Described a system for anomaly detection using anomaly cueing. In operation, an input image having two-dimensional (2D) image mixtures of primary components is reformatted into one-dimensional (1D) input signals. Blind source signal separation is used to separate the 1D input signals into separate output primary components, which are 1D output signals. The 1D output signals are reformatted into 2D spatially independent component output images. The system then calculates all possible pair product images of the 2D spatially independent component output images and corresponding signal-to-noise ratios. A pair product image is selected based on the peak signal-to-noise ratio and thresholded to identify anomalies in the pair product image. Several types of devices can then be controlled based on the identified anomalies in the pair product image.

The invention relates to a method for filtering an input signal (3b, 4b, 5b) relative to a physical variable of a turbine engine (9), the input signal being digitised, the method implementing frequency filtering of said signal in a computer (6) of a control system (7) of said turbine engine (9), said signal being provided at the input of the computer, a digital derivative of said signal being intended for being used by the control system (7), characterised in that it involves: —detecting an amplitude variation of said variable on said input signal, by a step of generating a second derivative signal (S) of the input signal and a step of comparing a value of the second derivative value of the input signal with at least one predetermined threshold (S.sub.1 . . . S.sub.n); and —adapting the frequency filtering of said input signal as a function of the detected amplitude variation of said variable, by a step of controlling a controlled filter (PB.sub.11) capable of applying frequency filtering to the input signal, so that the controlled filter applies or does not apply the frequency filtering as a function of a result of the comparison step.

Example embodiments disclosed herein relate to filter coefficient updating in time domain filtering. A method of processing an audio signal is disclosed. The method includes obtaining a predetermined number of target gains for a first portion of the audio signal by analyzing the first portion of the audio signal. Each of the target gains is corresponding to a subband of the audio signal. The method also includes determining filter coefficients for time domain filtering the first portion of the audio signal so as to approximate a frequency response given by the target gains. The filter coefficients are determined by iteratively selecting at least one target gain from the target gains and updating the filter coefficient based on the selected at least one target gain. Corresponding system and computer program product for processing an audio signal are also disclosed.

The invention provides a method and apparatus for filtering a temporal signal. A target magnitude frequency response H.sub.T(f) is specified (101,201) of frequency f in terms of a column vector l of K weights l.sub.k where log H.sub.T(f)=l.sup.TW(f) and W(f) is a column vector of K magnitude basis functions W.sub.k(f). A constrained frequency response H.sub.c(f) is computed (102,214) defined by log H.sub.c(f)=g.sup.TV(f) , where V(f) is a column vector of N constrained basis functions V.sub.n(f) for which each exp g.sub.nV.sub.n(f) satisfies a constraint preserved by concatenation, and g is a column vector of N coefficients satisfying a matching criterion between l.sup.TW(f) and g.sup.TV(f). An input temporal signal is received (103,212) and filtered (104,210) with the constrained frequency response H.sub.c(f) to form a filtered temporal signal; and the filtered temporal signal is output (105,211).

A receiver circuit is disclosed. The receiver circuit includes a multi-PAM input circuit to receive a multi-PAM input symbol. The input symbol exhibits one of multiple threshold levels during a sampling period. The threshold levels correspond to a set of M-bit two's-complement values within a defined set of threshold values. An adaptive filtering circuit includes a first transcoder to transcode the set of M-bit two's-complement values to a set of N-bit values, where N<M. An adaptive filter operates to filter the set of N-bit values to generate a filtered set of data values. A second transcoder transforms the filtered set of data values to a second set of data values that corresponds to a set of filtered M-bit two's-complement values.

The invention provides a method and apparatus for filtering a temporal signal. A target magnitude frequency response H.sub.T(f) is specified (101,201) of frequency f in terms of a column vector l of K weights l.sub.k where log H.sub.T(f)=l.sup.TW(f) and W(f) is a column vector of K magnitude basis functions W.sub.k(f). A constrained frequency response H.sub.c(f) is computed (102,214) defined by log H.sub.c(f)=g.sup.TV(f) , where V(f) is a column vector of N constrained basis functions V.sub.n(f) for which each exp g.sub.nV.sub.n(f) satisfies a constraint preserved by concatenation, and g is a column vector of N coefficients satisfying a matching criterion between l.sup.TW(f) and g.sup.TV(f). An input temporal signal is received (103,212) and filtered (104,210) with the constrained frequency response H.sub.c(f) to form a filtered temporal signal; and the filtered temporal signal is output (105,211).

Traditional audio feedback elimination systems may attempt to reduce the effect of the audio feedback by simply scaling down the audio volume of the signal frequencies that are prone to howling. Other traditional feedback elimination systems may also employ adaptive notch filtering to detect and notch the so-called singing or howling frequencies as they occur in real-time. Such devices may typically have several knobs and buttons needing tuning, for example: the number of adaptive parametric equalizers (PEQs) versus fixed PEQs; attack and decay timers; and/or PEQ bandwidth. Rather than removing the singing frequencies with PEQs, the devices described herein attempt to holistically model the feedback audio and then remove the entire feedback signal. Two advantages of the devices described herein are: 1.) the system can operate at a much larger loop-gain (and hence with a much higher loudspeaker volume); and 2) setup is greatly simplified (i.e., no tuning knobs or buttons).

The invention relates to a method for filtering an input signal (3b, 4b, 5b) relative to a physical variable of a turbine engine (9), the input signal being digitised, the method implementing frequency filtering of said signal in a computer (6) of a control system (7) of said turbine engine (9), said signal being provided at the input of the computer, a digital derivative of said signal being intended for being used by the control system (7), characterised in that it involves: detecting an amplitude variation of said variable on said input signal, by a step of generating a second derivative signal (S) of the input signal and a step of comparing a value of the second derivative value of the input signal with at least one predetermined threshold (S.sub.1 . . . S.sub.n); and adapting the frequency filtering of said input signal as a function of the detected amplitude variation of said variable, by a step of controlling a controlled filter (PB.sub.11) capable of applying frequency filtering to the input signal, so that the controlled filter applies or does not apply the frequency filtering as a function of a result of the comparison step.

Example embodiments disclosed herein relate to filter coefficient updating in time domain filtering. A method of processing an audio signal is disclosed. The method includes obtaining a predetermined number of target gains for a first portion of the audio signal by analyzing the first portion of the audio signal. Each of the target gains is corresponding to a subband of the audio signal. The method also includes determining filter coefficients for time domain filtering the first portion of the audio signal so as to approximate a frequency response given by the target gains. The filter coefficients are determined by iteratively selecting at least one target gain from the target gains and updating the filter coefficient based on the selected at least one target gain. Corresponding system and computer program product for processing an audio signal are also disclosed.

A sound source separation apparatus includes: a separation-matrix processor that transforms a plurality of observation signals corresponding to sounds being propagated from a plurality of sound sources into a frequency-domain signal group the separation-matrix processor updating a separation matrix based on the frequency-domain signal group and transforming the updated separation matrix into time-series filter coefficients to output; a filter-coefficient transformer that partially removes non-causal components from the filter coefficients to transform the filter coefficients, and a separator that supplies the filter coefficients to a filter group, the separator generating a plurality of separation signals separated from the plurality of observation signals corresponding to the separation matrix.