Syntactic signal recognizer and pattern recognizer
First Claim
1. A pattern recognizer comprising:
- a) a sequential data extractor configured to;
i) extract a region of measured data from measured data, the measured data obtained using a measuring device, the measuring device capable of detecting changes in impedance; and
ii) processing the region of measured data to determine discrete position information of the individual changes in impedance;
b) a data pairer configured to;
i) receive the processed region of measured data from the sequential data extractor;
ii) receive a priori pattern data, the a priori pattern data containing expected positions of the individual changes in impedance;
iii) associate the processed region of measured data and the a priori pattern data;
c) a programmable recognition engine device having a decision output, the decision output configured to indicate whether the associated processed region of measured data and the a priori pattern data differ within predetermined criteria, the predetermined criteria including;
i) non-expected impedance changes;
ii) excessive dither; and
iii) missing impedance changes; and
wherein the recognition engine is a serial major-minor reset finite state machine.
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Abstract
A pattern recognizer includes a sequential data extractor, a data pairer, and a recognition engine. The sequential data extractor extracts a region of measured data obtained from a measuring device. The measuring device is preferably capable of detecting changes in impedance. The measured data should contain position information of the changes in impedance. The data pairer associates the region of measured data with a priori pattern data that contains expected positions of the changes in impedance. The recognition engine decides whether the associated region of measured data and the a priori pattern data differ within predetermined criteria, the predetermined criteria including: non-expected impedance changes; excessive dither; and missing impedance changes.
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Citations
14 Claims
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1. A pattern recognizer comprising:
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a) a sequential data extractor configured to; i) extract a region of measured data from measured data, the measured data obtained using a measuring device, the measuring device capable of detecting changes in impedance; and ii) processing the region of measured data to determine discrete position information of the individual changes in impedance; b) a data pairer configured to; i) receive the processed region of measured data from the sequential data extractor; ii) receive a priori pattern data, the a priori pattern data containing expected positions of the individual changes in impedance; iii) associate the processed region of measured data and the a priori pattern data; c) a programmable recognition engine device having a decision output, the decision output configured to indicate whether the associated processed region of measured data and the a priori pattern data differ within predetermined criteria, the predetermined criteria including; i) non-expected impedance changes; ii) excessive dither; and iii) missing impedance changes; and wherein the recognition engine is a serial major-minor reset finite state machine. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A non-transitory computer readable medium comprising a multitude of instructions configured to cause one or more processors to perform a method of pattern recognition comprising:
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a) extracting a region of measured data from measured data, the measured data derived from a measuring device, the measuring device capable of detecting changes in impedance; b) processing the region of measured data to determine discrete position information of the individual changes in impedance; c) associating the region of measured data and a priori pattern data, the a priori pattern data containing the expected positions of the individual changes in impedance; and d) making a decision that indicates whether the associated region of measured data and the a priori pattern data differ within a predetermined criteria, the predetermined criteria including; i) unanticipated changes in impedance; ii) missing changes in impedance; and iii) differences in the expected positions of the changes in impedance; and wherein the recognition engine is a serial major-minor reset finite state machine. - View Dependent Claims (8, 9, 10, 11, 12)
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13. A non-transitory computer-readable medium containing a series of computer readable synthesizable modules, each of the synthesizable modules including a series of hardware description language instructions employable by one or more processors to generate digital logic, the digital logic configured to perform a method comprising:
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a) extracting a region of measured data from measured data, the measured data derived from a measuring device, the measuring device capable of detecting changes in impedance; b) processing the region of measured data to determine discrete position information of the individual changes in impedance; c) associating the region of measured data and a priori pattern data, the a priori pattern data containing the expected positions of the individual changes in impedance; and d) making a decision, using a serial major-minor reset finite state machine, that indicates whether the associated region of measured data and the a priori pattern data differ within a predetermined criteria, the predetermined criteria including; i) unanticipated changes in impedance; ii) missing changes in impedance; and iii) differences in the expected positions of the changes in impedance.
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14. A pattern recognizer comprising:
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a) a sequential data extractor configured to; i) extract a region of measured data from measured data, the measured data obtained using a measuring device, the measuring device capable of detecting individual changes in measured data; and ii) processing the region of measured data to determine discrete position information of the measured data; b) a data pairer configured to; i) receive the region of measured data from the sequential data extractor; ii) receive a priori pattern data, the a priori pattern data containing expected positions of the individual changes in the measured data; iii) generating paired data by associating the region of measured data and the a priori pattern data; c) a programmable serial major-minor reset finite state machine recognition engine device having; i) an input, the input configured to receive the paired data; and ii) a decision output, the decision output configured to indicate whether the associated region of measured data and the a priori pattern data differ within a predetermined criteria, the predetermined criteria including; (1) non-expected changes in the measured data in the paired data; (2) excessive dither in the paired data; and (3) missing impedance changes in the paired data.
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Specification