Effects of fixed cutoff filtering on dark- and light-adapted ERG components and the application of variable cutoff filter

Purpose Human oscillatory potentials (OPs) are derived from dark-adapted (DA) electroretinograms (ERGs) with fixed frequency cutoff filters while light-adapted (LA) OPs are generally not isolated from ERGs. Our purpose was to analyze the effect of cutoff frequencies on DA and LA ERG components using a series of fixed and variable filters. Methods DA and LA ERGs were recorded from 10 healthy eyes of 10 subjects (mean age = 20.5 ± 6.7 years) following ISCEV standards. Each signal was filtered in the Fourier domain to acquire slow (a- and b-waves; below cutoff frequency) and fast (OPs; above cutoff frequency) components. Fixed cutoff frequencies ranged from 60 to 105 Hz and a variable cutoff frequency was calculated. Results were analyzed with statistical tests and specific models. Results DA ERG components were slightly influenced by the filter cutoff frequency. In contrast, fixed and variable filters significantly changed LA components: the lower the cutoff frequency the smaller the b-wave and OP3 and the higher the OP2/OP4 amplitudes. Analyzing the filter frequency limits a transition range between 68.9 Hz and 83.9 Hz was observed where amplitudes vary. Conclusions The present report shows that DA OPs may be isolated from ERGs using filtering procedures with high-pass cutoff frequency at about 75 Hz as recommended by ISCEV. On the other hand, the spectral distribution of low-frequency and high-frequency LA ERG components may overlap. Accordingly, filtering the signal using different cutoff frequencies is not necessarily separating b-wave and OPs.

COMBINING SUPER-RESOLUTION ALGORITHM (GAUSSIAN DENOISING AND KERNEL BLURRING) AND COMPARING WITH CAMERA SUPER- RESOLUTION

A good Super Resolution (SR) algorithm is one of the key successes to filter frequency that creates noise to a picture. Previous research that has published was concluded the Camera SR is the best algorithm to filter this frequency based on their Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) results. However, the current approach to achieving high resolution have not yielded enough signal to filter unwanted pixel. Hence, there is a need to find a better approach to those leads to higher resolution through lower noise reduction. To fulfill this need, this thesis proposed to utilize two proven SR algorithms; Gaussian Denoising and Kernel Blurring. This thesis will not only be obtaining these two existing algorithms in a stand-alone form but hence the combination of them (two combinations) will also be obtained as the new possible algorithms that can be utilized to filter frequency that create noise to a picture. To reach the research objective, the method that will be used is by training a total of four algorithms one by one to a public data set that contains 200 pictures and gets the PSNR and MSE results of each algorithm. Comprehensive experimental results show that all those four SR algorithms outperform previous SR algorithms in commonly used data set with variously higher PSNR by 21% and lower MSE by 5%.

Confirmation of monoperiodicity above 20 s for two blue large-amplitude pulsators

ABSTRACT Blue large-amplitude pulsators (BLAPs) are a new class of pulsating variable stars. They are located close to the hot subdwarf branch in the Hertzsprung–Russell diagram and have spectral classes of late O or early B. Stellar evolution models indicate that these stars are likely radially pulsating, driven by iron group opacity in their interiors. A number of variable stars with a similar driving mechanism exist near the hot subdwarf branch with multiperiodic oscillations caused by either pressure (p) or gravity (g) modes. No multiperiodic signals were detected in the OGLE (Optical Gravitational Lensing Experiment) discovery light curves since it would be difficult to detect short-period signals associated with higher order p modes with the OGLE cadence. Using the RISE instrument on the Liverpool Telescope, we produced high-cadence light curves of two BLAPs, OGLE-BLAP-009 (mv = 15.65 mag) and OGLE-BLAP-014 (mv = 16.79 mag), using a 720 nm longpass filter. Frequency analysis of these light curves identifies a primary oscillation with a period of 31.935 ± 0.0098 min and an amplitude from a Fourier series fit of 0.236 mag for BLAP-009. The analysis of BLAP-014 identifies a period of 33.625 ± 0.0214 min and an amplitude of 0.225 mag. Analysis of the residual light curves reveals no additional short-period variability down to an amplitude of 15.20 ± 0.26 mmag for BLAP-009 and 58.60 ± 3.44 mmag for BLAP-014 for minimum periods of 20 and 60 s, respectively. These results further confirm that the BLAPs are monoperiodic.

Combining eye tracking with EEG: Effects of filter settings on EEG for trials containing task relevant eye-movements

Co-registration of electroencephalography (EEG) and eye movements is becoming increasingly popular, as technology advances. This new method has several advantages, including the possibility of testing non-verbal populations and infants. However, eye movements can create artefacts in EEG data. Previous methods to remove eye-movement artefacts, have used high-pass filters before data processing. However, the role of filter settings for eye-artefact exclusion has not directly been investigated. The current study examined the effect of filter settings on EEG recorded in a dataset containing task-relevant eye movements. Part 1 models the effects of filters on eye-movement artifacts and part 2 demonstrates this effect on an EEG dataset containing task-relevant eye-movements. It shows that high-pass filters can lead to significant distortions and create artificial responses that are unrelated to the target. In conclusion, high-pass filter settings of 0.1 or lower can be recommended for EEG studies involving task-relevant eye movements.HighlightsCo-registration of EEG and eye-tracking is gaining popularityHowever, eye movements can create artifacts in the EEG signalThe current paper models the effect of high pass filters on eye-movement artifactsHigh pass filters can induce large distortions in EEG data containing regular eye-movementsThe distortion is affected by fixation duration and filter frequency

Differential Kalman Filter Design for GNSS Open Loop Tracking

Global navigation satellite system (GNSS) positioning in an urban environment is in need for accurate, reliable and robust positioning. Unfortunately, conventional closed-loop tracking fails to meet the demand. The open loop tracking shows improved robustness, however, the precision is unsatisfactory. We propose a differential Kalman filter for open loop, of which the measurement vector contains the differential values of open loop navigation results between adjacent epochs. The differential Kalman filter makes use of the satellite geometry (i.e., spatial domain) and motion relationship (i.e., temporal domain) to filter frequency and code phase estimations of conventional open loop tracking. The improved performances of this architecture have been analyzed theoretically and demonstrated by road tests in an urban environment. The proposed architecture shows more than 50% accuracy improvement than the conventional open-loop tracking architecture.