Power Spectral Method Research Articles

A rapid coarse-grained blind wideband spectrum sensing method for cognitive radio networks

Spectrum sensing aims to sense the potential spectrum resources available in the cognitive radio environment. It is also the premise of spectrum management and spectrum sharing in cognitive radio systems. To perceive the primary user’s activity and make full use of spectrum holes, rapid detection of a broad frequency span is an essential part of cognitive radio technology. Reducing the observation time for the data collection, the data storage requirements, and hardware/software computational complexity are urgent and challenging issues in wideband spectrum sensing. High accuracy power spectral density estimation is not the primary requirement; of course, the accuracy must be controlled within the appropriate range and can support the primary user activity’s determination. This paper proposes a sub-Nyquist wideband spectrum sensing method based on compressive covariance sensing for the rapid wideband spectrum sensing. Compared with the traditional Nyquist-rate method, this method can use low-speed ADC to detect wideband signals and effectively control the observation time and computational complexity. This paper’s main contributions include: (1) developing a sub-Nyquist sampling structure based on the multi-coset sampling banks, (2) proposing a coarse-grained power spectral density estimation method for wideband spectrum sensing with short observation time and low complexity. Simulations show that the proposed method exhibits this method is suitable for fast spectral detection. At the same time, the error of spectrum analysis is basically within the acceptable range.

Design of solar power system for the new mini region of broadband seismometer shelter in Tiganderket, Karo, North Sumatera, Indonesia

The solar power installation on a new broadband seismometer shelter will greatly be affected by the quality of waveform data. The lower power means a physically smaller footprint and a less costly installation for a new station which must be located far from the main power system. In this case, we have installed the solar power system in the new broadband seismometer shelter in the mini region at TKSM station, in Tiganderket, Karo, North Sumatera Indonesia. The main goal of this study, to design, testing the solar cell, and compute the power spectral after installation of the power cell in the new shelter, which located away from roads and cities and human activity. The results presented that the good performance of the solar power system (solar cell, solar charge controller, and battery) for continuous transmission and to collect the waveform data based on the performance TKSM station using power spectral density function methods.

Attenuation Coefficient Parameter Computations for Tissue Composition Assessment of Carotid Atherosclerotic Plaque in Vivo

Quantitative ultrasound has been used to assess carotid plaque tissue composition. Here, we compute the attenuation coefficient (AC) in vivo with the optimum power spectral shift estimator (OPSSE) and reference phantom method (RPM), extract AC parameters and form parametric maps. Differences between OPSSE and RPM AC parameters are computed. Relationships between AC parameters, surgical scores and histopathology assessments are examined. Kendall's τ correlations between OPSSE AC and surgical scores are significant, including those between cholesterol and Standard Deviation (adjusted p = 0.038); thrombus and Minimum (adjusted p = 0.002), Maximum (adjusted p = 0.021) and Standard Deviation (adjusted p = 0.001); ulceration and Average (adjusted p = 0.033), Median (unadjusted p = 0.013), Maximum (unadjusted p = 0.039) and Mode (adjusted p = 0.009). The strongest correlations with histopathology are percentage cholesterol and Median OPSSE (unadjusted p = 0.007); percentage hemorrhage and Minimum OPSSE (adjusted p < 0.001); hemosiderin score and Median OPSSE (adjusted p = 0.010); and percentage calcium and Percentage Non-physical RPM Pixels (unadjusted p = 0.014). Kruskal–Wallis H and Dunn's post hoc tests have the ability to distinguish between groups (p < 0.05). Results suggest AC parameters may assist in vivo evaluation of carotid plaque vulnerability.

Coloured Noise from Stochastic Inflows in Reaction\u2013Diffusion Systems

In this paper, we present a framework for investigating coloured noise in reaction–diffusion systems. We start by considering a deterministic reaction–diffusion equation and show how external forcing can cause temporally correlated or coloured noise. Here, the main source of external noise is considered to be fluctuations in the parameter values representing the inflow of particles to the system. First, we determine which reaction systems, driven by extrinsic noise, can admit only one steady state, so that effects, such as stochastic switching, are precluded from our analysis. To analyse the steady-state behaviour of reaction systems, even if the parameter values are changing, necessitates a parameter-free approach, which has been central to algebraic analysis in chemical reaction network theory. To identify suitable models, we use tools from real algebraic geometry that link the network structure to its dynamical properties. We then make a connection to internal noise models and show how power spectral methods can be used to predict stochastically driven patterns in systems with coloured noise. In simple cases, we show that the power spectrum of the coloured noise process and the power spectrum of the reaction–diffusion system modelled with white noise multiply to give the power spectrum of the coloured noise reaction–diffusion system.

Design and Characterization of an Actuated Drill Mockup for Orthopedic Surgical Training.

Haptic feedback in virtual reality-based trainers for surgical bone drilling is mostly provided via impedance-controlled haptic devices. Due to this, the displayable maximum stiffness is limited. In addition, vibration feedback is often only of reduced fidelity. To overcome these shortcomings, we have developed a hand-held, actuated admittance-controlled drill mockup, comprising enhanced kinesthetic and tactile feedback. This article reports on design and characterization of the device, and highlights its use for training. Kinesthetic feedback is provided through haptic augmentation, employing a ball-screw mechanism acting on a retractable drill-bit. Feedback computation relies on admittance control, thus allowing for stable display of very high resistance forces, and thus material stiffness, which cannot be achieved with standard impedance-control approaches. For the tactile mechanism, a modified linear vibration actuator is directly attached to the mockup handle, improving signal transmission. Tactile feedback computation is based on an extension of a previously proposed power spectral density control method. Frequency-specific gains are adjusted in real-time, compensating for differences between desired and measured vibrations. The performance of the device is characterized in several experiments, including comparisons to drilling with a real drill into artificial bone samples. In addition, several user studies have been carried out. We illustrate the capability of the mockup to render bone samples with different material layer stiffness and thickness. Moreover, we show that the mockup system allows for the same training effect as when rehearsing with a real drill.

Propagation characteristics of vortex beams in anisotropic atmospheric turbulence

The phase distortion of vortex beams caused by atmospheric turbulence is calculated by the power spectral inversion method. An analytical expression of the fundamental mode Gaussian vortex beam that propagates through anisotropic atmospheric turbulence has been deduced. The influences of altitude, anisotropic factor, and topological charge (TC) on the propagation characteristics of vortex beams are discussed in detail. The results show that when the altitude is in the region of 3–6 km, the change of altitude has little influence on the quality of vortex beams. When the altitude is in the region of 6–7.8 km, beam quality will become better along with the increase in altitude. Otherwise, beam quality will be better with the increase in anisotropic factor, and the ability to resist distortion will be stronger with the increase in TC.

A Power Spectral Density-Based Method to Detect Tremor and Tremor Intermittency in Movement Disorders.

There is no objective gold standard to detect tremors. This concerns not only the choice of the algorithm and sensors, but methods are often designed to detect tremors in one specific group of patients during the performance of a specific task. Therefore, the aim of this study is twofold. First, an objective quantitative method to detect tremor windows (TWs) in accelerometer and electromyography recordings is introduced. Second, the tremor stability index (TSI) is determined to indicate the advantage of detecting TWs prior to analysis. Ten Parkinson’s disease (PD) patients, ten essential tremor (ET) patients, and ten healthy controls (HC) performed a resting, postural and movement task. Data was split into 3-s windows, and the power spectral density was calculated for each window. The relative power around the peak frequency with respect to the power in the tremor band was used to classify the windows as either tremor or non-tremor. The method yielded a specificity of 96.45%, sensitivity of 84.84%, and accuracy of 90.80% of tremor detection. During tremors, significant differences were found between groups in all three parameters. The results suggest that the introduced method could be used to determine under which conditions and to which extent undiagnosed patients exhibit tremors.

Theoretical investigations on flow-induced vibration of fuel rods with spacer grids in axial flow

Fuel rods, one of the most important components in the nuclear reactor core, are usually supported by spacer grids along the axial direction. Since those fuel rods are long and slender, flow-induced vibration (FIV) will be induced and cause abrasion of the cladding in the axial flow of high-velocity coolant. A theoretical study applying modal analysis method and power spectral analysis method is carried out to analyze the vibration characteristics and FIV root-mean-square (RMS) response of fuel rods. In this study, a fuel rod with spacer grids is modeled as one dimensional multi-span beam and the fluid force along the fuel rod is considered as random impulsive load. The influences of span length, the axial flow velocity and the correlation length coefficient of axial flow on FIV response displacement of fuel rods are studied. The sensitivity analysis results reveal that the FIV of fuel rods has strong negative correlation with span length, while it is positive by related to the axial flow velocity and correlation length coefficient.

Prognosis of Sleep Bruxism Using Power Spectral Density Approach Applied on EEG Signal of Both EMG1-EMG2 and ECG1-ECG2 Channels

Bruxism is a sleep syndrome, in which individual involuntarily grinding and clenching the teeth. If sleep does not complete properly, then it generates many disorders such as bruxism, insomnia, sleep apnea, narcolepsy, rapid eye movement behavioral disorder, and nocturnal frontal lobe epilepsy. The aim of this paper is to draw the results in the form of signal spectrum analysis of the changes in the domain of different stages of sleep. The present research completed in three stages such as the collection of the data, analysis of the electroencephalogram (EEG) signal, and comparative analysis between bruxism patients and normal subjects. Importantly, the channels EMG1-EMG2 and ECG1-ECG2 of the EEG signal were combined for the prognosis of bruxism by using power spectral density, which mainly focused on two sleep stages such as wake (W) and rapid eye movement (REM). The total number of one-minute EEG recordings from bruxism patients and normal subjects analyzed in this work were 149 and 95, respectively. The obtained results show that the average normalized values of the power spectral density of the EMG1-EMG2 and ECG1-ECG2 channels during REM and W sleep stages are several folds higher in case of the bruxism than those in the normal. Moreover, the proposed power spectral density-based method by using the decision tree classifier shows a higher accuracy for the prognosis of sleep bruxism in comparison with previous works. In addition, the proposed approach in the prognosis of the bruxism is noise free and accurate as it is in mathematical form and has taken very less time as compared with the traditional systems. The present research work would provide a fast and effective prognosis system of the human bruxism with high accuracy for medical applications.

Partitioning of Terrain Features Based on Roughness

Surface roughness is a key parameter that reflects topographic characteristics and influences surface processes, and characterization of surface roughness is a fundamental problem in geoscience. In recent years, although there have been basic studies on roughness, few studies have compared the concept and quantification of roughness, and there have been few studies that have evaluated the ability of partition terrain features. Based on 1″ resolution Shuttle Radar Topography Mission (SRTM) data and previous studies, we selected the Qinba Mountain region of China and its adjacent areas as our study area, and used 13 different roughness algorithms to extract roughness in this study. Using spatial patterns and statistical distributions, the results were analyzed, and the best algorithm suited to partitioning terrain features was selected. We then evaluated the ability of the algorithm to distinguish the terrain morphology. The results showed the following: (1) The 13 algorithms were able to be classified into four types, that is, gradient (SLOPE), relief (root mean squared height, RMSH), local vector (directional cosine eigenvalue, DCE) and power-spectral (two-dimensional continuous wavelet transform, 2D CWT). (2) The SLOPE and RMSH algorithms were better able to express and distinguish terrain, as they were able to macroscopically distinguish between four types of terrain in the study areas. Based on power-spectral methods, 2D CWT had the same discrimination ability as the first two methods following a normalization transform, whereas the DCE method had a general effect and could only distinguish two types of terrain. (3) Different roughness algorithms had their own applicability for different terrain areas and application directions.

The complexity-entropy causality plane based on multiscale power spectrum entropy of financial time series.

The complexity of financial time series is an important issue for nonlinear dynamic systems. We propose multiscale power spectral entropy. Based on this method, this paper uses the complex entropy causal plane ( ) to evaluate the complexity of the stock market. Multiscale power spectral entropy takes full advantage of the interrelationships between data in state space and estimates system complexity from different temporal resolutions. Then, we use a complex causal entropy plane to track changes in stock signals. The simulation data are used to test the performance of this method. Finally, we compare the method with the traditional power spectral entropy method. The results show that the method is more sensitive to changes in the stock market and can fully extract the intrinsic dynamics of the stock sequence.

Jeavons Syndrome, Eyelid Myoclonus with Absences (EMA) with Epileptic Status and Hypoactive Delirium

Abstract The evaluation of electroencephalogram (EEG) and the clinical picture of eyelid myoclonus (EM) with absences (EMA) using classical EEG signal evaluation and power spectral analysis currently presents a major challenge to predict further improvement, unsteady status, neurological defect outcomes in patients, or lethal termination in septic encephalopathy and acid-base imbalance due to kidney failure. At the Clinic of Anaesthesiology and Intensive Medicine (CAIM) of University Hospital in Martin (UHM) we clinically examined a patient N.J., a 58-year-old male with EMA. We used the Neuron-Spectrum-AM specialized software to measure the EEG signal visually and by means of power spectral analysis methods to quantitatively analyse the EEG record. The power spectral colour maps confirmed a disturbance of consciousness, approximating the depth of unconsciousness, affirmatively with a clinical disorder in absences, hypoactive delirium, and showed extinction of functional brain foci with the possibility of topical interpretation, and established an EEG correlate of impaired cognition, attention and lucidity of consciousness that were assessed by the clinical findings of the attending physician. The EMA syndrome was a final agonal condition with hypoactive delirium and was considered to be idiopathic epilepsy linked to severe metabolic-septic encephalopathy as an epileptic syndrome.

Wide frequency band electrochemical noise measurement and analysis of a Li/SOCl2 primary battery

Electrochemical noise of a primary LiSOCl2 battery was measured in a wide frequency band during discharge at a constant value resistor. Power spectral density calculation method was used as the first stage of data analysis. Measurements with two analog to digital converter speed rates made it possible to carry out precision analysis in more than five order wide frequency bands starting from 2.5 kHz down to 17 mHz. It was shown that each power spectral density spectrum consists of two regions. Each of them possesses linear frequency dependence with its own slope. They intercept in the frequency band from 10 Hz down to 0.1 Hz depending on the state of charge value. Dispersion and high-order moments such as kurtosis and skewness calculation methods were applied to analyze electrochemical noise data as alternate analysis techniques. It was found that dispersion calculation can give useful information about electrochemical noise evolution during discharge process for the investigated battery type.

Power spectral density-based nearinfrared sub-band detection for noninvasive blood glucose prediction in both in-vitro and in-vivo studies

Diabetes is a widespread and serious disease and noninvasive measurement has been in high demand. To address this problem, a power spectral density-based method was offered for determining glucose sensitive sub-bands in the nearinfrared (NIR) spectrum. The experiments were conducted using phantoms of different optical properties in-vitro conditions. The optical bands 1200–1300[Formula: see text]nm and 2100–2200[Formula: see text]nm were found feasible for measuring blood glucose. After that, a photoplethysmography (PPG)-based low cost and portable optical system was designed. It has six different NIR wavelength LEDs for illumination and an InGaAs photodiode for detection. Optical density values were calculated through the system and used as independent variables for multiple linear regression analysis. The results of blood glucose levels for 24 known healthy subjects showed that the optical system prediction was nearly 80% in the A zone and 20% in the B zone according to the Clarke Error Grid analysis. It was shown that a promising easy-use, continuous, and compact optical system had been designed.

Qualitative appraisal of high resolution satellite derived free air gravity anomalies over the Maldive Ridge and adjoining ocean basins, western Indian Ocean

High resolution satellite derived Free Air Gravity (FAG) anomalies over the Maldive Ridge segment of the Chagos-Laccadive Ridge and adjoining areas of the Arabian Basin and Central Indian Basin was analyzed to understand their structure. Indian Ocean Geoidal Low corrected FAG depict the N-S trending relative highs associated with the Maldive Ridge, the lows associated with the Vishnu Fracture Zone, and the seafloor fabrics associated with spreading Central Indian Ridge in the Arabian Basin. Transformation operations for enhancing the short, intermediate and long wavelength anomalies were carried out. The northward continuation of the Vishnu Fracture Zone, the eastward extension of the fracture zones of the Arabian Basin into the Deep Sea Channel (DSC) region, between the Maldive Ridge and the Chagos Bank, and the signatures related to north-south trending coral reefs have been deciphered from the enhancement of short wavelength anomalies. The long wavelength anomalies show N-S highs along the axis of the Maldive Ridge and the DSC, which on comparison with previous studies, is inferred to be the signature related with the underplated material from the passage of the Indian plate over the Reunion Plume. Depth to top of two interfaces over the Maldive Ridge and the DSC were computed using the power spectral method by assuming a window of 110 km dimension and 50 km overlap. Depths were thus calculated for 44 blocks along the ridge axis. The average depth to the top of the shallow interface was found to be 5.5 km while that of the deeper was 11.0 km. These depths and interfaces were confirmed by undertaking 2D forward modelling along a 300 km long N-S profile along the western segment of the Maldive Ridge. Integrating with the available previous geophysical studies, it is inferred that the shallow interface represents the depth to the top of the acoustic basement underlying 1–1.5 km thick lava flow unit while the deeper is associated with the interface between the crust and initial Moho before the underplating took place (presently top of the underplated material). From the present study, it has been inferred that the Deep Sea Channel between the Maldive Ridge and Chagos Bank can be purely oceanic in nature.

Electrochemical noise measurement of a Li/SOCl2 primary battery

Electrochemical noise of a Li/SOCl2 primary battery was measured during discharge at a constant value resistor. The amplitude of the noise was found to be razing during discharge process. Power spectral density calculation method was used to analyze electrochemical noise. It was found that the slope of power spectral density frequency dependences increases with the battery discharging. The electrochemical impedance of the battery was measured during galvanostatic discharge and investigated using equivalent circuit analysis method. The correlations and some interactions between impedance components and electrochemical noise characteristics during battery discharge process were found and analyzed.

Deep convolutional networks with residual learning for accurate spectral-spatial denoising

Abstract Although hyperspectral image (HSI) denoising has been studied for decades, preserving spectral data efficiently remains an open problem. In this paper, we present a powerful and trainable spectral difference mapping method based on convolutional networks with residual learning in an end-to-end fashion for preserving spectral profile while removing noise in HSIs. Our approach, called SSDRN (spectral-spatial denoising by residual network), blends a spectral difference mapping strategy with a denoised key band for an efficient complete set of HSI denoising. The key band is selected based on a principal component transformation matrix. Experiments have been conducted on both ground based HSIs and airborne data. Comparative analyses validate that the proposed method presents superior denoising performance as it preserves spectral information better, and requires less computational time.

Performance of Blind Cooperative Spectrum Sensing under Nonuniform Signal and Noise Powers

This paper addresses the performance, the reporting channel traffic and the computational complexity of two blind centralized cooperative spectrum sensing schemes under the effect of unequal noise and received signal powers. The first one is the generalized likelihood ratio test with decision fusion, and with weighted and non-weighted data fusion of samples and eigenvalues. The second scheme is the circular folding cooperative power spectral density split cancellation method with data fusion. A total of eight techniques arose from variations of these two in terms of the different fusion and combining rules. It is demonstrated that different configurations of the system parameters may influence the above three metrics in different extents, meaning that none of the techniques is capable of overcoming the others in all metrics simultaneously. This indicates that the choice of the most suitable technique must be carefully made to match the specific scenario to which the technique is intended to be applied. The results presented in this paper serve as guidelines for assisting this choice.

Linear stability analysis of laminar flow near a stagnation point in the slip flow regime

The aim of the present contribution is to analyze the effect of slip parameter on the stability of a laminar incompressible flow near a stagnation point in the slip flow regime. The analysis is based on the traditional normal mode approach and assumes parallel flow approximation. The Orr-Sommerfeld equation that governs the infinitesimal disturbance of stream function imposed to the steady main flow, which is an exact solution of the Navier-Stokes equation satisfying slip boundary conditions, is obtained by using the powerful spectral Chebyshev collocation method. The results of the effect of slip parameter K on the hydrodynamic characteristics of the base flow, namely the velocity profile, the shear stress profile, the boundary layer, displacement and momentum thicknesses are illustrated and discussed. The numerical data for these characteristics, as well as those of the eigenvalues and the corresponding wave numbers recover the results of the special case of no-slip boundary conditions. They are found to be in good agreement with previous numerical calculations. The effects of slip parameter on the neutral curves of stability, for two-dimensional disturbances in the Reynolds-wave number plane, are then obtained for the first time in the slip flow regime for stagnation point flow. Furthermore, the evolution of the critical Reynolds number against the slip parameter is established. The results show that the critical Reynolds number for instability is significantly increased with the slip parameter and the flow turn out to be more stable when the effect of rarefaction becomes important.

Novel approaches to estimating the turbulent kinetic energy dissipation rate from low- and moderate-resolution velocity fluctuation time series

Abstract. In this paper we propose two approaches to estimating the turbulent kinetic energy (TKE) dissipation rate, based on the zero-crossing method by Sreenivasan et al. (1983). The original formulation requires a fine resolution of the measured signal, down to the smallest dissipative scales. However, due to finite sampling frequency, as well as measurement errors, velocity time series obtained from airborne experiments are characterized by the presence of effective spectral cutoffs. In contrast to the original formulation the new approaches are suitable for use with signals originating from airborne experiments. The suitability of the new approaches is tested using measurement data obtained during the Physics of Stratocumulus Top (POST) airborne research campaign as well as synthetic turbulence data. They appear useful and complementary to existing methods. We show the number-of-crossings-based approaches respond differently to errors due to finite sampling and finite averaging than the classical power spectral method. Hence, their application for the case of short signals and small sampling frequencies is particularly interesting, as it can increase the robustness of turbulent kinetic energy dissipation rate retrieval.