Signal extraction

An adaptive method of extracting at least one of desired electro magnetic wave signals,

• sound wave signals (40, 42), and any other signals from a mixture of signals (40, 42, 44, 46) and suppressing noise and interfering signals to produce enhanced signals (50) corresponding to desired (10) signals, said method comprising the steps of:
• said at least one of continuous-time and/or correspondingly discrete-time desired signals being predetermined by one or more parameter(s), wherein one of said parameters is the shape of their statistical probability density functions (pdf);
• said desired signal(s) parameter(s) differing from said noise and interfering signals' parameter(s);
• received signal data from said desired (10) source and noise and interfering signals being collected through at least one suitable sensor means (12) for that purpose, sampling said continuous-time input signals to form discrete-time input signals, or processing correspondingly discrete-time signals;
• transforming (82) said signal data into a set of sub-bands;
• at least one of attenuating for each time-frame of input signals in each sub-band for all signals such that desired signals are attenuated less than noise and interfering signals and/or amplifying for each time-frame of input signals in each sub-band for all signals such that desired (10) signals are amplified, and that they are amplified more than noise and interfering signals;
• updating filter coefficients (90) for each time-frame of input signals in each sub-band so that an error criterion between the filtered input signals and transformed output signals is minimized;
• and
• said sub-band signals being filtered (90) by a predetermined set of sub-band filters producing a predetermined number of output signals each one of them favoring said desired signals on the basis of the distinguishing parameter(s), wherein the parameter for distinguishing between the different signals in the mixture is based on the pdf;
• and
• reconstructing said sub-band output signals with an inverse transformation (100);

An apparatus adaptively extracting at least one of desired electro magnetic wave signals, sound wave signals (40, 42), and any other signals from a mixture of signals (40, 42, 44, 46) and suppressing noise and interfering signals to produce enhanced signals (50) corresponding to desired (10) signals, comprising:

• functions adapted to determine one or more distinguishing parameters of at least one of continuous-time and/or correspondingly discrete-time, desired signals, wherein one of said parameters is the shape of their statistical probability density functions (pdf), said distinguishing parameter(s) differing from said noise and interfering signals' parameter(s);
• at least one sensor (12) adapted to collect signal data from desired (10) signals, noise and interfering signals, sampling said continuous-time input signals to form a set of discrete-time input signals, or processing correspondingly discrete-time signals;
• a transformer (82) adapted to transform said signal data into a set of sub-bands;
• an amplifier and/or attenuator adapted to amplify or attenuate each time-frame of input signals in each sub-band for all signals such that desired signals are amplified or attentuated, and that they are amplified more or less than noise and interfering signals;
• a set of filter coefficients (90) for each time-frame of input signals in each sub-band, adapted to being updated so that an error criterion between the filtered input signals and transformed output signals is minimized;
• and
• a set of filter coefficients (90) adapted so that said sub-band signals are being filtered by a predetermined set of sub-band filters producing a predetermined number of said output signals each one of them favoring desired signals defined by the distinguishing parameter(s), wherein the parameter for distinguishing between the different signals in the mixture is based on the pdf;
• and
• a reconstruction adapted to perform an inverse transformation (100) to said sub-band output signals.