A signal processing apparatus for a frequency modulation, FM, receiver, the signal processing apparatus comprising: a noise detector configured to: receive a multiplex signal representative of a stream of audio signal samples; detect samples in the received multiplex signal that are distorted by impulse noise in order to generate a noise detection signal, wherein the noise detection signal also identifies preceding and succeeding samples that are undistorted; a processor (814; 902, 904) configured to: receive a sum signal and a difference signal that are derived from the multiplex signal; receive the noise detection signal from the noise detector; determine, based on preceding and/or succeeding undistorted samples in the received sum signal and difference signal, auto-regressive model parameters (410; 510); apply the auto-regressive model parameters to the preceding undistorted samples to determine forward linear predicted values of the distorted samples (420; 520); apply the auto-regressive model parameters to the succeeding undistorted samples to determine backward linear predicted values of the distorted samples (422; 522); combine the forward and backward linear predicted values by means of a window function to determine composite predicted values of the distorted samples (424; 524); and replace the distorted samples in the received sum signal and difference signal with the composite predicted values (426; 526) to provide a reconstructed sum signal and a reconstructed difference signal. a noise detector configured to: receive a multiplex signal representative of a stream of audio signal samples; detect samples in the received multiplex signal that are distorted by impulse noise in order to generate a noise detection signal, wherein the noise detection signal also identifies preceding and succeeding samples that are undistorted; a processor (814; 902, 904) configured to: receive a sum signal and a difference signal that are derived from the multiplex signal; receive the noise detection signal from the noise detector; determine, based on preceding and/or succeeding undistorted samples in the received sum signal and difference signal, auto-regressive model parameters (410; 510); apply the auto-regressive model parameters to the preceding undistorted samples to determine forward linear predicted values of the distorted samples (420; 520); apply the auto-regressive model parameters to the succeeding undistorted samples to determine backward linear predicted values of the distorted samples (422; 522); combine the forward and backward linear predicted values by means of a window function to determine composite predicted values of the distorted samples (424; 524); and replace the distorted samples in the received sum signal and difference signal with the composite predicted values (426; 526) to provide a reconstructed sum signal and a reconstructed difference signal. receive a multiplex signal representative of a stream of audio signal samples; detect samples in the received multiplex signal that are distorted by impulse noise in order to generate a noise detection signal, wherein the noise detection signal also identifies preceding and succeeding samples that are undistorted; a processor (814; 902, 904) configured to: receive a sum signal and a difference signal that are derived from the multiplex signal; receive the noise detection signal from the noise detector; determine, based on preceding and/or succeeding undistorted samples in the received sum signal and difference signal, auto-regressive model parameters (410; 510); apply the auto-regressive model parameters to the preceding undistorted samples to determine forward linear predicted values of the distorted samples (420; 520); apply the auto-regressive model parameters to the succeeding undistorted samples to determine backward linear predicted values of the distorted samples (422; 522); combine the forward and backward linear predicted values by means of a window function to determine composite predicted values of the distorted samples (424; 524); and replace the distorted samples in the received sum signal and difference signal with the composite predicted values (426; 526) to provide a reconstructed sum signal and a reconstructed difference signal. receive a sum signal and a difference signal that are derived from the multiplex signal; receive the noise detection signal from the noise detector; determine, based on preceding and/or succeeding undistorted samples in the received sum signal and difference signal, auto-regressive model parameters (410; 510); apply the auto-regressive model parameters to the preceding undistorted samples to determine forward linear predicted values of the distorted samples (420; 520); apply the auto-regressive model parameters to the succeeding undistorted samples to determine backward linear predicted values of the distorted samples (422; 522); combine the forward and backward linear predicted values by means of a window function to determine composite predicted values of the distorted samples (424; 524); and replace the distorted samples in the received sum signal and difference signal with the composite predicted values (426; 526) to provide a reconstructed sum signal and a reconstructed difference signal.