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At least 541 records · Page 30

Simulation study of communication link for Pioneer Saturn/Uranus atmospheric entry probe

A digital simulation is presented for a candidate modem in a modeled atmospheric scintillation environment with Doppler, Doppler rate, and signal attenuation typical of the radio link conditions for an outer planets atmospheric entry probe. The results indicate that the signal acquisition characteristics and the channel error rate are acceptable for the system requirements of the radio link. The simulation also outputs data for calculating other error statistics and a quantized symbol stream from which error correction decoding can be analyzed.

Hinrichs, C. A.↗

A Ground-Based Network for Improved Validation of Satellite Carbon Dioxide and Methane Observations Over the Eastern United States

Satellite observations of greenhouse gases (GHGs), notably carbon dioxide and methane, over the Eastern United States, are currently only validated indirectly and/or sporadically. There are only four existing routine, ground-based remote sensing locations in the United States suitable for validation of satellite GHG observations: Edwards and Pasadena, CA, Lamont, OK, and Park Falls, WI as part of the Total Carbon Column Observing Network (TCCON). Among other efforts, e.g. the Network for the Detection of Atmospheric Composition Change (NDACC) and EM27/SUN deployments led by the University of Toronto, the only sites west of the Mississippi River are Park Falls, WI and Toronto, ON. The only remaining validation tools, vicarious calibration and airborne campaigns, are sporadic in space and/or time and thus coincide with only a small subsample of available soundings and conditions. As a result, satellite GHG observations over the east coast of the United States, home to more than half of its population, lack a consistent, widespread means of validation. We describe an ongoing effort to position 8 EM27/SUN spectrometers along the Eastern Seaboard over the next two years. The goals of this effort are to improve both satellite validation and our understanding of human and natural influences on the carbon cycle of the Eastern US, the former enabling the latter. This work is intended to augment past, ongoing, and future inter-agency programs, e.g., the NIST Urban Testbed, routine aircraft and aircore sampling by NOAA, and NASA’s Atmospheric Carbon and Transport (ACT)-America sub-orbital campaign, in particular by offering information on broader time and spatial scales than what is already available while maintaining the high-accuracy constraints of in situ data. We will present early analysis including siting considerations to capture local and/or background conditions and comparison to NASA’s Goddard Earth Observing System (GEOS) modeling and assimilation systems. This includes a 40-day, 3-km horizontal resolution global simulation of early 2020 and a 50-km retrospective analysis of Orbiting Carbon Observatory 2 (OCO-2) observations over 2015-present. Both are valuable tools for analyzing expected and observed signals and are useful boundary conditions for yet higher-resolution studies.

Brad Weir↗

Integration of Decentralized Graph-Based Multi-Agent Reinforcement Learning with Digital Twin for Traffic Signal Optimization

Machine learning (ML) methods, particularly Reinforcement Learning (RL), have gained widespread attention for optimizing traffic signal control in intelligent transportation systems. However, existing ML approaches often exhibit limitations in scalability and adaptability, particularly within large traffic networks. This paper introduces an innovative solution by integrating decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin to enhance traffic signal optimization, targeting the reduction of traffic congestion and network-wide fuel consumption associated with vehicle stops and stop delays. In this approach, DGMARL agents are employed to learn traffic state patterns and make informed decisions regarding traffic signal control. The integration with a Digital Twin module further facilitates this process by simulating and replicating the real-time asymmetric traffic behaviors of a complex traffic network. The evaluation of this proposed methodology utilized PTV-Vissim, a traffic simulation software, which also serves as the simulation engine for the Digital Twin. The study focused on the Martin Luther King (MLK) Smart Corridor in Chattanooga, Tennessee, USA, by considering symmetric and asymmetric road layouts and traffic conditions. Comparative analysis against an actuated signal control baseline approach revealed significant improvements. Experiment results demonstrate a remarkable 55.38% reduction in Eco_PI, a developed performance measure capturing the cumulative impact of stops and penalized stop delays on fuel consumption, over a 24 h scenario. In a PM-peak-hour scenario, the average reduction in Eco_PI reached 38.94%, indicating the substantial improvement achieved in optimizing traffic flow and reducing fuel consumption during high-demand periods. These findings underscore the effectiveness of the integrated DGMARL and Digital Twin approach in optimizing traffic signals, contributing to a more sustainable and efficient traffic management system.

42 ENGINEERING↗

Fiber-Optic Continuous Liquid Sensor for Cryogenic Propellant Gauging

An innovative fiber-optic sensor has been developed for low-thrust-level settled mass gauging with measurement uncertainty <0.5 percent over cryogenic propellant tank fill levels from 2 to 98 percent. The proposed sensor uses a single optical fiber to measure liquid level and liquid distribution of cryogenic propellants. Every point of the sensing fiber is a point sensor that not only distinguishes liquid and vapor, but also measures temperature. This sensor is able to determine the physical location of each point sensor with 1-mm spatial resolution. Acting as a continuous array of numerous liquid/vapor point sensors, the truly distributed optical sensing fiber can be installed in a propellant tank in the same manner as silicon diode point sensor stripes using only a single feedthrough to connect to an optical signal interrogation unit outside the tank. Either water or liquid nitrogen levels can be measured within 1-mm spatial resolution up to a distance of 70 meters from the optical interrogation unit. This liquid-level sensing technique was also compared to the pressure gauge measurement technique in water and liquid nitrogen contained in a vertical copper pipe with a reasonable degree of accuracy. It has been demonstrated that the sensor can measure liquid levels in multiple containers containing water or liquid nitrogen with one signal interrogation unit. The liquid levels measured by the multiple fiber sensors were consistent with those virtually measured by a ruler. The sensing performance of various optical fibers has been measured, and has demonstrated that they can survive after immersion at cryogenic temperatures. The fiber strength in liquid nitrogen has also been measured. Multiple water level tests were also conducted under various actual and theoretical vibration conditions, and demonstrated that the signal-to-noise ratio under these vibration conditions, insofar as it affects measurement accuracy, is manageable and robust enough for a wide variety of spacecraft applications. A simple solution has been developed to absorb optical energy at the termination of the optical sensor, thereby avoiding any feedback to the optical interrogation unit

Xu. Wei↗

Integration of Decentralized Graph-Based Multi-Agent Reinforcement Learning with Digital Twin for Traffic Signal Optimization

Machine learning (ML) methods, particularly Reinforcement Learning (RL), have gained widespread attention for optimizing traffic signal control in intelligent transportation systems. However, existing ML approaches often exhibit limitations in scalability and adaptability, particularly within large traffic networks. This paper introduces an innovative solution by integrating decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin to enhance traffic signal optimization, targeting the reduction of traffic congestion and network-wide fuel consumption associated with vehicle stops and stop delays. In this approach, DGMARL agents are employed to learn traffic state patterns and make informed decisions regarding traffic signal control. The integration with a Digital Twin module further facilitates this process by simulating and replicating the real-time asymmetric traffic behaviors of a complex traffic network. The evaluation of this proposed methodology utilized PTV-Vissim, a traffic simulation software, which also serves as the simulation engine for the Digital Twin. The study focused on the Martin Luther King (MLK) Smart Corridor in Chattanooga, Tennessee, USA, by considering symmetric and asymmetric road layouts and traffic conditions. Comparative analysis against an actuated signal control baseline approach revealed significant improvements. Experiment results demonstrate a remarkable 55.38% reduction in Eco_PI, a developed performance measure capturing the cumulative impact of stops and penalized stop delays on fuel consumption, over a 24 h scenario. In a PM-peak-hour scenario, the average reduction in Eco_PI reached 38.94%, indicating the substantial improvement achieved in optimizing traffic flow and reducing fuel consumption during high-demand periods. These findings underscore the effectiveness of the integrated DGMARL and Digital Twin approach in optimizing traffic signals, contributing to a more sustainable and efficient traffic management system.

actuated signal control↗

A sun acquisition sensor for spacecraft guidance and control

The combination of a strap-down analog sun acquisition sensor (AS) and an on-board digital programmable signal processor results in a versatile guidance and control system. The combination can orient the rotation axis of a spin-stabilized spacecraft to the sun no matter what the initial attitude of the spacecraft. During the sun orientation process, spacecraft spin rate can be sensed and supplied as an input to the control algorithm. If needed, the AS-signal processor combination can be used to perform a rhumb-line turn maneuver. In case of unexpected spacecraft operating conditions, or unplanned pointing directions, the signal processor program can be updated via earth-based transmission of another program to cover the new situation. Using only three radiation-hard cadmium-sulfide detectors, containing no moving parts, needing only a few microwatts of power, included in a volume of 550 cubic cm (a redundant pair), and weighing only 540 grams, the AS is a small, simple, sturdy sensing device.

Birnbaum, M. M.↗

SSTDR and FDR Detection of Un-Energized and Energized Cable Anomalies Including Thermal Degradation Using Machine Learning

Historically, cables are initially qualified for nuclear power plant use for 40 years. As plants extend their operating license to 60 and 80 years, continued use of these cables must shift to a performance-based approach since it is cost prohibitive to completely replace cables that are likely still capable of performing their design function. A variety of cable tests are available and are commonly applied during outages when the cables can be taken out of service. Frequency domain reflectometry (FDR) is one of these test methods that is being more broadly accepted and used because it not only detects anomalies along the cable with a low-voltage signal that does not stress the cable insulation, but the technique also locates the anomalies. This supports follow-up local inspection and local repair or partial replacement of a damaged cable segment. Currently, FDR testing is only applied to cables that are taken out of service since the test instrument would be damaged by operational voltages. A related technology that has found some acceptance in the aircraft and rail industry is spread spectrum time domain reflectometry (SSTDR). This technology has been implemented with a custom commercial instrument by LiveWire Innovation that is designed to operate on live cables up to 1000 volts and with a bandwidth of 48 MHz. Initial evaluation by the Pacific Northwest National Laboratory (PNNL) of the Live Wire system indicated that a broader bandwidth (BW) SSTDR may be better for many kinds of flaws. This led PNNL to develop an SSTDR laboratory instrument suitable for tests up to 500 MHz bandwidth. Testing on energized cables is also desirable for online monitoring systems so an inductive clamshell coupler was developed that allows energized cables to be tested up to at least 5 kV and likely higher voltage levels. Dielectric spectroscopy and tan delta testing plus various laboratory destructive tests were included in this data acquisition campaign directed to feed a machine learning (ML) study. With these kinds of developments, online energized cable tests may be possible with industrial adoption of such hardware advances but it will be completely impractical to have highly skilled data analysts continually examine these complex signals for indications of damage or compromised conditions. If online testing is to be implemented in new test hardware, it must be accompanied by software that can interpret the signals and alert plant operators of changing or degraded conditions. The thermally aged, shielded cable investigated here was separately treated for ML analysis. Visual analysis of electrical data showed generally increasing peaks where the cable entered and exited the oven. These peaks were not exactly aligned with expected locations, but these differences were attributed to velocity of propagation calibration errors. Only supervised ML was applied to the thermally aged data as this data was only available shortly before the committed publication date of this report. The supervised ML was structured to divide the 0 to 70-day responses as ‘normal’ from 0 to 35 days or ‘anomalous’ from 36 to 70 days, based on cable tensile elongation at break (EAB) insulation characterization. Using 80% of the data for training and 20% for testing, the supervised ML predicted normal versus anomalous was 70% accurate. Important conclusions include: • Accuracy to predict the presence of cable damage is improved from the 2023 effort by more training data. Weighted accuracies for comparisons among the instruments ranged from 67 to 89 % for unsupervised ML and 71 to 99% for supervised ML. • Based on the synthetic data tests, the unsupervised models are more generalizable to unseen anomalies. The Multi-Layer Perceptron classifier (MLP) model reported as high as 99.7% accuracy on the test data, but this dropped to 58.3% when tested on the synthetic data. In contrast, the unsupervised Pointwise model only achieved 89.7% accuracy on the experimental data but reported 78.3% accuracy on the synthetic data. • The best anomaly indicators are higher frequency (400 MHz BW) FDR data. Other tests may be interesting but for this study, this was the best predicter.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Jikiken /EXOS-B/ observation of Siple transmissions

Preliminary results of observations by the Japanese magnetospheric satellite Jikiken (EXOS-B) of Siple transmissions and VLF emissions triggered by the Siple signals are reviewed. The experiments discussed were carried out in July, August, and September of 1979 and in December 1979 and January 1980. Only four events concentrated within the period from August 14 to 18 were found in which triggered emissions were associated with Siple transmissions. The electron distributions observed on the equatorial crossing passes, when Siple triggered emissions were detected, suggest that the cyclotron resonance condition is satisfied for Siple signals and electrons of energy around 1 keV or less, provided the interaction region is inside the plasmapause. It is noted that if these emissions were generated outside the plasmapause, electron energies much higher than 10 keV would be necessary for the cyclotron interaction, which were above the range of the measurements. For the high latitude passes of August 14 and 17, the electron fluxes were found to be very small.

Kimura, I.↗

Molecular Signaling in Muscle Plasticity

Extended spaceflight under microgravity conditions leads to significant atrophy of weight-bearing muscles. Atrophy and hypertrophy are the extreme outcomes of the high degree of plasticity exhibited by skeletal muscle. Stimuli which control muscle plasticity include neuronal, hormonal, nutritional, and mechanical inputs. The mechanical stimulus for muscle is directly related to the work or exercise against a load performed. Little or no work is performed by weight-bearing muscles under microgravity conditions. A major hypothesis is that focal adhesion kinase (FAK) which is associated with integrin at the adherens junctions and costa meres of all skeletal muscles is an integral part of the major mechanism for molecular signaling upon mechanical stimulation in all muscle fibers. Additionally, we propose that myotonic protein kinase (DMPK) and dystrophin (DYSTR) also participate in distinct mechanically stimulated molecular signaling pathways that are most critical in type I and type II muscle fibers, respectively. To test these hypotheses, we will use the paradigms of hindlimb unloading and overloading in mice as models for microgravity conditions and a potential exercise countermeasure, respectively, in mice. We expect that FAK loss-of-function will impair hypertrophy and enhance atrophy in all skeletal muscle fibers whereas DYSTR and DMPK loss-of-function will have similar but more selective effects on Type IT and Type I fibers, respectively. Gene expression will be monitored by muscle-specific creatine kinase M promoter-reporter construct activity and specific MRNA and protein accumulation in the soleus (type I primarily) and plantaris (type 11 primarily) muscles. With these paradigms and assays, the following Specific Project Aims will be tested in genetically altered mice: 1) identify the roles of DYSTR and its pathway; 2) evaluate the roles of the DMPK and its pathway; 3) characterize the roles of FAK and its pathway and 4) genetically analyze the mechanisms and interactions between the FAK, DYSTR, and DMPK-associated pathways in single and specific combinations of mutants. The identification of potential signaling mechanisms may permit future development of pharmacological countermeasures for amelioration and prevention of the microgravity-induced atrophy in extended spaceflight, and the analysis of both overloading and unloading paradigms may provide further support for development of exercise-based countermeasures. Understanding the basic mechanisms of molecular signaling in muscle plasticity may aid our understanding and treatment of skeletal muscle atrophy not only in spaceflight but in similar problems of the aging population, in prolonged bed rest, and in cachexia associated with chronic disease.

Epstein, Henry F.↗

Investigations of Remote Plasma Irregularites by Radio Sounding: Applications of the Radio Plasma Imager on IMAGE

The Radio Plasma Imager (RPI) on the Imager for Magnetopause-to-Aurora Global Exploration (IMAGE) mission operates like a radar by transmitting and receiving coherent electromagnetic pulses. Long-range echoes of electromagnetic sounder waves are reflected at remote plasma cutoffs. Thus, analyses of RPI observations will yield the plasma parameters and distances to the remote reflection points. These analyses assume that the reflecting plasma surfaces are cold and are sufficiently smooth that they effectively behave as plane mirrors to the incoming sounder waves, i.e., that geometric optics can be used. The RPI will employ pulse compression and spectral integration techniques, perfected in ground-based ionospheric digital sounders, in order to enhance the signal-to-noise ratio in long-range magnetospheric sounding. When plasma irregularities exist in the remote magnetospheric plasmas that are being probed by the sounder waves, echo signatures may become complicated. Ionospheric sounding experience indicates that while topside sounding echo strengths can actually be enhanced by the presence of irregularities, ground-based sounding indicates that coherent detection techniques can still be employed. In this paper we investigate the plasma conditions that will allow coherent signals to be detected by the RPI and the signatures to be expected, such as scattering and plasma resonances, in the presence of multi-scale irregularities, may possibly have on RPI signals. Sounding of irregular plasma structures in the plasmasphere, plasmapause and magnetopause are also discussed.

Fung, Shing F.↗

Detection of large-scale organized motions in a turbulent boundary layer

This paper presents and discusses experimental data from an investigation of organized motions in a supersonic turbulent boundary layer. Conditional sampling of crossed-wire and multiple normal-wire signals is performed. A comparison is made between events detected using the VITA conditional sampling technique and those found by thresholding the UV signal. Based on this comparison, limitations of the VITA technique are discussed. The conditional sampling results indicate that most organized motions are consistent with hairpin vortices.

Fernando, E. M.↗

Extracting Ocean-Generated Tidal Magnetic Signals from Swarm Data Through Satellite Gradiometry

Ocean-generated magnetic field models of the Principal Lunar, M2, and the Larger Lunar elliptic, N2, semidiurnal tidal constituents were estimated through a "Comprehensive Inversion" of the first 20.5 months of magnetic measurements from European Space Agency's (ESA) Swarm satellite constellation mission. While the constellation provides important north-south along-track gradiometry information, it is the unique low-spacecraft pair that allows for east-west cross-track gradiometry. This latter type is crucial in delivering an M2 estimate of similar quality with that derived from over 10 years of CHAMP satellite data but over a shorter interval, at higher altitude, and during more magnetically disturbed conditions. Recovered N2 contains nonoceanic signal but is highly correlated with theoretical models in regions of maximum oceanic amplitude. Thus, satellite magnetic gradiometry may eventually enable the monitoring of ocean electrodynamic properties at temporal resolutions of 1 to 2 years, which may have important implications for the inference of ocean temperature and salinity.

Magnetic↗

Developing Signal-Pattern-Recognition Programs

Pattern Interpretation and Recognition Application Toolkit Environment (PIRATE) is a block-oriented software system that aids the development of application programs that analyze signals in real time in order to recognize signal patterns that are indicative of conditions or events of interest. PIRATE was originally intended for use in writing application programs to recognize patterns in space-shuttle telemetry signals received at Johnson Space Center's Mission Control Center: application programs were sought to (1) monitor electric currents on shuttle ac power busses to recognize activations of specific power-consuming devices, (2) monitor various pressures and infer the states of affected systems by applying a Kalman filter to the pressure signals, (3) determine fuel-leak rates from sensor data, (4) detect faults in gyroscopes through analysis of system measurements in the frequency domain, and (5) determine drift rates in inertial measurement units by regressing measurements against time. PIRATE can also be used to develop signal-pattern-recognition software for different purposes -- for example, to monitor and control manufacturing processes.

Shelton, Robert O.↗

Evaluation of a new DIII-D Doppler backscattering system for higher wavenumber measurement and signal enhancement

The high density fluctuation poloidal wavenumber, k θ (k θ > 8 cm –1 , k θ ρ s > 5, ρs is the ion gyro radius using the ion sound velocity), measurement capability of a new Doppler backscattering (DBS) system at the DIII-D tokamak has been experimentally evaluated. In DBS, wavenumber (k) matching becomes more important at higher wavenumbers, owing to the exponential dependence of the measured signal loss factor on wave vector mismatch. Wave vector matching allows for the Bragg scattering condition to be satisfied, which minimizes the signal loss at higher k’s. In the previous DBS system, without toroidal wave vector matching, the measured DBS signal-to-noise ratio at higher k θ (>8 cm –1 ) is substantially reduced, making it difficult to measure higher k θ turbulence. The new DBS system has been optimized to access higher wavenumber, k θ ≤ 20 cm –1 , density turbulence measurement. The optimization hardware addresses fluctuation wave vector matching using toroidal steering of the launch mirror to produce a backscattered signal with improved intensity. The probe’s sensitivity to high-k density fluctuations has been increased by approximately an order of magnitude compared to the old system that has been in use at DIII-D. Note that typical measurement locations are above or below the tokamak midplane on the low field side with normalized radial ranges of 0.5–1.0. As a result, the new DBS probe system with the toroidal matching of fluctuation wave vectors is thought to be critical to understanding high-k turbulent transport in fusion-relevant research at DIII-D.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Subband Coding Method for HDTV

This paper introduces a new HDTV coder based on motion compensation, subband coding, and high order conditional entropy coding. The proposed coder exploits the temporal and spatial statistical dependencies inherent in the HDTV signal by using intra- and inter-subband conditioning for coding both the motion coordinates and the residual signal. The new framework provides an easy way to control the system complexity and performance, and inherently supports multiresolution transmission. Experimental results show that the coder outperforms MPEG-2, while still maintaining relatively low complexity.

Chung, Wilson↗

Detection of Objects Hidden in Highly Scattering Media Using Time-Gated Imaging Methods

Non-intrusive and non-invasive optical imaging techniques has generated great interest among researchers for their potential applications to biological study, device characterization, surface defect detection, and jet fuel dynamics. Non-linear optical parametric amplification gate (NLOPG) has been used to detect back-scattered images of objects hidden in diluted Intralipid solutions. To directly detect objects hidden in highly scattering media, the diffusive component of light needs to be sorted out from early arrived ballistic and snake photons. In an optical imaging system, images are collected in transmission or back-scattered geometry. The early arrival photons in the transmission approach, always carry the direct information of the hidden object embedded in the turbid medium. In the back-scattered approach, the result is not so forth coming. In the presence of a scattering host, the first arrival photons in back-scattered approach will be directly photons from the host material. In the presentation, NLOPG was applied to acquire time resolved back-scattered images under the phase matching condition. A time-gated amplified signal was obtained through this NLOPG process. The system's gain was approximately 100 times. The time-gate was achieved through phase matching condition where only coherent photons retain their phase. As a result, the diffusive photons, which were the primary contributor to the background, were removed. With a large dynamic range and high resolution, time-gated early light imaging has the potential for improving rocket/aircraft design by determining jets shape and particle sizes. Refinements to these techniques may enable drop size measurements in the highly scattering, optically dense region of multi-element rocket injectors. These types of measurements should greatly enhance the design of stable, and higher performing rocket engines.

Galland, Pierre A.↗

Digital simulation of a communication link for Pioneer Saturn Uranus atmospheric entry probe, part 1

A digital simulation study is presented for a candidate modulator/demodulator design in an atmospheric scintillation environment with Doppler, Doppler rate, and signal attenuation typical of the conditions of an outer planet atmospheric probe. The simulation results indicate that the mean channel error rate with and without scintillation are similar to theoretical characterizations of the link. The simulation gives information for calculating other channel statistics and generates a quantized symbol stream on magnetic tape from which error correction decoding is analyzed. Results from the magnetic tape data analyses are also included. The receiver and bit synchronizer are modeled in the simulation at the level of hardware component parameters rather than at the loop equation level and individual hardware parameters are identified. The atmospheric scintillation amplitude and phase are modeled independently. Normal and log normal amplitude processes are studied. In each case the scintillations are low pass filtered. The receiver performance is given for a range of signal to noise ratios with and without the effects of scintillation. The performance is reviewed for critical reciever parameter variations.

Hinrichs, C. A.↗

Estimating the Single-Trial Characteristics of Event-Related Responses: Evaluation of the MCERP Algorithm

Single-trial event-related responses collected during the course of an experiment are typically averaged before analysis resulting in a rather crude picture of event-related brain dynamics. It has been quite clear for some time that these responses exhibit trial-to-trial variability: however, the computational techniques necessary to deal with such responses in noisy conditions have not been available. To this end we have developed the multiple-component, event-related potential model (mcERP), which assumes that the each event-related response consists of a sum of multiple evoked components each described by a stereotypical waveshape. These waveshapes are allowed to vary in amplitude and onset latency from trial to trial, which allows us to capture, to first-order, the trial-dependent variations in event-related brain dynamics. We have constructed many sets of synthetic data designed to simulate intracortical recordings from a 15 channel, linear-array multielectrode implanted acutely in V1 of an awake-behaving macaque undergoing visual stimulation with a red light flash. This synthetic data was used to characterize the performance of the mcERP algorithm. First we quantified the degree to which such trial-to-trial variability aids in the identification of multiple components, and we demonstrate that amplitude variability is a more important factor in component separation than latency variability. Second, we quantified the behavior of the algorithm under two distinct signal-to-noise ratio (SNR) conditions: Gaussian noise independently present in each channel, and highly correlated (1/f distributed), far-field noise presented identically in each channel of the array. The mcERP algorithm was found to be robust to noise accurately identifying all component waveshapes and their associated single-trial characteristics down to SNR levels of -20dB for Gaussian noise and -7dB for 1/f far-field noise. Comparisons of the performance of this algorithm with factor analysis (FA) and independent component analysis (ICA) will be described by Knuth et al. (SFN abstracts, 2002). In addition, the advantages of application of mcERP to real data will be described by Shah et al, (these abstracts, 2002: SFN abstracts, 2002).

Knuth, K. H.↗