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Bilgisayar Mühendisliği Bölümü Yayın Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/253

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Browsing Bilgisayar Mühendisliği Bölümü Yayın Koleksiyonu by Author "102350"

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    Citation Count: Kondakci, S, "An approach to noise reduction in human skin admittance measurements", 23rd Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society, Vol. 23, pp. 2028-2031, (2001).
    An approach to noise reduction in human skin admittance measurements
    (IEEE, 2001) Kondakçı, Süleyman; 102350
    This paper presents the development of a signal averaging algorithm for recovering excitation responses contaminated by overwhelming amount of various types of interference in skin admittance measurements. The algorithm is designed to eliminate Gaussian-distributed noise by use of a recursive approach. The process of recovering low magnitude voltage responses from highly noise-contaminated waveforms is a CPU-intensive task. In real-time measurements, iterative reconstruction algorithm is inefficient and time consuming when slow varying input waveforms are present. To increase the quality of the reconstruction a considerably large number of recursions is required. Increasing the number of recursions is appropriate for batch processing of measurement data. However, the algorithm considers measurements in real-time, whereas required quality of signal reconstruction should be kept independent from the number of recursions.
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    Citation Count: Kondakci, S, "Efficiency evaluation of the averaging noise reduction system", 23rd Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society, Vol. 23, pp. 1958-1961, (2001).
    Efficiency evaluation of the averaging noise reduction system
    (IEEE, 2001) Kondakçı, Süleyman; 102350
    This paper presents the development of a method for estimation of denoising performance performed by an averaging algorithm presented in an earlier work Ill. The method was designed to evaluate statistical results when the noise reduction algorithm was applied to Gaussian-distributed noisy responses from a measurement system. Iterative noise reconstruction algorithm is efficient when number of iterations is kept at a higher level. However, the reduction in noise tends to converge slowly after a certain number of recursions were achieved[l]. Determination of the slow convergence point is important in order to find an optimum system configuration. Otherwise, improper usage will cause reduced system bandwidth, thus making the system useless for real-time measurements.