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;
pre-processing the data signal;
estimating the preprocessed signal'"'"'s derivative to generate a derivative vector;
applying an expansion function to the derivative vector to generate estimated coefficients; and
processing the estimated coefficients to classify the data signal.
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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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Citations
11 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;
pre-processing the data signal;
estimating the preprocessed signal'"'"'s derivative to generate a derivative vector;
applying an expansion function to the derivative vector to generate estimated coefficients; and
processing the estimated coefficients to classify the data signal. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A method for detecting and classifying signals, comprising:
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acquiring a data signal from a dynamical system;
pre-processing the data signal;
estimating the preprocessed signal'"'"'s derivative to generate a derivative vector; and
applying an expansion function to the derivative vector to generate estimated coefficients by performing a polynomial expansion on the derivative vector to generate a design matrix, and decomposing the design matrix to generate a feature vector having the estimated coefficients. - View Dependent Claims (8, 9)
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10. A method for detecting and classifying signals, comprising:
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acquiring a data signal from a dynamical system;
pre-processing the data signal;
estimating the preprocessed signal'"'"'s derivative to generate a derivative vector; and
applying an expansion function to the derivative vector to generate estimated coefficients by performing a orthogonal function expansion on the derivative vector to generate a design matrix, and decomposing the design matrix to generate a feature vector having the estimated coefficients.
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11. A method for detecting and classifying signals, comprising:
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acquiring a data signal from a dynamical system, wherein the data signal comprises at least one two-dimensional image;
pre-processing the data signal;
estimating the preprocessed signal'"'"'s derivative to generate a derivative vector; and
applying an expansion function to the derivative vector to generate estimated coefficients.
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Specification