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http://dx.doi.org/10.33851/JMIS.2022.9.3.233

Autocorrelation Coefficient for Detecting the Frequency of Bio-Telemetry  

Nakajima, Isao (Seisa University)
Muraki, Yoshiya (Seisa University)
Yagi, Yukako (Memorial Sloan Kettering Cancer Center)
Kurokawa, Kiyoshi (National Graduate Institute for Policy Studies, Health and Global Policy Institute)
Publication Information
Journal of Multimedia Information System / v.9, no.3, 2022 , pp. 233-244 More about this Journal
Abstract
A MATLAB program was developed to calculate the half-wavelength of a sine-curve baseband signal with white noise by using an autocorrelation function, a SG filter, and zero-crossing detection. The frequency of the input signal can be estimated from 1) the first zero-crossing (corresponding to ¼λ) and 2) the R value (the Y axis of the correlogram) at the center of the segment. Thereby, the frequency information of the preceding segment can be obtained. If the segment size were optimized, and a portion with a large zero-crossing dynamic range were obtained, the frequency discrimination ability would improve. Furthermore, if the values of the correlogram for each frequency prepared on the CPU side were prepared in a table, the volume of calculations can be reduced by 98%. As background, period detection by autocorrelation coefficients requires an integer multiple of 1/2λ (when using a sine wave as the object of the autocorrelation function), otherwise the correlogram drawn by R value will not exhibit orthogonality. Therefore, it has not been used in bio-telemetry where the frequencies move around.
Keywords
Frequency-Voltage Conversion; Orthogonality; Zero-Cross; Savitzky-Golay; Hawkmoth Receiver;
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