Digital Signal Processing Procedure Research Articles

Can AI Predict the Magnitude and Direction of Ortho-K Contact Lens Decentration to Limit Induced HOAs and Astigmatism?

Background: The aim is to investigate induced higher-order aberrations (HOA)s and astigmatism as a result of non-toric ortho-k lens decentration and utilise artificial intelligence (AI) to predict its magnitude and direction. Methods: Medmont E300 Video topographer was used to scan 249 corneas before and after ortho-k wear. Custom-built MATLAB codes extracted topography data and determined lens decentration from the boundary and midpoint of the central flattened treatment zone (TZ). An evaluation was carried out by conducting Zernike polynomial fittings via a computer-coded digital signal processing procedure. Finally, an AI-based machine learning neural network algorithm was developed to predict the direction and magnitude of TZ decentration. Results: Analysis of the first 21 Zernike polynomial coefficients indicate that the four low-order and four higher-order aberration terms were changed significantly by ortho-k wear. While baseline astigmatism was not correlated with lens decentration (R = 0.09), post-ortho-k astigmatism was moderately correlated with decentration (R = 0.38) and the difference in astigmatism (R = 0.3). Decentration was classified into three groups: ≤0.50 mm, reduced astigmatism by -0.9 ± 1 D; 0.5~1 mm, increased astigmatism by 0.8 ± 0.1 D; >1 mm, increased astigmatism by 2.7 ± 1.6 D and over 50% of lenses were decentred >0.5 mm. For lenses decentred >1 mm, 29.8% of right and 42.7% of left lenses decentred temporal-inferiorly and 13.7% of right and 9.4% of left lenses decentred temporal-superiorly. AI-based prediction successfully identified the decentration direction with accuracies of 70.2% for right and 71.8% for left lenses and predicted the magnitude of decentration with root-mean-square (RMS) of 0.31 mm and 0.25 mm for right and left eyes, respectively. Conclusions: Ortho-k lens decentration is common when fitting non-toric ortho-k lenses, resulting in induced HOAs and astigmatism, with the magnitude being related to the amount of decentration. AI-based algorithms can effectively predict decentration, potentially allowing for better control over ortho-k fitting and, thus, preferred clinical outcomes.

Gradient-descent noise whitening techniques for short-reach IM-DD optical interconnects with severe bandwidth limitation.

Bandwidth limitation in optoelectrical components and the chromatic dispersion-induced power fading phenomenon cause severe inter-symbol interference (ISI) in high-speed intensity modulation and direct detection (IM-DD) optical interconnects. While the equalizer implemented in the receiver's digital signal processing procedure can mitigate ISI, it also inevitably enhances the noise located in the decayed frequency region, known as equalization-enhanced colored noise (EECN). Additionally, the nonlinear impairments of the modulator and photodetector also deteriorate the performance of the IM-DD system, especially for high-order modulation formats. In this work, we propose a gradient-descent noise whitening (GD-NW) algorithm to address EECN and extend it by introducing nonlinear kernels to simultaneously mitigate EECN and nonlinear impairments. The proposed algorithms are compared with conventional counterparts in terms of the achievable baud rate and the receiver optical power sensitivity. As a proof-of-concept experiment, we validate the principles of the proposed algorithms by successfully transmitting 360-GBd on-off-keying (OOK) and 180-GBd 4-level pulse-amplitude-modulation (PAM-4) signals in the back-to-back case under a 62-GHz brick-wall bandwidth limitation. 280-GBd OOK and 150-GBd PAM-4 transmissions are also demonstrated over 1-km standard single-mode fiber with a bit error rate below 7% hard-decision forward error correction aided by the proposed approach.

Upgraded Fiber-Optic Sensor System for Dynamic Strain Measurement in Spallation Neutron Source

We describe an upgraded fiber-optic sensor system and its performance in measuring the dynamic strains in a mercury target of the Spallation Neutron Source (SNS). Strains result from dynamic pressure waves in the stainless-steel mercury target induced by short (~700 ns), intense (up to 23.3 kJ), high-energy (~1 GeV) proton pulses. In the upgraded sensor system, the output of each sensor head is interrogated with a compact, all-fiber based Faraday Michelson interferometer, which generates interference signals with a steady phase shift. Strain waveforms are recovered from the phase-shifted interference signals using a high-speed digital signal processing procedure developed in our previous work. We demonstrate successful measurements of dynamic strain pulses, e.g., <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$400 \mu \varepsilon $ </tex-math></inline-formula> over <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$190 \mu \text{s}$ </tex-math></inline-formula> , on a recently installed SNS target using the upgraded sensor system. The measured strain waveforms are analyzed for more than 20 sensor locations and/or orientations, and provide information regarding the temporal structure of strain profiles and dependence of the strain magnitude on the proton powers of 200 – 1400 kW. The new interrogator also measures the radiation-induced-attenuation (RIA) in the optical fiber, enabling experimental investigations of RIA profiles induced by a 700-ns radiation pulse. The radiation effects on the strain measurement performance are discussed over a radiation dose range of up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${4}\times {10}^{{8}}$ </tex-math></inline-formula> Gy and an RIA compensation method is proposed. The measurements allow insight into the response of this unique piece of equipment and can be used for validation of simulations.

Spatiotemporal Image Encoding for Cross-Subject Zero Calibration Driver’s Drowsiness Detection through EEG Signals

In this digital signal processing procedure, which analyses Electroencephalogram (EEG) data within a specified framework, the signal's frequency sub-bands were broken down using DWT, and a collection of features representing the distribution of wavelet coefficients was retrieved from the sub-bands. With the use of feature extraction techniques like mean, standard deviation, and variance, the size of the data is decreased. Following that, the classifier utilised these attributes as input to determine if the input data was normal or drowsy, and it classified the data accordingly. To demonstrate the superiority of the classification process, the performance of classification is evaluated. The system's main goal is to increase the precision of patient monitoring systems, remove variations in EEG signals, and enhance process accuracy.

SIGNAL PROCESSING ALGORITHM IN MULTICHANNEL RESCUE RADAR

The stochastic task of mutual detecting, estimating the number and angle position of slow-moving targets is formulated. The angular resolution algorithm for targets is built on the principle of statistical hypotheses testing. The concept of resolution, in contrast to the Rayleigh energy criterion, involves setting a numerical value for the probability of correct resolution (i.e., the probability of correctly indicating the number of targets in the zone of responsibility of the observation system). A priori information about the characteristics of signals and interference, when targets are moving, as well as their probabilistic properties, allows to build a signal processing procedure that provides a high resolution exceeds the energy limit criterion of Rayleigh. It is shown, that resolution win becomes higher when the signal-to-noise ratio is growing up. The digital signal processing procedure is performed in real time only under the assumption of linear unidirectional movement of targets relative to the antenna system of the radar. Analytical relations for the procedure of jointly detecting the targets and measuring the angle of arrival of their signals based on analysis of statistical hypotheses are obtained. The main performance characteristics of the radar system are calculated. Recommendations on the implementation of digital signal processing algorithms for real-time operation are given.

Experimental Demonstration of Ultra-Dense WDM-PON With Seven-Core MCF-Enabled Self-Homodyne Coherent Detection

We demonstrate an ultra-dense wavelength-division-multiplexing (UDWDM) passive optical network (PON) in a spatial-division-multiplexing system utilizing our home-made seven-core multicore fiber (MCF) with a self-homodyne coherent detection (SHCD) scheme. In the SHCD system, we transmit 12 channels of 40-Gb/s UDWDM-PON signals using polarization-division-multiplexing quadrature phase-shift keying (PDM-QPSK) with a 12-GHz grid through the six outer cores of the seven-core MCF with the central core used to transmit the pilot tone. An optical frequency comb generator is employed to supply the multi-carriers for cost saving. After 37-km low-crosstalk seven-core MCF long-reach transmission with compact fan-in/fan-out multiplexers, a large transmission capacity of 2.88 Tb/s and a power budget of 26 dB are obtained. At the optical network unit side, a narrow linewidth local oscillator laser is no longer necessary since SHCD is adopted in our system. The complexity of the digital signal processing procedure at the coherent receiver is also greatly reduced as the carrier phase recovery and carrier frequency offset estimation are not needed.

Variable Sampling Composite Observer Based Frequency Locked Loop and its Application in Grid Connected System

A modified digital signal processing procedure is described for the on-line estimation of DC, fundamental and harmonics of periodic signal. A frequency locked loop (FLL) incorporated w ...

Eigenvalue Signal Processing for Weather Radar Polarimetry: Removing the Bias Induced by Antenna Coherent Cross-Channel Coupling

We present a novel digital signal processing procedure, named eigenvalue signal pocessing (henceforth ESP), patented by the first author with Brookhaven Science Associates in 2013. The method enables the removal of the bias due to antenna coherent cross-channel coupling and is applicable in the LDR mode, the ATSR mode and the STSR orthogonal mode of weather radar measurements. In this paper, we focus on the LDR mode and consider copolar reflectivity at horizontal transmit $({\rm Z}_{\rm HH})$ , cross-polar reflectivity at horizontal transmit $({\rm Z}_{\rm VH})$ , linear depolarization ratio at horizontal transmit $({\rm LDR}_{\rm H})$ and degree of polarization at horizontal transmit $({\rm DOP}_{\rm H})$ . The ESP (ESP) method is substantiated by an experiment carried out in November 2012 using C-band weather radar with a parabolic reflector located at the Selex ES—Gematronik facilities in Neuss, Germany. The experiment involved comparison of weather radar measurements taken 1.5 minutes apart in two hardware configurations, namely with cross-coupling on (cc-on) and cross-coupling off (cc-off). It is experimentally demonstrated that eigenvalue-derived variables are invariant with respect to antenna coherent cross-channel coupling. This property had to be expected, since the eigenvalues of the Coherency matrix are SU(2) invariant.

Modeling magnetostrictive material for high-speed tracking

This work proposes a simplified model applicable to devices based on magnetostrictive materials conceived to be implemented in the control of a micropositioner. The 1D magnetomechanical dynamic model of the active material is based on the Preisach hysteresis model and includes classical eddy currents. The model has been used in a digital signal processing procedure for the determination of the supply current tracking position. Comparisons with experiments, obtained by controlling the actual micropositioner in an open loop chain, are satisfactory.

Decimative Multiplication of Entropy Arrays, with Application to Influenza

The use of the digital signal processing procedure of decimation is introduced as a tool to detect patterns of information entropy distribution and is applied to information entropy in influenza A segment 7. Decimation was able to reveal patterns of entropy accumulation in archival and emerging segment 7 sequences that were not apparent in the complete, undecimated data. The low entropy accumulation along the first 25% of segment 7, revealed by the three frames of decimation, may be a sign of regulation at both protein and RNA levels to conserve important viral functions. Low segment 7 entropy values from the 2009 H1N1 swine flu pandemic suggests either that: (1) the viruses causing the current outbreak have convergently evolved to their low entropy state or (2) more likely, not enough time has yet passed for the entropy to accumulate. Because of its dependence upon the periodicity of the codon, the decimative procedure should be generalizable to any biological system.

Multivariate classification of animal communication signals: A simulation-based comparison of alternative signal processing procedures using electric fishes

Evolutionary studies of communication can benefit from classification procedures that allow individual animals to be assigned to groups (e.g. species) on the basis of high-dimension data representing their signals. Prior to classification, signals are usually transformed by a signal processing procedure into structural features. Applications of these signal processing procedures to animal communication have been largely restricted to the manual or semi-automated identification of landmark features from graphical representations of signals. Nonetheless, theory predicts that automated time-frequency-based digital signal processing (DSP) procedures can represent signals more efficiently (using fewer features) than can landmark procedures or frequency-based DSP – allowing more accurate classification. Moreover, DSP procedures are objective in that they require little previous knowledge of signal diversity, and are relatively free from potentially ungrounded assumptions of cross-taxon homology. Using a model data set of electric organ discharge waveforms from five sympatric species of the electric fish Gymnotus, we adopted an exhaustive simulation approach to investigate the classificatory performance of different signal processing procedures. We considered a landmark procedure, a frequency-based DSP procedure (the fast Fourier transform), and two kinds of time-frequency-based DSP procedures (a short-time Fourier transform, and several implementations of the discrete wavelet transform -DWT). The features derived from each of these signal processing procedures were then subjected to dimension reduction procedures to separate those features which permit the most effective discrimination among groups of signalers. We considered four alternative dimension reduction methods. Finally, each combination of reduced data was submitted to classification by linear discriminant analysis. Our results support theoretical predictions that time-frequency DSP procedures (especially DWT) permit more efficient discrimination of groups. The performance of signal processing was found to depend largely upon the dimension reduction procedure employed, and upon the number of resulting features. Because the best combinations of procedures are dataset-dependent and difficult to predict, we conclude that simulations of the kind described here, or at least simplified versions of them, should be routinely executed before classification of animal signals - especially unfamiliar ones.

Hardware and software improvements in flow-cytometry measurements

This paper deals with the hardware and software innovations of a new flow-cytometry measurement device, optimized for diagnostic applications in the oncology field. The hardware innovations regard to (i) the data acquisition system, (ii) the laser beam automatic alignment system, and (iii) the cell flow chamber. The software innovations regard to (i) the digital signal processing procedure, (ii) the optimized methodology for classification of the different cell types, and (iii) the programmable gain of each input channel. The paper describes both the hardware and the software architectures of the new flow cytometer. Moreover, the operating mode is highlighted. Preliminary experimental tests evidencing the improved performance of the new measurement device are also discussed.

Wavefront-flatness evaluation by wavefront-correlation-information-entropy method and its application for adaptive confocal microscope

A simple wavefront evaluation method is proposed which employs only one Fourier transform lens, one CCD camera and a digital signal processing procedure. The optical setup is sufficiently simple to be used in numerous types of optical systems. The feasibility of the method is demonstrated in an adaptive confocal microscope which dynamically corrects aberrations. This confocal microscope contains a deformable membrane mirror whose shape is optimized using a genetic algorithm and a wavefront evaluation method.

Accurate self-synchronizing technique for measuring transmitter phase and frequency errors in TDMA digitally encoded cellular systems

Measurement of phase and frequency errors, affecting the transmitted signal in digitally encoded cellular systems, is discussed here. To this aim, a new, cost-effective technique, particularly suitable in time domain multiple access (TDMA) systems, is proposed. In contrast to other measurement methods or instruments, the proposed technique gains burst synchronization on the analyzed signal through digital signal-processing, thus avoiding the need of sophisticated and expensive analog triggering solutions. Only a general-purpose data acquisition system is, in fact, required to capture a proper time window of the transmitted signal, preliminarily down-converted to intermediate frequency. Furthermore, in the same way as other methods or instruments, phase and frequency errors are evaluated according to a standard digital signal-processing procedure, which applies both for the actual and reference phase trajectory of the transmitted signal. The technique makes both trajectories available just at the end of the aforementioned burst synchronization stage, thus also optimizing the computational burden.

Perceptual-center modeling is affected by including acoustic rate-of-change modulations.

This study investigated the acoustic correlates of perceptual centers (p-centers) in CV and VC syllables and developed an acoustic p-center model. In Part 1, listeners located syllables' p-centers by a method-of-adjustment procedure. The CV syllables contained the consonants /s/,/r/,/n/,/t/,/d/,/k/, and /g/; the VCs, the consonants /s/,/r/, and /n/. The vowel in all syllables was /a/. The results of this experiment replicated and extended previous findings regarding the effects of phonetic variation on p-centers. In Part 2, a digital signal processing procedure was used to acoustically model p-center perception. Each stimulus was passed through a six-band digital filter, and the outputs were processed to derive low-frequency modulation components. These components were weighted according to a perceived modulation magnitude function and recombined to create six psychoacoustic envelopes containing modulation energies from 3 to 47 Hz. In this analysis, p-centers were found to be highly correlated with the time-weighted function of the rate-of-change in the psychoacoustic envelopes, multiplied by the psychoacoustic envelope magnitude increment. The results were interpreted as suggesting (1) the probable role of low-frequency energy modulations in p-center perception, and (2) the presence of perceptual processes that integrate multiple articulatory events into a single syllabic event.

Extracting quantitative information from digital electrogastrograms.

Cutaneous recordings of gastric electrical activity (electrogastrography (EGG)) could become a valuable non-invasive tool for recognising gastric electrical abnormalities. Although signals obtained with internally implanted electrodes deliver quantitative information, this technique cannot be used for diagnostic purposes because of its invasive nature. On the other hand, the objectivity of electrogastrography is still in question. The aims of this work are to develop computer techniques for extracting quantitative information from digital electrogastrograms, and to evaluate quantitatively EGG recordings from healthy volunteers. The dynamics of all four EGG parameters are studied: amplitude, frequency, time shift between different channels, and waveform. Four separate two-dimensional computer plots are developed using specially designed digital signal-processing procedures. Each parameter is evaluated in a study of 20 healthy volunteers. Frequency is found to be the only EGG parameter that shows quantitative consistency and merit.

Microdefocusing method for measuring acoustic properties using acoustic microscope

Many papers have been reporting on measuring acoustic properties of materials by acoustic microscopy. In a conventional method of V (z) curve analysis, the phase velocity and the propagation attenuation of a leaky surface acoustic wave (LSAW) are determined from the interference period Deltaz and the slope of the V(z) curve, respectively. For this method it is necessary to measure the V(z) curve for a period several times as long as the interference period Deltaz. Therefore, it is difficult to measure the acoustic properties of a sample with high resolution by the method. In order to overcome these problems, a method called the microdefocusing method is proposed. The method determines the acoustic properties of a sample by analyzing V (z) values measured in the microdefocusing region within an interference period Deltaz near a focal plane. An ultrasonic transducer called the butterfly transducer is proposed to be applied to this microdefocusing method and a digital signal processing procedure is developed to analyze the output of the ultrasonic transducer. Basic experiments are performed to confirm the principles of the new method.

Transient electromagnetic scattering: data acquisition and signal processing

A historical overview is given of the motivations and developments of transient electromagnetic scattering ranges. This is followed by a discussion of the theory and operation of the free-field transient scattering facility at the US Naval Postgraduate School. Attention is given to the concepts and methodology for the measurement and postprocessing of ultrawideband transient scattering signatures. Examples are presented to illustrate the experimental and digital signal processing procedures. The role of the facility in research support for natural resonance radar target classification is elaborated.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Measurement of mean velocities, velocity fluctuations and Reynolds stresses in a turbulent jet with a modified laser interferometric technique

A new optical technique for the measurement of flow velocities with a laser interferometric technique was reported by Menn et al. (1981). Since then the technique has been improved and the authors describe the technique as well as a digital signal processing procedure which has been developed to computer the velocity components from the signal acquired. The method was used to measure velocity fluctuations and Reynolds stresses in an axisymmetric circular air jet. Experimental results are presented and compared with measurements of previous researchers.