Abstract: A computer-implemented method of processing audio data, the method comprising receiving input audio data (x) comprising a time-series of amplitude values; transforming the input audio data (x) into an input frequency band decomposition (X1) of the input audio data (x); transforming the input frequency band decomposition (X1) into a first latent representation (Z); processing the first latent representation (Z) by a first deep neural network to obtain a second latent representation (Z{circumflex over (?)}, Z1{circumflex over (?)}); transforming the second latent representation (Z{circumflex over (?)}, Z1{circumflex over (?)}) to obtain a discrete approximation (X3{circumflex over (?)}); element-wise multiplying the discrete approximation (X3{circumflex over (?)}) and a residual feature map (R, X5{circumflex over (?)}) to obtain a modified feature map, wherein the residual feature map (R, X5{circumflex over (?)}) is derived from the input frequency band decomposition (X1); processing a pre-shaped frequency band

Abstract: A method is provided for detecting limit cycles in a sigma delta modulator having an output signal that varies over a series of time intervals. In this method a first value that is indicative of the level of the modulator output signal after a predetermined time interval is stored in a first memory, and a second value that is indicative of the level of the modulator output signal after a further time interval subsequent to the predetermined time interval is stored in a second memory. The first value stored in the first memory is compared with the second value stored in the second memory, and an output indicative of a tendency for limit cycles to be produced in the modulator output signal is provided in response to such comparison. Such a method is particularly advantageous for detecting limit cycles in a sigma delta modulator as it can be implemented in a straightforward manner and offers a very accurate limit cycle detection mechanism.

Abstract: A method is provided for detecting limit cycles in a sigma delta modulator having an output signal that varies over a series of time intervals. In this method a first value that is indicative of the level of the modulator output signal after a predetermined time interval is stored in a first memory, and a second value that is indicative of the level of the modulator output signal after a further time interval subsequent to the predetermined time interval is stored in a second memory. The first value stored in the first memory is compared with the second value stored in the second memory, and an output indicative of a tendency for limit cycles to be produced in the modulator output signal is provided in response to such comparison. Such a method is particularly advantageous for detecting limit cycles in a sigma delta modulator as it can be implemented in a straightforward manner and offers a very accurate limit cycle detection mechanism.