Vehicle classification system using a passive audio input to a neural network
First Claim
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1. A passive audio classification system for classifying an object emitting sound, said system comprising:
- an analog to digital converter for converting analog sound wave characteristics associated with said object to digital sound wave characteristics;
means for converting said digital sound wave characteristics, said digital sound wave characteristics measured from a time interval, into a power spectrum;
means for applying a fuzzification function to said power spectrum to create a vector of a predetermined dimension, said vector characterizing said power spectrum; and
a neural network for receiving said vector and for producing a classification designator based on said vector.
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Abstract
A system for classifying vehicles based on the sound waved produced by the vehicles receives analog sound pressure levels and converts them to a power spectrum. Fuzzification functions, such as asymmetric wedge shaped functions, are convoluted with the power spectrum to create a vector that characterizes the power spectrum while reducing the dimensionality of the characterizing vector. A neural network analyzes the characterizing vector and produces a classification designator indicative of the class of the object associated with the analog sound pressure levels received by the system.
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Citations
22 Claims
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1. A passive audio classification system for classifying an object emitting sound, said system comprising:
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an analog to digital converter for converting analog sound wave characteristics associated with said object to digital sound wave characteristics; means for converting said digital sound wave characteristics, said digital sound wave characteristics measured from a time interval, into a power spectrum; means for applying a fuzzification function to said power spectrum to create a vector of a predetermined dimension, said vector characterizing said power spectrum; and a neural network for receiving said vector and for producing a classification designator based on said vector. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 22)
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14. A method of classifying an object emitting sound, said method comprising the steps of:
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receiving analog sound wave characteristics associated with said object, said analog sound wave characteristics measured from a time interval; convening said analog sound wave characteristics to digital sound wave characteristics; converting said digital sound wave characteristics to a power spectrum; applying a fuzzification function to said power spectrum to create a vector of a predetermined dimension for characterizing said power spectrum; and producing a class designator at a neural network based on said vector. - View Dependent Claims (15, 16, 17, 18, 19, 20, 21)
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Specification