Signal recognition system and method

A method of creating a signal library useful in broadcast signal recognition, comprising the steps of:

• receiving a reference signal to be broadcast, and converting the reference signal into a plurality of electrical signals having different frequency bands;
• sampling each of the plurality of electrical signals at a plurality of sampling points to produce a plurality of signal values for each frequency band;
• calculating a plurality of statistical moments corresponding to the plurality of frequency bands using the plurality of signal values, each statistical moment being calculated according to the formula:
• ##EQU10## where:
• N=the number of sampling points;
• n=1<n<N
• X=the sampled signal value at a sampling point;
• .mu.=a mean of the sampled signal values;
• .sigma.=a standard deviation of the sampled signal values;
• and
• k=an integer greater than 1;
• deriving a feature vector from the calculated statistical moments;
• and
• storing the feature vector or a representation thereof in a broadcast signal memory.

A method of classifying a broadcast signal comprising the steps of:

• receiving the broadcast signal and converting it into a plurality of electrical signals having different frequency bands;
• sampling each of the plurality of electrical signals for each frequency band at a plurality of points to produce a plurality of signal values;
• deriving a multi-value feature vector from said plurality of signal values derived from said plurality of electrical signals;
• quantizing said feature vector by replacing each feature vector value with a category value determined from a predetermined quantization pattern which non-uniformly categorizes feature vector values;
• and
• accessing a predetermined broadcast signal library with the quantized vector and outputting from said library a signal identification code corresponding to the received signal.

A method of preparing a broadcast signal identification library useful in identification of broadcast signals, comprising the steps of:

• receiving a signal to be broadcast and converting it into a plurality of electrical signals having different frequency bands;
• sampling each of the plurality of electrical signals to provide a plurality of signal values for each frequency band;
• deriving a plurality of multi-value feature vectors from said plurality of signal values;
• quantizing each feature vector, including the substeps of:
• establishing a plurality of quantization levels;
• distributing the quantization levels non-uniformly over a predetermined statistical distribution of vector quantization values;
• deriving a plurality of quantization thresholds in accordance with the distributed quantization levels;
• and
• replacing each value of each multi-value feature vector with a corresponding quantization value determined by said quantization thresholds;
• and
• storing, in a broadcast signal memory, a value representing each quantized vector as the signal identification for the corresponding received signal.

A method of identifying broadcast information, comprising the steps of:

• receiving broadcast information and converting it into an electrical signal;
• spectrally analyzing the electrical signal to produce a plurality of analyzed waveforms having different frequency bands;
• forming a plurality of linear combinations of said analyzed waveforms;
• computing at least one statistical moment for each said linear combination;
• deriving a feature vector from the computed statistical moments;
• quantizing the feature vector;
• using the quantized feature vector to assess a broadcast signal memory storing a plurality of identifications of broadcast information;
• and
• identifying the received broadcast information based on the stored identifications, and outputting a signal corresponding to the received broadcast information.

A method of classifying broadcast information, comprising the steps of:

• receiving broadcast information and converting it into a received electrical signal;
• performing a spectral analysis of said received electrical signal and providing a plurality of electrical signals having different frequency bands;
• computing a plurality of linear combinations of said plurality of electrical signals;
• calculating a statistical moment for each said linear combination;
• and
• classifying the received broadcast information based on the calculated statistical moments and a plurality of predetermined broadcast signal identifications stored in a broadcast signal memory.

A method of classifying a broadcast signal comprising the steps of:

• receiving the broadcast signal and converting it into an electrical signal;
• bandpass filtering the converted electrical signal to provide a plurality of filtered signals having different frequency passbands;
• rectifying and low pass filtering the filtered signals to provide a plurality of low bandwidth signals;
• computing a plurality of linear combinations of said low bandwidth signals;
• sampling several of the linear combinations to provide several sets of sampled values;
• calculating a skew value and a kurtosis value for each set of sampled values;
• forming a feature vector form the skew and kurtosis values of the several sets of sampled values;
• quantizing the feature vector by replacing each skew and kurtosis value with a category value derived from a plurality of stored predetermined non-uniform quantization patterns;
• using the quantized vector to access a first broadcast signal memory data base storing a plurality of signal identification lists, each list capable of storing a plurality of signal identification codes;
• extracting from the first data base the signal identification list corresponding to the quantized vector;
• extracting from a second data base stored correlation signals corresponding to the signals in the signal identification list extracted from the first data base;
• correlating the extracted correlation signals with one of the linear combinations computed in said computing step;
• and
• classifying the broadcast information as similar to one of said correlation signals when its correlation with said one linear combination exceeds a predetermined threshold.

Broadcast signal recognition apparatus, comprising:

• means for receiving a broadcast signal and converting it into a plurality of electrical signals having different frequency bands;
• and
• processing means for (a) sampling each of the plurality of electrical signals at a plurality of sampling points to produce a plurality of signal values for each frequency band, (b) calculating a plurality of statistical moments corresponding to the plurality of frequency bands using the plurality of signal values, each statistical moment being calculated according to the formula:
• ##EQU12## where:
• N=the number of sampling points;
• n=1<n<N
• X=the signal value of said electrical signal at a sampling point;
• .mu.=a mean of the signal values;
• .sigma.=a standard deviation of the signal values;
• and
• k=an integer greater than 1,
• (c) storing, in a broadcast signal memory, a library containing a plurality of stored signal identifications, (d) comparing the calculated statistical moments with the plurality of stored signal identifications in said library, and (e) recognizing the received signal as similar to one of said stored signal identifications when said comparison step produces an indication that the calculated statistical moments are similar to the at least one stored signal identification, and outputting a signal indicating that the received broadcast signal is similar to the at least one stored signal identification.

Apparatus for creating a signal library useful in signal recognition comprising:

• means for receiving a reference signal to be broadcast and converting it into a plurality of electrical signals having different frequency bands;
• a broadcast signal memory;
• processing means for (a) sampling each of said plurality of electrical signals at a plurality of sampling points to produce a plurality of signal values for each frequency band, (b) calculating a plurality of statistical moments corresponding to the plurality of frequency bands using the plurality of signal values, each statistical moment being calculated according to the formula:
• ##EQU13## where:
• N=the number of sampling points;
• n=1<n<N
• X=the sampled signal value at a sampling point;
• .mu.=a mean of the sampled signal values;
• .sigma.=a standard deviation of the sampled signal values;
• and
• k=an integer greater than 1,
• (c) deriving a feature vector from the calculated statistical moments, and (d) storing the feature vector or a representation thereof in said memory.

Apparatus for preparing a broadcast signal identification library useful in identification of broadcast signals, comprising:

• receiver means for receiving a signal to be broadcast and converting it into a plurality of electrical signals having different frequency bands;
• a broadcast signal memory;
• a processor for (a) sampling each of the plurality of electrical signals to provide a plurality of signal values for each frequency band;
• (b) deriving a plurality of multi-value feature vectors from said plurality of signal values, and (c) quantizing each feature vector, including the substeps of:
• (c1) establishing a plurality of quantization levels;
• (c2) distributing the quantization levels non-uniformly over a predetermined statistical distribution of vector quantization values;
• (c3) deriving a plurality of quantization thresholds in accordance with the distributed quantization levels;
• and
• (c4) replacing each value of each multi-value feature vector with a corresponding quantization value determined by said quantization thresholds;
• and
• said processor (d) storing a value representing each quantized vector in said memory as the signal identification for the corresponding received signal.

Apparatus for identifying broadcast information, comprising:

• means for receiving broadcast information and converting it into an electrical signal;
• a broadcast signal memory storing a plurality of identifications of broadcast information;
• means for spectrally analyzing the electrical signal to produce a plurality of analyzed waveforms having different frequency bands;
• and
• processing means for (a) forming a plurality of linear combinations of said analyzed waveforms, (b) computing at least one statistical moment for each said linear combination, (c) deriving a feature vector from the computed statistical moments, (d) quantizing the feature vector, (e) using the quantized feature vector to access said plurality of identifications of broadcast information stored in said memory, and (f) identifying the received broadcast information based on the stored identifications in said memory, and outputting an identification signal corresponding to the identified received broadcast information.

Apparatus for classifying a broadcast signal comprising:

• a receiver for receiving the broadcast signal and converting it to an electrical signal;
• a broadcast signal memory;
• a computer for (a) bandpass filtering the converted electrical signal to provide a plurality of filtered signals having different frequency passbands, (b) envelope detecting and low pass filtering the filtered signals to provide a plurality of low bandwidth signals, (c) computing a plurality of linear combinations of said low bandwidth signals, (d) sampling several of the linear combinations to provide several sets of sampled values, (e) calculating a skew value and a kurtosis value for each set of sampled values, (f) forming a feature vector from the skew and kurtosis values of the several sets of sampled values, (g) quantizing the feature vector by replacing each skew and kurtosis value with a category value derived from a plurality of stored predetermined non-uniform quantization patterns stored in said memory, (h) using the quantized vector to access in said memory a first data base storing a plurality of signal identification lists, each list capable of storing a plurality of signal identification codes, (i) extracting from the first data base the signal identification list corresponding to the quantized vector, (j) extracting from a second data base stored in said memory correlation signals corresponding to the extracted signal identification list, (k) correlating the extracted correlation signals with one of the computed linear combinations, and (l) classifying the broadcast information as similar to one of said correlation signals when its correlation with said one linear combination exceeds a predetermined threshold, and outputting a signal corresponding to the classification.