion unit, configured to convert the at least one sound wave signal to at least one audio signal; a positioning unit, configured to determine position information related to the at least one sound wave signal; a processing unit, configured to determine a sending time point of at least one audio signal based on the position information and a first time point, where the first time point is a time point at which the receiving unit receives the at least one sound wave signal; and a sending unit, configured to send the at least one audio signal through the electromagnetic wave.

The present disclosure presents a feedback active noise control system and strategy with online secondary-path modeling, and belongs to the technical field of active noise control. The linear prediction subsystem takes the residual noise as its input and separates the remaining sinusoidal noise from the broadband noise. The remaining sinusoidal noise is used effectively not only to update the controller but also to scale the auxiliary noise, while the broadband noise serves as a desired input of online secondary-path modeling subsystem. In this way, the coupling between the controller and the online secondary-path modeling subsystem is significantly mitigated, leading to both faster convergence and improved noise reduction performance. A practical scheme for refreshing the entire system is also developed to enhance its robustness against even abrupt changes with the secondary path or the primary noise. The present disclosure enhances the applicability of feedback active noise control in practical applications.

An open acoustic device (100) may include a fixing structure (120) configured to fix the acoustic device (100) near an ear of a user without blocking an ear canal of the user; a first microphone array (130) configured to acquire environmental noise (410); a signal processor (140) configured to: determine, based on the environmental noise, a primary route transfer function (420) between the first microphone array (130) and the ear canal of the user; estimate, based on the environmental noise and the primary route transfer function, a noise signal (430) at the ear canal of the user; and generate, based on the noise signal at the ear canal of the user, a noise reduction signal (440); and a speaker (150) configured to output, according to the noise reduction signal, a noise reduction acoustic wave (450), the noise reduction acoustic wave being configured to eliminate the noise signal.

A computer-implemented method for automatically optimizing a hybrid active noise cancellation system, the hybrid active noise cancellation system comprising a feedback filter and a feedforward filter, the method comprising optimizing the feedforward filter, thereby optimizing the hybrid active noise cancellation system, wherein optimization of the feedforward filter is dependent on the feedback filter.

A system has a sound generator (20) that generates superimposed sound to a sound to be manipulated. An error sensor (50) measures sound and outputs a corresponding feedback signal (e′(n)). A signal generator (91) generates a sound signal (y(n)). A controller (92) generates a control signals (λ.sub.1(n)) and (λ.sub.2(n)). The adder (94) subtracts one control signal (λ.sub.2(n)) from the feedback signal (e′(n)) and outputs a modified feedback signal (en(n)) to the signal generator (91). A weighter (95) weights the sound signal (y(n)) with the control signal (λ.sub.1(n)) and outputs the weighted sound signal (y′(n)). The generated sound signal (y(n)) is a function of the modified feedback signal (e(n)). The controller (92) generates the control signals (λ.sub.1(n), λ.sub.2(n)) such that a value of the amplitudes of the feedback signal (∥e′(n)∥) corresponds to a predefinable value (Δ).