Signal and pattern detection or classification by estimation of continuous dynamical models
First Claim
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1. A method for detecting and classifying signals, comprising:
- acquiring a data signal from a dynamical system;
normalizing the data signal;
estimating the normalized signal'"'"'s derivative; and
performing a polynomial expansion of the normalized signal'"'"'s derivative to generate estimated coefficients.
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Abstract
A signal detection and classification technique that provides robust decision criteria for a wide range of parameters and signals strongly in the presence of noise and interfering signals. The techniques uses dynamical filters and classifiers optimized for a particular category of signals of interest. The dynamical filters and classifiers can be implemented using models based on delayed differential equations.
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2 Claims
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1. A method for detecting and classifying signals, comprising:
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acquiring a data signal from a dynamical system;
normalizing the data signal;
estimating the normalized signal'"'"'s derivative; and
performing a polynomial expansion of the normalized signal'"'"'s derivative to generate estimated coefficients. - View Dependent Claims (2)
the data signal is normalized to zero mean and unit variance; and
the polynomial expansion is performed in conjunction with a model based on delayed differential equations.
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Specification
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Current AssigneeAdobe Inc.
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Original AssigneeNonlinear Solutions, Inc.
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InventorsKadtke, James B., Kremliovsky, Michael N.
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Primary Examiner(s)ASSOUAD, PATRICK J
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Application NumberUS09/105,529Time in Patent Office1,152 DaysField of Search702/189, 702/196, 703/2, 704/243, 700/52US Class Current702/189CPC Class CodesG06F 18/21 Design or setup of recognit...
