Power Spectrum Density Analysis Research Articles

Reinforcement Learning-Based Mobile AR/VR Multipath Transmission With Streaming Power Spectrum Density Analysis

Multi-path transmission control protocol (MPTCP) is an extension of TCP that enables the concurrent transmission of information through different network interfaces (e.g., Cellular, Wi-Fi, 802.11p, and so on) available at terminal side. It is well known that MPTCP can provide significant advantages in bandwidth aggregation and transmission stability. Unfortunately, path diversity can limit bandwidth aggregation efficiency and incur higher delays. These issues become critical when in presence of emerging mobile AR and VR applications, which are bandwidth hungry, time-sensitive and exhibit abrupt variations of the bitrate. To address these issues, we propose the <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</u> einforcement <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</u> earning-based mobile AR/VR multipath transmission with streaming <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P</u> ower <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</u> pectrum <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</u> ensity analysis (RL-PSD). RL-PSD analyses the Power Spectrum Density (PSD) of the AR/VR input stream to extract its features. Then, both the input stream and network features are considered to model the MPTCP congestion control as an reinforcement learning process. Finally, a two-stage reinforcement algorithm is proposed to optimize transmission performance. RL-PSD has been tested in both single-terminal and multi-terminal scenarios: results show that it outperforms the other advanced solutions conceived to support the multipath transmission of AR/VR streams.

Prediction of REM (Rapid Eye Movement) Sleep Behaviour Disorder using EEG Signal applied EMG1 and EMG2 Channel

This sleep disorder is reflected as the changes in the electrical activities and chemical activities in the brain that can be observed by capturing the brain signals and the images. In this research, Short Time-frequency analysis of Power Spectrum Density (STFAPSD) approach applied on Electroencephalogram (EEG) Signals for prediction of RBD sleep disorder. Collection of Electroencephalogram (EEG) of normal subjects &amp; different type of sleep disordered subjects &amp; application of signal processing on EEG data for development the algorithm for detection of sleep disorder and implementation in MATLAB.

A comparative study of dynamic mode decomposition methods for mode identification in a cryogenic swirl injector

The dynamic mode decomposition (DMD) is one of the post-processing methods used in analyzing dynamic or transient flow field data from experiments or CFD analyses. This method extracts resonant frequencies, damping coefficients, and spatial structures of mode shapes without a priori physical knowledge of the specific form of structure or power spectrum density analysis. The optimized DMD method is applied to improve the accuracy of DMD results in finding the eigen-components by fitting the nonlinear dynamic system from initial eigenvalues and modes determined by applying the exact DMD. A comparison is made between the optimized DMD and the exact DMD method. Two DMD methods are applied to the numerical data calculated with a cryogenic swirl injector to show validity of their algorithms in identifying acoustic modes of a dynamic system. Compared with the exact DMD, the optimized DMD can extract feasibly the acoustic modes of the dynamic system with higher accuracy. Furthermore, the optimized DMD can find the resonant modes of the system more completely.

Control and modelling evaluation of a piezoelectric harvester system

The predominant role of a piezoelectric harvester system in Vibration Energy Harvesting (VEH) is to gather vibrations energy caused by road profile disturbances. In this paper, a new piezoelectric harvester model with two degrees of freedom is modelled by the Bond Graph technics and simulated in a 20-Sim environment connected to MATLAB/Simulink software. The proposed modelling techniques have the ability to extend the ride comfort of the driver when the electric vehicle is moving upon different types of road profiles such as random road surfaces. The proposed harvester system is used to examine and ensure the health criterion and ride comfort of drives. Further, simulation results in the time domain and electrical power spectrum density analysis are carried out for the EV and proposed modelling techniques. The simulation results confirm that the proposed piezoelectric harvester system is more efficient in all different dimensions, and significantly improves the ride comfort, and increases the power quantity for the three different road classes. Finally, the results are illustrated and discussed graphically for various particular cases.

Clinical significance of electroencephalography power spectrum density and functional connection analysis in neonates with hypoxic-ischemic encephalopathy.

To investigate the effects of electroencephalography (EEG) power and functional connectivity analysis on cerebral cortex function in neonates with hypoxic-ischemic encephalopathy (HIE), and to identify the neurobiological indicators of neural development in HIE. We recruited 20 mild HIE neonates, 15 moderate HIE neonates, and 30 controls. EEG was performed about 72hr after birth. The power spectral density (PSD) and imaginary part of coherency (ICOH) were analyzed. Gesell developmental schedule (GDS) was used to evaluate the neural development in the mild and moderate HIE groups at 1year of age, and the correlation between the quantitative EEG results and the state of neural development was analyzed. Compared with the controls, FP1, FP2, C3, C4, Fz, Cz, Pz , F3, and P4 of moderate HIE neonates showed that the PSD of theta, alpha and beta bands decreased significantly. In terms of the mean whole-brain PSD, themoderate HIEgroupshowed a significant decrease in all frequency bands. ICOH of the moderate HIE group showed that functional connectivity was significantly less than that in the controls mainly in the delta band, and the functional connectivity of the delta, theta, alpha1, and alpha2 bands was markedly reduced compared with the mild HIE. GDS test at 1year old showed that two infants in the moderate HIE group had suspected neurological delay in gross motor and language. The developmental quotient(DQ) of gross motor, language, and personal-social ability in the moderate HIE group were significantly lower than in the mild HIE group. And there was a significant positive correlation between PSD in each EEG frequency band and GDS score in the moderate HIE group. PSD and ICOH can be used to evaluate brain function. PSD can detect the delayed neurological development in infants with moderate HIE, and can be a neurobiomarker of brain development in HIE.

Experimental study of crossflow instability in a Mach 6 delta wing flow

In this paper, the traveling crossflow instability in the boundary layer on the windward side of a delta wing is studied. The experiments are carried out in a Mach 6 low-noise wind tunnel, with the angles of attack of the model being 5° and 10°, and the Reynolds number being in a range of 2.43 × 10&lt;sup&gt;6&lt;/sup&gt;–14.21 × 10&lt;sup&gt;6&lt;/sup&gt; m&lt;sup&gt;–1&lt;/sup&gt;. The wall fluctuation pressure is measured by fast-response Kulite pressure transducers. The power spectrum density (PSD) analysis is conducted to obtain the disturbance waves' development process in the boundary layer. The temperature-sensitive paints (TSPs) and nano-tracer based planar laser scattering (NPLS) technique are also used. From the TSP results, the boundary layer transition near the leading edge of the delta wing is smooth and parallel to the leading edge. A peak around 10 kHz in power spectrum density is detected by the fast-response pressure sensor, which may be caused by the traveling crossflow waves. To verify this dominant mode, an NPLS image in the plane of &lt;i&gt;n&lt;/i&gt; = 36 mm is obtained. The shapes of vortex structures correspond to the shapes of the crossflow vortices from the numerical simulation. Only when the boundary layer is laminar can the traveling crossflow wave signal be observed from the PSD curves. When the boundary layer is at a transitional or turbulent phase, the low-frequency component is dominant in the PSD curve. With the increase of Reynolds number, the characteristic frequency of the crossflow wave increases, and the wave’s amplitude first increases and then decreases. Moreover, the angle of attack effect is obtained. The increasing of the angle of attack can make the traveling crossflow wave grow faster and saturate, attenuate at the position closer to the leading edge of the delta wing or at a lower Reynolds number. By sensor pairs composed of three Kulite transducers, the phase velocity and the propagation angle of the traveling crossflow wave are investigated. The dimensionless phase velocities of the traveling wave are in ranges of 0.24–0.26 and 0.26–0.32 at 5° and 10° angles of attack, respectively. The propagation angles are at 50°–60° and 40°–55° at the angles of attack of 5° and 10°, respectively. At a larger angle of attack, the traveling wave’s propagation angel is smaller, but the phase velocity is bigger. It may be because the spanwise pressure gradient is higher at a larger angle of attack, and then the crossflow velocity is stronger.

Intranasal Ketamine for Acute Pain: Behavioral and Neurophysiological Safety Analysis in Mice

BackgroundSubanesthetic ketamine has been used for treatment-resistant depression and is popular as an opioid-sparing agent.ObjectiveThe present study aimed to investigate the dose-dependent antinociceptive effect of intranasal ketamine (INK) along with behavioral and neurophysiological safety in mice.MethodsAntinociceptive efficacy was evaluated in the terms of thermal nociceptive response and formalin test. The safety studies were carried out separately in healthy mice using telemetry-based cortical electroencephalography, hemodynamic changes, and spontaneous behavioral functions, including anxiety, stereotypic movement, and locomotor functions.ResultsINK administration significantly augmented the thermal nociceptive threshold and alleviated the pain response in the tonic phase of the formalin test. The results showed the dose-independent effectiveness of ketamine for thermal nociceptive responses because there were no significant differences among different INK dose groups. Behavioral safety analysis using the open field exploratory test revealed no significant effect of INK on anxiety-like functions in healthy mice. However, INK mice showed significantly more stereotypic movement but slower locomotor activities. The electroencephalography signal power spectrum density analysis revealed no significant changes by INK administration except a lower value in the α range. No significant changes were reported in heart rate, diastolic blood pressure, or systolic blood pressure at the higher dose equivalent used in the pain model.ConclusionsThe study demonstrated the behavioral and neurophysiological safety of INK, although it had a mild sedative effect. Therefore, INK is suggested as a potentially safe candidate for the management of acute pain. (Curr Ther Res Clin Exp. 2021; 82:XXX–XXX)© 2021 Elsevier HS Journals, Inc.

Analysis of Overturning and Vibration during Field Operation of a Tractor-Mounted 4-Row Radish Collector toward Ensuring User Safety

The overturning stability and vibration of upland crop machinery under development are important issues for analysis because farms for upland crops are usually uneven, which may cause work-related fatalities, and vibration affects user comfort and reduces the durability of components. In this study, the overturning stability and vibration of a tractor-mounted radish collector were investigated to ensure safety during radish collection. To analyze lateral stability, the center of gravity (CG) of the tractor-mounted radish collector system was calculated mathematically. Then, a simulation was performed to determine the lateral overturning angles at different folding positions of the radish conveyor belt and load conditions, and the results were validated through tests. Vibration sensors were used to measure the vibration levels and the power spectrum density (PSD) was obtained to check the cyclic apparatuses of the major frequencies. The load conditions, different conveyor speeds, and locations were considered as factors affecting the vibration levels. Considering the physical parameters of the tractor–collector system, the analytical overturning angle was 30.5°. The average overturning angle difference between the simulation and validation was 5°, and the difference between loaded and unloaded conditions was 2°. For 0, 45, and 90° folding positions of the conveyor belt, overturning angles increased and varied from 0.5 to 1°. The vibration level was greater under the unloaded conditions and increased with an increase in the conveyor speed. Vibrations under the loaded condition (0.37~0.48 ms−2) satisfied the ISO (International Organization for Standardization) standard (except the first conveyor belt). According to the PSD analysis, high magnitude peaks (&gt;25 dB) appeared frequently in all directions, which indicates a high possibility of damage to the first conveyor belt. This study provides useful information for improving the safety and durability of agricultural machinery for uneven and sloped field conditions.

6 Hz transcranial alternating current stimulation of mPFC improves sustained attention and modulates alpha phase synchronization and power in dorsal attention network

ABSTRACT Transcranial alternating current stimulation (tACS) is a noninvasive brain stimulation tool appropriate to modulate cortical oscillations and activity via the application of weak currents. The major goal of this study was to investigate the effects of medial Prefrontal Cortex (mPFC) stimulation on sustained attention task performance measured by Rapid Visual Information Processing (RVIP) task and the brain networks assumed to be critical to sustained attention. mPFC has been shown to be involved in sustained attention performance and as a main hub in default mode network (DMN). mPFC activity modulation via theta tACS was implemented in this study. This was a single blind study with 21 participants receiving active and sham stimulation with the electrodes on FPz and the Inion. tACS was able to impact different RVIP measures (total hits, A’ (sensitivity to target), total correct rejection, etc.). Relative power spectrum density (PSD) analysis yielded significant increases in theta frequency mostly in the fronto-central regions after active tACS and current source density (CSD) analysis yielded significant power modulations in theta frequency band in post-central gyrus. Furthermore, phase locking value (PLV) analysis showed that there were significant changes in cortical connections in the Dorsal Attention Network (DAN) in alpha frequency band. This study showed that theta frequency tACS over mPFC, was able to produce significant modulations in an RVIP task and its associated brain networks in healthy participants.

Multi-Sensor Data Fusion for Remaining Useful Life Prediction of Machining Tools by IABC-BPNN in Dry Milling Operations.

Inefficient remaining useful life (RUL) estimation may cause unpredictable failures and unscheduled maintenance of machining tools. Multi-sensor data fusion will improve the RUL prediction reliability by fusing more sensor information related to the machining process of tools. In this paper, a multi-sensor data fusion system for online RUL prediction of machining tools is proposed. The system integrates multi-sensor signal collection, signal preprocess by a complementary ensemble empirical mode decomposition, feature extraction in time domain, frequency domain and time-frequency domain by such methods as statistical analysis, power spectrum density analysis and Hilbert-Huang transform, feature selection by a Light Gradient Boosting Machine method, feature fusion by a tool wear prediction model based on back propagation neural network optimized by improved artificial bee colony (IABC-BPNN) algorithm, and the online RUL prediction model by a polynomial curve fitting method. An example is used to verify whether if the prediction performance of the proposed system is stable and reliable, and the results show that it is superior to its rivals.

The effect of using activity workstations on heart rate variability during complex cognitive tasks

Objectives The purpose of the current study was to examine the effects of using an activity workstation on the physiological stress response as measured by heart rate variability while completing cognitively demanding tasks. Participants: Eleven college students (6 females; age: 19.4 ± 0.9 years) participated in the study. Methods: The participants completed three psychologically stressful cognitive tasks while seated at a traditional desk and while using an activity workstation. Heart rate variability was recorded and analyzed with power spectrum density and time-domain analysis. Results: Using activity workstations while completing stressful cognitive tasks did not negatively affect task performance. There was; however, a reduction in low frequency heart rate variability but no change in cardiac sympathovagal balance. Conclusion: The results indicate that using activity workstations while completing difficult tasks reduces sympathetic reactivity to stress in college students. This suggests that using activity workstations could provide a coping mechanism for stress.

Lipid Hydroperoxidation Effect on the Dynamical Evolution of the Conductance Process in Bilayer Lipid Membranes: A Condition Toward Criticality.

Cell membranes are one of the main targets of oxidative processes mediated by reactive oxygen species (ROS). These chemical species interact with unsaturated fatty acids of membrane lipids, triggering an autocatalytic chain reaction, producing lipid hydroperoxides (LOOHs) as the first relatively stable product of the ROS-mediated lipid peroxidation (LPO) process. Numerous biophysical and computational studies have been carried out to elucidate the LPO impact on the structure and organization of lipid membranes. However, although LOOHs are the major primary product of LPO of polyunsaturated fatty acids (PUFAs), to the best of our knowledge, there is no experimental evidence on the effects of the accumulation of these LPO byproducts on the electrical properties and the underlying dynamics of lipid membranes. In this work, bilayer lipid membranes (BLMs) containing 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocoline (POPC) with increasing hydroperoxidized POPC (POPC-OOH) molar proportions (BLMPC/PC-OOH) are used as model membranes to investigate the effect of LOOH-mediated LPO propagation on the electrical behavior of lipid bilayers. Voltage-induced ion current signals are analyzed by applying the fractal method of power spectrum density (PSD) analysis. We experimentally prove that, when certain LOOH concentration and energy threshold are overcome, oxidized membranes evolve toward a critical state characterized by the emergence of non-linear electrical behavior dynamics and the pore-type metastable structures formation. PSD analysis shows that temporal dynamics exhibiting "white" noise (non-time correlations) reflects a linear relationship between the input and output signals, while long-term correlations (β > 0.5) begin to be observed closely to the transition (critical point) from linear (Ohmic) to nonlinear (non-Ohmic) behavior. The generation of lipid pores appears to arise as an optimized energy dissipation mechanism based on the system's ability to self-organize and generate ordered structures capable of dissipating energy gradients more efficiently under stressful oxidative conditions.

Numerical analysis and performance enhancement of active suspension system using bat optimization

The predominant role of an active suspension system in Heavy Duty Vehicles (HDV) is to minimize vibrations caused by road disturbances. In this study, linear two degrees of freedom HDV model is simulated in a MATLAB/Simulink environment. The conventional Proportional Integral and Derivative (PID) controller has little effect on vibration suppression. To reduce the effect of vibration in the HDV, the PID controller’s output parameters are optimized by bat and Grey Wolf optimization techniques. The proposed optimization techniques have the potential to enrich the ride comfort of the passenger when the HDV is travelling over different types of road surfaces such as step, sinusoidal and ISO 8608 random road profiles. The ISO 2631 standard is used to examine the health criterion and ride comfort of the passengers. Further, comparative time domain and power spectrum density analyses are carried out for the PID controller and proposed optimization techniques. The simulation results confirm that the proposed bat tuned PID is more efficient in all aspects and significantly improves the ride comfort for the three different road profiles.

Proposal of frequency‐based decomposition approach for minimization of errors in surface texture parameter calculation

In this paper, the frequency‐based decomposition approach (FBDA) for preprocessing of surface texture parameters calculation/assessment was proposed. Two types of textures were analysed: turned or grinded details. They were measured with interferometric method. For detection/minimization of high‐frequency measuring errors (HFME) the wavelets, Haar, Daubechies, Coiflet, biorthogonal or reverse‐biorthogonal approaches were proposed. Moreover, in some cases, the power spectrum density and/or autocorrelation function analysis provided an additional and/or valuable information about surface texture/features as well. It was assumed that application of various extraction methods (such as FBDA) can provide reasonable results for noise extraction in accordance to the commonly used algorithms, such as median filter, moving average (arithmetic mean) filter or other denoising procedures (e.g., Gaussian denoising filter) proposed in commercial software. The influence of proposed procedure on calculation (error minimization) of surface topography parameters (from ISO 25178 standard) was also presented. Some errors (especially those caused by false estimation of noise‐removal procedure) in surface topography parameter calculation were comprehensively studied with profile analysis; for areal HFME decomposition, the noise surface was defined. For some turned details, the HFME was observed in profiles analysis mostly. The biggest high frequencies from removed noise surface (created by noise extraction with FBDA) contained, the better results (of proposed approach) were obtained. It was also assumed that FBDA for preprocessing of both grinded and turned surfaces with various decomposition filters (in some cases the RBW) gave more ‘direct results’ that commonly used denoising approaches.

Peak Alpha Frequency in Relation to Cognitive Performance

Objective Peak alpha frequency (PAF) is reported to be a nervous system property which is genetically endowed and reflected in individual’s cognitive functioning. Cognitive performance denotes the mental processes for effective changes in response to situations in general and mental task in particular. None of the study has till now used reading comprehension as a measure of cognitive functioning, which is considered to be a measure of higher cognitive processes. The reading comprehension task used in the study implies certain cognitive processes such as reading ability, comprehension, memory performance involving information maintenance, and retrieval. Therefore, the study was conducted to test the hypothesis of differences in cognitive reading comprehension performance between high- and low-peak alpha subjects. Materials and Methods A group of 300 healthy participants were selected on the basis of incidental-cum-probabilistic sampling from seven districts of Indian state of Haryana. In the present study, reading comprehension task (Hindi–English; bilingual format) was used to assess the cognitive performance and multichannel electroencephalography alpha frequencies were recorded to measure PAF through power spectrum density analysis of each subject. Results The findings revealed that individuals with high-peak alpha frequency had significantly higher score ( p < 0.05) on reading comprehension task as compared with individuals with low PAF. Conclusion The present study concluded that the reading comprehension task is effected by peak alpha frequency of an individual. PAF can be considered to be a correlate of cognitive performance.

Shear-induced viscosity stratified flow past a pair of heated side-by-side square cylinders in a confined domain

In this article, investigations have been carried out to decipher the effect of thermal buoyancy in a viscosity stratified flow field for a shear-thinning fluid flowing past a pair of heated side-by-side square cylinders, which is an extension part of our recent study [Sanyal, A. and Dhiman, A., “Wake interactions in a fluid flow past a pair of side-by-side square cylinders in presence of mixed convection,” Phys. Fluids 29, 103602 (2017)]. It is found that the leading-edge flow-separations from the square cylinders influence the near-wake structures and vortex shedding patterns in the presence of shear-thinning effects, which is otherwise missing for Newtonian fluid flow at Reynolds number Re = 40 and Richardson number Ri = 1. The distribution of wall-viscosity η along the inner surfaces of the side-by-side square cylinders, at different values of transverse spacings s/d and flow-behavior indices n, hints at large dependency on the inflections in the velocity profile within the gap-flow region. Under thermal buoyancy-driven mild shear-thinning flow conditions (n = 0.6 and 0.8), the gap-flow characteristics have been classified into “pressure-driven” and “momentum-driven” flow regimes, which provides a good explanation for the aberrations noted in the distribution pattern of η. The root-mean-square fluctuations of the velocity-magnitude and vortex shedding phenomenon are found to reciprocate a consistent flow physics associated with a shear-thinning flow at near and far-field downstream. The single body deflected type flow is primarily seen under predominant shear-thinning flow conditions (n = 0.4), compared to chaotic or quasi-periodic flow under mild shear-thinning conditions. Besides, the evolution of non-linear dynamics-based flow regimes (classified with respect to s/d using power spectrum density analysis) at different values of n and s/d is thoroughly summarized. The time-variant fluctuations of lift and drag force parameters are also found to be unified through cause and effects.

Delineation of hydrocarbon and non-hydrocarbon zones using fractal analysis of well-log data from Bhogpara oil field, NE India

Hydrocarbon (HC) and non-hydrocarbon (NHC) zones have been characterized using fractal analysis of wireline log data. Well-log responses such as spontaneous potential (SP), gamma ray (GR), resistivity (LLD, LLS, MSFL), neutron porosity (NPHI), bulk density (RHOB) log have been analyzed from five boreholes of Bhogpara oil field using rescaled range (R/S) and power spectrum density (PSD) techniques. Primarily, both the techniques were applied on the log responses associated with the traditionally identified potential and non-potential zones of 100 m thickness. The Hurst exponent (HPSD) obtained using PSD analysis for GR, NPHI and RHOB log, shows higher values for HC zones as compared to the NHC zones. Furthermore, to understand the scaling pattern more explicitly for main potential sector of the reservoir. Both of the techniques were applied to the wireline log data that are associated with traditionally defined HC and NHC zones of different thickness. The Hurst exponent (HR/S) obtained using R/S analysis was found to be of relatively higher values for HC zones as compared to the NHC zones for all wireline log response. Again opposite trend was also observed for HPSD values that obtained from GR, MSFL, NPHI and RHOB log responses only. Hence, the HC and NHC zones can be delineated from fractal analysis of wireline logs and also overcome the chance of misinterpretation, which is quite possible in the case of hydrocarbon zone detection in traditional reservoir characterization.

Effect of fixed dental prosthesis on the brain functions of partially edentulous patients - pilot study with power spectrum density analysis.

This study was done to analyse the influence of fixed dental prosthesis (FDP) on brain function by analysing power spectral density of partially edentulous patients. The study included unilateral missing mandibular molar replacement patients. The patients were restored with three-unit metal ceramic FDP restorations. The cognitive function was analysed with a mental state questionnaire. Power spectral density (PSD) analysis of EEG alpha waves was made pre- treatment, post treatment and 3 months after FDP treatment to analyse the brain function. The data in various phases were obtained before and after chewing. The results were statistically analysed. The mean pre and post treatment PSD was 0.0175 (SD ±0.0132) and 0.0178 (SD ±0.0135). The mean post treatment PSD after three months was 0.024 (SD± 0.019). The results were analysed with repeated ANOVA and were statistically significant. (p<0.01). The study displayed improvement in brain function of partially edentulous patients with FDP rehabilitation.

High-Mobility CoMP Massive MIMO Uplink Transmissions: Channel PSD Analysis and Doppler Spread Suppression

Coordinated Multi-Point transmission/reception (CoMP) is one of the promising techniques for high-mobility wireless communications systems to increase cell edge user throughput in both uplink and downlink transmission. In this paper, we consider the high-mobility CoMP uplink transmission, where a high-speed terminal (HST) simultaneously transmits signals to multiple base stations (BSs) with angle-domain Doppler shifts compensation. We derive the exact channel power spectrum density (PSD) for uplink CoMP transmissions. The antenna weighting technique is then proposed to suppress the Doppler spread, where an optimization problem is formulated to minimize the maximum Doppler spread among all the BSs. Numerical results are provided to corroborate both the PSD analysis and the superiority of antenna weighting technique.

Channel Projection-Based CCA Target Identification Method for an SSVEP-Based BCI System of Quadrotor Helicopter Control.

The brain-computer interface (BCI) plays an important role in assisting patients with amyotrophic lateral sclerosis (ALS) to enable them to participate in communication and entertainment. In this study, a novel channel projection-based canonical correlation analysis (CP-CCA) target identification method for steady-state visual evoked potential- (SSVEP-) based BCI system was proposed. The single-channel electroencephalography (EEG) signals of multiple trials were recorded when the subject is under the same stimulus frequency. The CCAs between single-channel EEG signals of multiple trials and sine-cosine reference signals were obtained. Then, the optimal reference signal of each channel was utilized to estimate the test EEG signal. To validate the proposed method, we acquired the training dataset with two testing conditions including the optimal time window length and the number of the trial of training data. The offline experiments conducted a comparison of the proposed method with the traditional canonical correlation analysis (CCA) and power spectrum density analysis (PSDA) method using a 5-class SSVEP dataset that was recorded from 10 subjects. Based on the training dataset, the online 3D-helicopter control experiment was carried out. The offline experimental results showed that the proposed method outperformed the CCA and the PSDA methods in terms of classification accuracy and information transfer rate (ITR). Furthermore, the online experiments of 3-DOF helicopter control achieved an average accuracy of 87.94 ± 5.93% with an ITR of 21.07 ± 4.42 bit/min.