An active noise cancellation system for cancelling environmental noise in a plurality of sound zones, comprising: a plurality of sound zones, each including one or more microphones and one or more loudspeakers ; a diagonalization matrix precomputed before runtime of the active noise cancellation system , wherein, in an offline acoustic tuning and design of the diagonalization filter matrix , the diagonalization filter matrix is tuned to group the loudspeakers to the sound zones based on acoustic measurement data of the loudspeakers to microphone transfer functions; and an audio processor programmed to: generate adaptive filter output signals, based on reference signals and feedback error signals through a set of adaptive filters , using an estimated acoustic transfer function that provides an estimated effect on sound waves traversing a physical path , the set of adaptive filters being driven by a learning algorithm unit receiving as input at least frequency-domain reference signals and error processing output signals generated from estimated output signals and from the feedback error signals ; sum the adaptive filter output signals to generate a set of anti-noise signals per sound zone; process the set of anti-noise signals using the diagonalization matrix to generate a set of output signals per loudspeaker ; and drive the loudspeakers using the output signals per loudspeaker to apply the anti-noise signals to cancel the environmental noise in each sound zone. a plurality of sound zones, each including one or more microphones and one or more loudspeakers ; a diagonalization matrix precomputed before runtime of the active noise cancellation system , wherein, in an offline acoustic tuning and design of the diagonalization filter matrix , the diagonalization filter matrix is tuned to group the loudspeakers to the sound zones based on acoustic measurement data of the loudspeakers to microphone transfer functions; and an audio processor programmed to: generate adaptive filter output signals, based on reference signals and feedback error signals through a set of adaptive filters , using an estimated acoustic transfer function that provides an estimated effect on sound waves traversing a physical path , the set of adaptive filters being driven by a learning algorithm unit receiving as input at least frequency-domain reference signals and error processing output signals generated from estimated output signals and from the feedback error signals ; sum the adaptive filter output signals to generate a set of anti-noise signals per sound zone; process the set of anti-noise signals using the diagonalization matrix to generate a set of output signals per loudspeaker ; and drive the loudspeakers using the output signals per loudspeaker to apply the anti-noise signals to cancel the environmental noise in each sound zone. generate adaptive filter output signals, based on reference signals and feedback error signals through a set of adaptive filters , using an estimated acoustic transfer function that provides an estimated effect on sound waves traversing a physical path , the set of adaptive filters being driven by a learning algorithm unit receiving as input at least frequency-domain reference signals and error processing output signals generated from estimated output signals and from the feedback error signals ; sum the adaptive filter output signals to generate a set of anti-noise signals per sound zone; process the set of anti-noise signals using the diagonalization matrix to generate a set of output signals per loudspeaker ; and drive the loudspeakers using the output signals per loudspeaker to apply the anti-noise signals to cancel the environmental noise in each sound zone. <EOS>