Complexity analysis of normal and deaf infant cry acoustic waves
نویسندگان
چکیده
This work describes the complexity found in the normal and the deaf crying acoustic waves. Using approximate entropy, in a single figure, the complexity of the auto-covariance of the signal is computed. Thus, using this complexity value, we are able to discriminate the normal and the deaf infants crying domains with
منابع مشابه
Normal and hypoacoustic infant cry signal classification using time-frequency analysis and general regression neural network
Crying is the most noticeable behavior of infancy. Infant cry signals can be used to identify physical or psychological status of an infant. Recently, acoustic analysis of infant cry signal has shown promising results and it has been proven to be an excellent tool to investigate the pathological status of an infant. This paper proposes short-time Fourier transform (STFT) based time-frequency an...
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