Band-pass Filtering Method Research Articles

A signal quality analysis method for electrocardiosignals in the CS domain

Compressed sensing (CS) is an important cutting-edge low-power technology for wearable health monitoring systems. To solve the problem of how the quality of compressive sampled electrocardiosignal (ECG) affects the subsequent arrhythmia recognition and signal reconstruction, a novel ECG quality evaluation method in the CS domain is proposed. In order to achieve the evaluation effect in the CS domain, a modified bandpass filter method is designed to obtain the approximate frequency band energy and approximate wavelet entropy, which are used as the evaluation index for the support vector machine classifier to realize the CS ECG signal quality evaluation. Based on the simulation results from the MIT-BIH ECG database, this method can reach an accuracy of more than 92% under different compression ratios (2, 4, 8 and 16). Simulation experiments based on data from the PhysioNet/CinC Challenge 2011 database show that the accuracy of this method can reach above 83% under different compression ratios. In evaluation experiments using actual ECG signals, we show that this method can achieve good accuracy when the compression ratio is less than eight. The accuracy of this method needs to be further improved when the compression ratio is 16. When the compression ratio is less than 8 and a sparse matrix is not used as the measurement matrix, the method proposed in this paper can directly evaluate the quality of ECG signals after compression sampling without reconstruction. Compared with the signal quality evaluation algorithm in the uncompressed domain, the experimental results of the proposed method are highly competitive and, under a certain compression ratio, the amount of transmitted data can be reduced while maintaning accuracy. Meanwhile, the proposed method also provides a new idea for signal quality evaluation in the compressed domain.

Time-Frequency Bandpass Filter with Nonstationary Signal Decomposition Application

In various applications such as speech processing, underwater sound, radar application and mechanical fault diagnosis, there are large number of nonstationary signals. In order to achieve nonstationary signal decomposition, the instantaneous frequency ridge is extracted through interactive mode, and a time-frequency bandpass filter (TFBPF) method is proposed. This method is the modified version of Intrinsic Chirp Component Decomposition (ICCD) and has the physical essence of time-frequency domain bandpass filter. The superiority and application potential of TFBPF in complex engineering signal decomposition are demonstrated through two numerical examples. In the first one, we prove that TFBPF can decompose the weak signal component directly through analyzing the vibration signal of hydraulic turbine; While in the second one, we prove that TFBPF can effectively overcome the drawbacks of ICCD through analyzing the vibration signal during the speed-up process of a complex equipment. TFBPF is still very effective even for complex signal decomposition in a strong noise environment.

Recurrent Quantification Analysis-Based Emotion Classification in Stroke Using Electroencephalogram Signals

Stroke is a cerebrovascular disorder, and one of the most common effects of stroke is emotional disturbances. This present work classifies six emotions (anger, sadness, happiness, fear, disgust, and surprise) of two types of stroke (left brain damage and right brain-damage) using electroencephalogram (EEG) signals. EEG signals are collected from 19 each subject of LBD, RBD, and normal control (NC) at a sampling rate of 128 Hz. The IIR Bandpass filter and amplitude thresholding methods are used to reduce noise and artifacts' effects, respectively. Discrete Wavelet Packet Transform is used to extract five EEG frequency bands (alpha, beta, gamma, alpha to gamma, and beta to gamma). A set of nonlinear features are extracted from five different EEG frequency ranges using recurrent quantification analysis. Finally, the extracted features are mapped to six corresponding emotions using three nonlinear classifiers (K nearest neighbor, probabilistic neural network, and random forest). The experimental results indicate that LBD subjects have severe emotional impairment than RBD. The mean of diagonal line length ( ), recurrence rate, and maximum mean diagonal length (Lmax) feature give maximum classification rate of 85.24% NC, 79.54%, and 79.09% using RF classifier compared to other features. The alpha to gamma (13–49 Hz) band helps identify Stroke emotional state changes compared to other frequency bands.

Dual-Parameter Optical Fiber Probe Based on a Three-Beam Fabry-Perot Interferometer

Dual parameter detection without cross-sensitivity is a commonly important need but challenging, as most fiber detection components have a single sensitive mechanism. In this article, an optical fiber probe based on a three-beam Fabry-Perot interferometer (FPI) for temperature and refractive index (RI) measurement was proposed and experimentally realized. Theoretically, such structure has three reflective surfaces, forming three FPIs, and can obtain a hybrid sensing mechanism: wavelength-sensitive to temperature and intensity-sensitive to RI. Experimentally, the chemical etching method was used to form a concave in the fiber tip. Fused together with another section of un-etched fiber, an air bubble can be formed inside the fiber. Then, a cleavage near the bubble can shape the three-beam FPI. Using the fast Fourier Transform, the first-order spatial frequency is corresponding to the air-FPI, and the ratio of the second-order spatial frequency to first-order spatial frequency can describe how many smaller interference periods have been created within one original period due to the cleavage. The test temperature range is 30-40°C with a step of 2°C. The band pass filtering method was used to analyze different frequency components. Experimental results validate that the silica-FP was dominate for temperature sensing, and the average temperature sensitivity was 8.97 pm/°C with repeated linearity over 0.95. The test RI range was 1.3333-1.3908, and average RI sensitivity was 10.05 dB/RIU with repeated linearity over 0.92. Therefore, the proposed structure is a compact and efficient sensing component with hybrid sensitive mechanism that can achieve a temperature-RI dual-parameter measurement.

Disturbance observer-based torsional vibration damper for variable-speed wind turbines

This paper presents a robust torsional vibration damper for variable-speed wind turbines based on the disturbance observer method. The damper is designed by explicitly taking into account the pole placement of the closed-loop system in the presence of model uncertainties. Unlike the conventional band-pass filter method, it is analyzed that the proposed method not only has good performance on noise attenuation, but also can maintain the characteristics of the drivetrain system in low-frequency region. The performance of other generator speed-based controllers, such as the blade pitch controller, can therefore be preserved without the retuning procedures. An experimental system having high consistency with a 2 MW wind turbine is developed and the real-time hardware-in-the-loop experiments are carried out to demonstrate the effectiveness of the damper.

Direct Synthesis and Design of Dispersive Waveguide Bandpass Filters

In this article, a direct synthesis and dimensional design method for narrowband waveguide bandpass filters with a general dispersive coupling element is proposed. Comparing with the dispersion-less filter synthesis approaches, the general dispersive coupling matrix (DCM) that incorporates unique dispersive characteristics of a physical realization is introduced to provide an accurate description of the filter to be designed. Moreover, the DCM can describe not only strong dispersive coupling elements for realizing transmission zeros (TZs), but also dispersive resonators. A DCM consists of a frequency-invariant part and a dispersive part. For a given dispersive part, by iteratively remedying the characteristic polynomials, the frequency-invariant part for an equal-ripple response can be directly obtained. Consequently, according to the synthesized frequency-invariant coupling matrix, the filter dimensions can be designed only by electromagnetic (EM) simulation of each individual coupling element at the center frequency. Two design examples are presented, including a four-pole filter with two TZs and an eight-pole filter with four TZs. The examples are validated either by hardware prototyping or by EM simulation, demonstrating the effectiveness, accuracy, and generality of the proposed synthesis and design framework.

Shannon Energy Application for Detection of ECG R-peak using Bandpass Filter and Stockwell Transform Methods

Shannon energy-based algorithm has been implemented in peak detection method of various physiological signals including electrocardiogram, which is used to enhance significant peaks fo ...

Tunable Coaxial Cavity Resonator-Based Filters Using Actuated Liquid Metal Posts

This letter presents a new tuning method for coaxial cavity resonator-based bandpass filters (BPFs). The proposed tuning mechanism lays its foundations on pneumatically-actuated Galinstan that functionalizes the inner conductor of a capacitively-loaded coaxial cavity resonator. By altering the volume of Galinstan (i.e., height of inner conductor), ultrawide (>octave) and low loss RF tuning can be obtained without the need for small capacitive gaps that typically limit the RF performance of coaxial BPFs. To validate the concept, a coaxial cavity resonator with frequency tuning between 2.9 and 9.9 GHz (3.4:1 tuning range), and unloaded quality factor between 120 and 625 was manufactured and measured. Furthermore, the RF performance of a two-pole BPF with: 1) tunable frequency between 3.4 and 7.5 GHz (2.2:1); 2) an intrinsically switched-off state; 3) insertion loss <1 dB; and 4) return loss <10.5 dB was experimentally validated.

An Effective Approach to Suppressing the Spurious Mode in Rectangular Waveguide Filters

In this letter, a new method for rectangular waveguides bandpass filters with improved stopband performance is presented. By setting the position of the coupling window, the coupling of the high-order mode can be attenuated, which makes it difficult to form parasitic passbands. It can significantly improve the stopband rejection of the filter without introducing additional elements. Furthermore, the whole structure can be fabricated using the conventional computer numerical control (CNC) milling technology. A Ka -band waveguide filter is designed and tested. The stopband rejection of the design is increased from 1.4 times to 1.94 times the center frequency of the filter with the insertion loss of 0.5 dB. Finally, the measurement results validated the proposed design.

MJO Anomalies relationship with Volcanic Eruption in Indonesian Archipelago

Madden-Julian Oscillation (MJO) is a large-scale atmospheric phenomenon that crosses the equator with a propagation area ranging from 15° North to 15° South, and moves from west to east, precisely from the Indian Ocean to the Pacific. MJO propagation is usually characterized by the rising of Sea Surface Temperature (SST) in Indian Ocean respectively. MJO anomaly is closely related to the variability of weather in the area it passes, including the Indonesian Archipelago. The impact of MJO anomaly in Indonesian Archipelago itself is suspected to cause not only excessive rainfall, but also a very long consecutive No Rain Days (NRD), with in the end can also trigger massive crop failures. In addition to SST, there are also external events that can affect the duration of the MJO, i.e. volcanic eruptions. Therefore, the study aims to determine the effect of volcanic eruption events on MJO anomalies, through the SST variable as an MJO anomaly parameter and also the occurrence of volcanic eruptions in the same time span. Data from both variables were taken over a period of 35 years, from 1982 to 2016. The SST data is a daily average data, obtained from ESRL NOAA, which is then filtered by the Bandpass Filter method to reinforce the oscillation of data. The MJO anomaly that seen from the SST fluctuations is then matched with time data and the duration of volcanic eruption events over the same time span. It found out that there are three MJO anomalies occurred during the time span of 35 years, and it is hypothesized that they were clearly in correspondence between the duration of volcanic eruption events with the incidence of MJO anomalies in Indonesian Archipellago.

Contributing Factors to Spatiotemporal Variations of Outgoing Longwave Radiation (OLR) in the Tropics

Abstract Factors governing spatiotemporal variations of the daily outgoing longwave radiation (OLR) are studied using 35-yr (1979–2013) data records by employing multiple linear regression, wavelet transforms, and bandpass filtering methods. From the regression coefficients of nine predictors and the explained variances, we found that the largest contributions to OLR variability are associated with the Madden–Julian oscillation and El Niño–Southern Oscillation (ENSO). The ENSO signatures on OLR show dipole patterns over the Maritime Continent (MC) and Pacific regions with an extension to the Atlantic. Subsequently, the third significant contribution of the Indian Ocean dipole is confined to the Indian Ocean and Africa. Then, the solar cycle and stratospheric aerosols show mainly negative correlations, while a positive linear trend is observed mainly in the Northern Hemisphere. Lastly, factors associated with the stratospheric quasi-biennial oscillation (QBO) are the least significant contributor to OLR. In terms of oscillatory signals, time–longitude variations of the annual cycle (AC) show pairs of contrasting phases that characterize monsoon systems, in which the MC and Pacific regions are found to be in the same phase group. The most consistent AC signals are found to correspond with North and South American monsoons that respectively exhibit weakening and strengthening trends. Wavelet spectra and filtered OLR signals in intraseasonal oscillation, QBO, and ENSO frequency bands show an interdependent relationship that largely varies with time scale and longitudes.

Synthesis and Design of Lumped-Element Filters in GaAs Technology Based on Frequency- Dependent Coupling Matrices

A novel synthesis method for lumped-element bandpass filters is proposed on the basis of frequency-dependent coupling matrices, which can preserve the moderate bandwidth response matching with coupling matrix prototype better. The available element values of resonators and inverters with the acceptable quality factor are determined by adjusting normalized slope parameters or reference susceptance parameters. To validate the design approach, two third-order inline filters with the fractional bandwidth of 20% at a center frequency of 3 GHz are designed and fabricated in the GaAs HBT technology. Good agreement is obtained between the simulated and measured results. The measured shape factors K20dB of the two filters with and without external couplings are 1.8 and 1.85, respectively. The filter followed by a one-stage amplifier also demonstrates the high frequency selectivity.

Design of Bandpass and Bandstop Infinite Impulse Response Filters Using Fractional Derivative

In this paper, a new design method for digital bandpass and bandstop infinite impulse response filters with nearly linear-phase response is proposed. In this method, the phase response of an all-pass filter is optimized in the frequency domain to yield less passband error ${\text{Er}}_{p}$ and stopband error ${\text{Er}}_{s}$ with optimal stopband attenuation $A_{s}$ . To achieve high accuracy in passband and stopband regions, fractional derivative (FD) constraints are evaluated in the respective regions, and the filter coefficients are computed using the Lagrange multiplier method. The behavior of fidelity parameters measured in terms of ${\text{Er}}_{p}{,\text{Er}}_{s}$ , and phase error ${\text{Er}}_{{\text{ph}}}$ is multimodel w.r.t. FD values. Therefore, modern heuristic technique, known as cuckoo search optimization is used for determining the optimal value of FDs and reference frequency simultaneously to minimize the fitness function, which is constructed as a sum of the squared error in passband and stopband. The designed filter yields up to 60% reduction in ${\text{Er}}_{p}$ and ${\text{Er}}_{{\text{ph}}}$ in the case of bandpass filter. Meanwhile, the response of filter is not degraded due to the finite word length effect.

The New Zealand financial cycle 1968–2017

ABSTRACTThis paper identifies a financial cycle for New Zealand over the period 1968–2017 using spectral analysis and band-pass filter methods. We report the main characteristics of the financial cycle and examine the extent to which it is synchronised with the business cycle in New Zealand and the financial cycle in the United States. Our results suggest that the median length of the financial cycle in New Zealand is 8 years, and its duration has increased substantially (from 4.75 to 9.75 years) following the economic reforms of the mid-eighties. There appears to be a strong relationship between financial cycle contractions and real economic outcomes, with 83% of financial cycle contractions preceding a recession by a median of 2.5 years. We also find a strong degree of synchronicity between the New Zealand and US financial cycles.

Design Method for Multiband Filters With Compact Configuration in Substrate Integrated Waveguide

In this paper, a design method for multiband bandpass filters with compact configuration in substrate integrated waveguide is proposed by combining the single-band/dual-band synthesis method and the multimode resonator theory. The designed filters could generate multiple filtering passbands without expanding their entire physical size. In addition, all the passbands could be efficiently synthesized and designed with any prescribed order in theory, which has been rarely reported in multiband filters, especially in the design of quad-band filters. As examples, one third-order quad-band filter and one third-order tri-band filter are designed, fabricated, and measured. Good agreement is attained between their simulated and measured S-parameters, and both the two sets of results have verified the feasibility of the proposed design method and attractive performances of the designed multiband filters.

Improved Algebraic-Loop Relaxation in CPVBR Models of Synchronous Machines Under Power Electronic Switching

Constant parameter voltage-behind-reactance models of salient pole synchronous machines have been recently proposed for efficient interfacing in state-variable-based simulation programs. Therein, a constant and decoupled RL interfacing circuit is achieved using a low-pass filter (LPF) approximation that relaxes an algebraic-loop making the model explicit. However, in machine-converter systems, the ac currents and voltages contain harmonics due to switching, which necessitates the use of stiff poles in the LPF resulting in slow simulations. This letter proposes using a band-pass filter (BPF) that may be tuned depending on the switching harmonics of interest. The proposed hybrid LPF–BPF method allows the use of nonstiff poles and reduces the computational burden without compromising numerical accuracy as opposed to the conventional method.

Motion artefact minimization from photoplethysmography based non-invasive hemoglobin sensor based on an envelope filtering algorithm

An envelope-filtered method of enhancement of non-invasive Hemoglobin (Hb) monitoring is described. Results using a four-wavelength two-wavelength Photoplethysmography (PPG) probe gathered from five randomly selected healthy subjects demonstrate that the measurement of Hb coefficient, based on the novel envelope method filtered PPG, has a superior performance on minimization of the motion artefact than that from band-pass filtered PPG data in both stationary and non-stationary scenarios. Hemodynamic pressure variation near the sensor probe is also induced from a vertical height difference (VHD) between the finger sensor probe and the heart level. Results of this study show that the Hb coefficients determined using the proposed filtering method based on the envelope algorithm are also capable of minimization of VHD variations similar to the traditional band-pass filter method.

Generating ActiGraph Counts from Raw Acceleration Recorded by an Alternative Monitor.

This study aimed to implement an aggregation method in Matlab for generating ActiGraph counts from raw acceleration recorded with an alternative accelerometer device and to investigate the validity of the method. The aggregation method, including the frequency band-pass filter, was implemented and optimized based on standardized sinusoidal acceleration signals generated in Matlab and processed in the ActiLife software. Evaluating the validity of the aggregation method was approached using a mechanical setup and with a 24-h free-living recording using a convenient sample of nine subjects. Counts generated with the aggregation method applied to Axivity AX3 raw acceleration data were compared with counts generated with ActiLife from ActiGraph GT3X+ data. An optimal band-pass filter was fitted resulting in a root-mean-square error of 25.7 counts per 10 s and mean absolute error of 15.0 counts per second across the full frequency range. The mechanical evaluation of the proposed aggregation method resulted in an absolute mean ± SD difference of -0.11 ± 0.97 counts per 10 s across all rotational frequencies compared with the original ActiGraph method. Applying the aggregation method to the 24-h free-living recordings resulted in an epoch level bias ranging from -16.2 to 0.9 counts per 10 s, a relative difference in the averaged physical activity (counts per minute) ranging from -0.5% to 4.7% with a group mean ± SD of 2.2% ± 1.7%, and a Cohen's kappa of 0.945, indicating almost a perfect agreement in the intensity classification. The proposed band-pass filter and aggregation method is highly valid for generating ActiGraph counts from raw acceleration data recorded with alternative devices. It would facilitate comparability between studies using different devices collecting raw acceleration data.

Improvement of Back-EMF Self-Sensing For Induction Machines When Using Deadbeat-Direct Torque and Flux Control

Back-electromotive force (back-EMF) self-sensing is commonly used in induction machine (IM) drive systems for its maintenance cost and safety considerations. In recent years, compared with standard indirect field oriented control, deadbeat-direct torque and flux control (DB-DTFC) has been shown to be a highly effective method for IM control with a fixed switching frequency. It has advantages such as fast torque dynamics with one step dynamic response for torque and flux with no current regulator. This paper evaluates the synergy between back-EMF self-sensing technology and DB-DTFC for IM drive systems. In this paper, an observer-based closed-loop back-EMF tracking self-sensing control in an IM DB-DTFC drive system is presented. It includes a back-EMF state filter, back-EMF tracking observer, and cascaded motion observer. Back-EMF harmonic decoupling is explored to improve the low-speed performance. The band-pass filter method (BPF) for back-EMF self-sensing is also presented. Finally, the closed loop system dynamic stiffness at very low speeds, with and without the BPF method, is experimentally evaluated.

Random noise de-noising and direct wave eliminating based on SVD method for ground penetrating radar signals

In this paper, we present a method using singular value decomposition (SVD) which aims at eliminating the random noise and direct wave from ground penetrating radar (GPR) signals. To demonstrate the validity and high efficiency of the SVD method in eliminating random noise, we compare the SVD de-noising method with wavelet threshold de-noising method and bandpass filtering method on both noisy synthetic data and field data. After that, we compare the SVD method with the mean trace deleting in eliminating direct wave on synthetic data and field data. We set general and quantitative criteria on choosing singular values to carry out the random noise de-noising and direct wave eliminating process. We find that by choosing appropriate singular values, SVD method can eliminate the random noise and direct wave in the GPR data validly and efficiently to improve the signal-to-noise ratio (SNR) of the GPR profiles and make effective reflection signals clearer.