The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jul. 26, 1994

Filed:

Apr. 22, 1993
Applicant:
Inventor:

Brian M McCarthy, Lafayette Hill, PA (US);

Assignee:
Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
H04M / ;
U.S. Cl.
CPC ...
379386 ; 379282 ; 379283 ; 379351 ; 379 89 ;
Abstract

A method of operating a digital signal processor to detect DTMF tones in a digital voice telephone system in which the digitally encoded signals appearing on the telephone channel are decimated to compress the spectrum to be monitored for the appearance of call signalling tones. The signals received in a decimated block are 'correlated' or convolved with one another on a forward and backward time-shifted basis and each forward and backward correlation product is summed to form the elements of a 5.times.5 modified covariance matrix. The modified covariance matrix exhibits the desirable property that its eigenvectors will be symmetric. Since all eigenvectors of the modified covariance matrix are orthogonal and the eigenvectors associated with the signal span the signal subspace, the signal subspace is orthogonal to the eigenvector associated with the noise. The dot product of the noise eigenvector with the signal subspace is set to zero. The roots of the resultant polynomial identify the frequencies of the DTMF tones, if in fact the same were present in the received signal. The noise and signal eigenvectors of the modified covariance matrix are more quickly and efficiently determined and advantageously, on a 'real time' basis, by partitioning the modified covariance matrix into conjugate and anti-conjugate submatrices. The conjugate matrix is inverted and its eigenvalues determined, advantageously by applying the well-known power method. The largest eigenvalue of the inverted conjugate submatrix is related to the smallest eigenvalue of the original modified covariance matrix. When appropriate tones are being received this last-mentioned eigenvector should be the eigenvector associated with the noise. After determining the noise eigenvector the product of the signal space vector and the noise eigenvector is set to zero and the roots of the resultant polynomial are identified as the frequencies of the DTMF tones, advantageously through the use of a fast search technique.


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