PubMed · 8147320
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D Rylaarsdam, R Arzbaecher. 1994-03-15. Error in published article.. https://doi.org/10.1016/0002-9149(94)90354-9
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A method for electrically detected magnetic resonance (EDMR) measurement at different ESR frequencies under a constant alternating magnetic field has been established wherein the accurate relationship between EDMR signal intensity (from a photoexcited silicon crystal and a silicon diode) and a resonant frequency of 300 to 900 MHz (UHF band) was systematically clarified. EDMR signal intensity from a photoexcited silicon crystal against a resonant frequency fitted the curve of y = a(1 - e(-bx)) well, which approached a constant value at higher frequencies. The increase in the EDMR signal intensity from the silicon diode at higher resonant frequencies was smaller than that from the photoexcited silicon crystal. The difference can be explained by the influence of the skin effect; i.e., the microwaves do not penetrate deep into a highly conductive sample at higher frequencies. EDMR signal intensities of samples vs microwave power were measured at 890 MHz. The EDMR signal intensity from the silicon diode continued to increase as the microwave power was increased, while the signal intensity from the photoexcited silicon crystal saturated within the range. The difference can be similarly explained: due to the skin effect, the microwaves gradually penetrate into the silicon diode as the power increases, so that even when saturation has been reached outside, the microwave field inside the diode does not reach the saturation level.
The performance of different wavelet- and wavelet packet-based methods for removing simulated noise was studied using an electrocardiogram (ECG) signal. A non-linear denoising approach was investigated by applying soft and hard thresholding methods, in which thresholds were chosen using four different methods. Coiflet wavelet and wavelet packet functions were used to build up the dyadic wavelet and optimized wavelet packet decompositions. This study involves the quantitative comparison of different denoising approaches by means of optimized error measures and visual inspection of the denoised ECG and the error signal. The localization of the denoising error within the cardiac cycle was studied by visual inspection of the denoised signal and extracting the error measures during the QRS-complex. The results showed that wavelet denoising approaches were generally more efficient than wavelet packet approaches in all cases, but with Heuristic Sure threshold selection rule as hard thresholding for white noises was used. Denoising errors tend to concentrate within the QRS-area when the wavelet approach was employed. Moreover, soft and hard non-linearities showed different balances in denoising the high-frequency parts of an ECG.