Band-pass Filtering Method Research Articles

A deep learning method for contactless emotion recognition from ballistocardiogram

Emotion recognition is a major research point in the field of affective computing. Existing research on the application of physiological signals to emotion recognition mainly focuses on the processing of contact signals. However, there are issues with contact signal acquisition equipment, such as limited portability and poor user compliance, which make it difficult to promote its use. To explore a new method for emotion recognition based on contactless ballistocardiogram (BCG), we proposed a SE-CNN model with a multi-class focal loss function. To construct the dataset, we used audio-visual stimuli to evoke the subjects’ emotions and collected data on the subjects’ three discrete emotions, positive, neutral, and negative, through our established BCG signal acquisition system based on a piezoelectric ceramics sensor. Root mean square filter and thresholding were used to detect and eliminate motion artifacts of BCG signals. We did two kinds of preprocessing on BCG signals: wavelet transform and bandpass filtering, to explore the effect of different components of BCG on emotion recognition. Subsequently, we verified the model’s performance and cross-time working ability through traditional K-Fold and our proposed K-Session cross-validation methods. The results showed that the band-pass filtering method was more beneficial to the current classification task. Under K-Fold cross-validation, the model’s accuracy, precision, and recall were 97.21%, 97.00%, and 97.11%. Under K-Session cross-validation, the model’s accuracy, precision, and recall were 94.66%, 93.92%, and 94.86%, respectively, all of which were better than the classification effect of synchronous ECG. The reliability of BCG in contactless emotion recognition was proved.

A comparative study of bandpass-filter-based multi-scale methods for turbulence energy cascade

Two different bandpass filtering methods have been used in the literature to study turbulence energy cascade simultaneously in physical and scale spaces. One of them is the derivative-based filter by Leung et al. [J Fluid Mech. 2012;V710:453–481] and the other is the difference-based filter by Motoori and Goto [J Fluid Mech. 2021;V911:A27]. The differences in their definitions lead to a variability in the quantitative results across the literature. In this work, we compare the two filtering methods and show that the difference-based filter can be related to the derivative-based filter through Taylor's approximation. Within the truncation error, the deviation between the two filters depends on the ‘filter width’, ‘a’, which is an input to the difference-based filter. The apparent reason for the deviations is that for large ‘a’, the difference-based filter extracts scales in a wider bandwidth compared to the derivative-based filter, which corresponds to the limiting case of the difference-based filter as a → 1 . Thus, one must be careful while choosing a filter based on their objectives, and while comparing results based on different filter designs. It is hoped that the present work will help reconcile the quantitative variations across the relevant literature.

A General and Effective Design Method for Compact Bandpass Filters With Extensible Orders/Channels on a Modified Patch Resonator

A General and Effective Design Method for Compact Bandpass Filters With Extensible Orders/Channels on a Modified Patch Resonator

A novel design method for wideband bandpass filters with fewer inductors

Inductors that are widely used in wideband filter designs could result in large filter size and high insertion loss. A novel design method using admittance matrix based on direct circuit implementation is introduced for wideband bandpass filters. Firstly, a frequency transformation is performed on cross-couplings to realize the conversion between inductor and capacitor, thereby reducing usage of inductors. Moreover, by virtue of an enhanced resonator (type I), an approach of adding extra transmission zero is proposed to improve the out-of-band rejection without any additional usage of inductors. Thirdly, based on the frequency transformation, another enhanced resonator (type II) is introduced to further improve the frequency characteristics without compromising usage of inductors. Finally, by cascading the enhanced resonators of type I and type II, a novel filter can be constructed. This novel filter is designed and fabricated using a glass-based integrated passive device (IPD) technology. The measurement results are highly consistent with the simulation results. It is shown that the proposed design method can reduce the filter size and thus improve the chip integration. It enriches the freedoms during the filter design.

A PRECISE RESPIRATORY AND HEART RATE DETECTION METHOD FOR MILLIMETER-WAVE RADAR

Millimeter wave radar as a type of noncontact sensor can more conveniently and insensibly obtain breathing and heartbeat signals. However, due to the weak radar echo signal and the influence of noise, there may be phase ambiguity and separation distortion of breathing and heartbeat signals during the processing, which affects the accuracy of detection. In this paper, an enhanced extended differential and cross multiplication (EDACM) algorithm is presented to obtain chest position signals without phase ambiguity. A specific order finite impulse response (FIR) filter with a Blackman window is applied to extract breath signals without waveform distortion from phase signals, and the heartbeat signal without rate distortion is extracted from the phase signal by means of the designed Chebyshev II filter. The measured results show that the proposed method achieves 96.78% accuracy for heart rate detection and 94.44% accuracy for respiratory rate detection, and improves the accuracy of heart rate detection by 2.22% and respiratory rate detection by 4.06% compared to the band-pass filter method under the same parameter conditions.

Bandpass filter and frequency-time mapping method for pulse measurement with optical delay.

The pulse signal's transients and low duty cycle characteristics lead to excessive omission and erroneous amplitude measurement in signal capture. We offer a combined microwave photonics frequency-time mapping and optical delay electrical pulse measurement system. Beneficial from the true delay of a long fiber with several paths, the pulse is extended to have a more significant duty cycle so as to boost the capturing possibility. We adopt the bandpass filter to avoid sampling the low-frequency range, prevent phase noise from affecting the signal measurement, and improve the signal-to-noise ratio (SNR). This solves the phase noise issue induced by multiple optical delay paths. The proof-of-concept experiments conduct that a 25 μs pulse with a 50 μs period is stretched to a continuous wave, and the SNR is improved by 7 dB.

Classification of coma/brain-death EEG dataset based on one-dimensional convolutional neural network.

Electroencephalography (EEG) evaluation is an important step in the clinical diagnosis of brain death during the standard clinical procedure. The processing of the brain-death EEG signals acquisition always carried out in the Intensive Care Unit (ICU). The electromagnetic environmental noise and prescribed sedative may erroneously suggest cerebral electrical activity, thus effecting the presentation of EEG signals. In order to accurately and efficiently assist physicians in making correct judgments, this paper presents a band-pass filter and threshold rejection-based EEG signal pre-processing method and an EEG-based coma/brain-death classification system associated with One Dimensional Convolutional Neural Network (1D-CNN) model to classify informative brain activity features from real-world recorded clinical EEG data. The experimental result shows that our method is well performed in classify the coma patients and brain-death patients with the classification accuracy of 99.71%, F1-score of 99.71% and recall score of 99.51%, which means the proposed model is well performed in the coma/brain-death EEG signals classification task. This paper provides a more straightforward and effective method for pre-processing and classifying EEG signals from coma/brain-death patients, and demonstrates the validity and reliability of the method. Considering the specificity of the condition and the complexity of the EEG acquisition environment, it presents an effective method for pre-processing real-time EEG signals in clinical diagnoses and aiding the physicians in their diagnosis, with significant implications for the choice of signal pre-processing methods in the construction of practical brain-death identification systems.

Wideband bandpass filters with suppressed harmonics using vertically installed planar structures

AbstractThis article presents a closed‐form synthesis method for wideband bandpass filters with suppressed harmonics, where stepped‐impedance resonators (SIRs), scaled lines, and vertically installed planar (VIP) structures are introduced to improve the in‐band and out‐of‐band performances. By combining SIRs and scaled lines, the rejection level of the filter is greatly improved and a more compact size is achieved. And the VIP structures help to bring wide passband as well as suppressed harmonics. Then, a 3rd‐order filter is designed to verify the validity of the proposed method and topology. The simulated and measured results demonstrate that the proposed design has a wide passband (FBW = 52.9%), low insertion loss (<0.4 dB), and suppressed harmonics with the level of 20 dB up to 7.1f0.

Deep Learning Methods for Improving Electromagnetic Telemetry Signal-to-Noise Ratio

Summary Electromagnetic (EM) telemetry is a cost-competitive method for communication between downhole tools and oilfield surface equipment. However, EM telemetry use is limited to wellsite deployments that result in favorable signal-to-noise ratio (SNR) levels. Increasingly, the EM attenuation brought by deeper wells, conductive service fluids, and conductive formation layers has made it more important to increase EM telemetry SNR. This study explored the ability of various deep learning (DL) methods to improve EM telemetry SNR with data sets composed of mixed synthetic downhole signals and real field noise. The DL models explored were previously proven to achieve state-of-the-art performance with seismic random noise attenuation and speech separation use cases. Furthermore, architectural adjustments that improved model performance with EM telemetry data were targeted. Then, the SNR improvement performance of different design changes was evaluated. Finally, the study targeted improvements that reduced the requirements for deployment hardware, including number of stakes, without sacrificing SNR improvement performance. Optimized models were found to successfully improve SNR in EM telemetry data, outperforming traditional bandpass filter methods and enabling the demodulation of mixtures that were otherwise too noisy to be demodulated.

An effective procedure for extracting mode shapes of simply-supported bridges using virtual contact-point responses of two-axle vehicles

This paper proposed an effective procedure using virtual contact-point responses to extract mode shapes of a simply-supported bridge. The theoretical closed-form solution of virtual contact-point response using two connected two-axle vehicles is derived based on the vehicle-bridge interaction theory. Variational mode decomposition and band-pass filter (VMD-BPF) method is adopted to decompose the virtual contact-point responses and extract the bridge mode shapes. And a mode shape splicing method is proposed to reduce the influence of vehicle length on the bridge mode shape identification. The accuracy of the identified mode shapes is verified by numerical simulations, indicating that the virtual contact-point responses of the front axle or rear axle in the two-axle vehicle can be used for mode shape extraction. Furthermore, parametric studies such as track irregularity, vehicle speed, and noise are conducted to analyze the parameters that affect the identification accuracy of the mode shapes. The results show that the first four order natural frequencies and corresponding mode shapes of bridges can be well identified by the virtual contact-point responses even when the track irregularity of grade 4 is used. It is also demonstrated that the proposed procedure has a good performance and robustness in extracting the mode frequencies and mode shapes of simply-supported bridges.

Measurement of international crude oil price cyclical fluctuations and correlation with the world economic cyclical changes

The frequent fluctuations in oil price have caused great concern. Scholars have conducted a lot of researches on reasons for oil price fluctuations, but few examined the impact of the world economic cyclical changes on oil price cyclical fluctuations. This study applies wavelet analysis, Hodrik-Prescott Filter, Band-Pass Filter methods to measure oil price cyclical fluctuations, and applies vector autoregressive model to test correlation between economic cyclical changes and oil price cyclical fluctuations from two stages. The results show that the main cycle of oil price fluctuations is 6–7 years and there are two mutation points with an interval of 32 years, which reflects long-wave component of oil price fluctuations. In the first stage, there is a one-way Granger causality between oil price cyclical fluctuations and the world economic cyclical changes. In the second stage, there is a one-way Granger causality between the world economic cyclical changes and oil price cyclical fluctuations. When the world economic growth rate increases by 1%, oil price increases by 5.70%. The world economic cyclical changes contribute more to oil price cyclical fluctuations than OPEC's daily production. This study believes the world economic cyclical changes have a one-way causality to oil price cyclical fluctuations.

Band-pass filtering analysis on low-frequency tonal noise generated from a Krueger storage cavity

With the aim of investigating noise characteristics of tonal noise generated from a Krueger storage cavity, aero-acoustic experiments on a two-dimensional, Krueger flap configuration with an open or closed gap were conducted in the D5 aero-acoustic wind tunnel at Beihang University. The angles of attack are from 4° to 8°, and the free-stream velocities are from 45 m/s to 60 m/s. To study further the noise temporal characteristics and generation mechanism, experimental results were analyzed using a band-pass filtering method. The results show that low-frequency noise generated by the Krueger storage flow is dominant when the Krueger flap is deployed without a gap. For the Krueger configuration with a closed gap, low-frequency multiple tones observed at a free-stream velocity above 45 m/s are generated by self-excited oscillation within the storage cavity. The frequencies corresponding to these tonal noises have an octave relationship and satisfy the Strouhal number related scaling law. Filtering results reveal further that these low-frequency tones are intermittently and alternately excited in time and satisfy the oscillation mode switching mechanism.

FEM simulation-determined band pass filter method with continuously changed bandwidth for fault detection in axial piston pumps

The development of bearing fault detection methods is of great significance for the performance maintenance of axial piston pumps. However, the reciprocating movement induced strong natural periodic impulses that completely submerged the fault characteristic frequencies of the axial piston pump. To solve this problem, a finite element method (FEM)-based band-pass filter method was proposed, combined with minimum entropy deconvolution. However, the performance is determined by the selected band-pass filter bandwidth and the pre-treated denoise techniques. In the present study, an improved version of the FEM-based band-pass filter method was developed by continuously changing the bandwidth of the filter. First, the central frequency was determined using the FEM-based band-pass filter method. Second, the bandwidths of the constructed band-pass filters were continuously changed with a certain incremental step to obtain multiple filtered signals from the raw signals. Third, the normalized Hilbert envelope spectra were collected from the filtered signals. Finally, the projection figure is obtained by automatically taking the spectrum lines with maximum amplitudes in the normalized Hilbert envelope spectra, and the fault features are further determined. The experimental results show that the bearing faults in the axial piston pump can be successfully detected using the proposed method. Compared to the original FEM-based band-pass filter method, the improved version does not require bandwidth selection of the band-pass filter and pre-treated denoising method.

THE STUDY OF THE CROSS-CORRELATION PROPERTIES OF COMPLEX SIGNALS ENSEMBLES OBTAINED BY FILTERED FREQUENCY ELEMENTS PERMUTATIONS

Context. The relevance is to study the cross-correlation properties of the developed complex signals ensembles of large volume with a low level of multiple access interference, thereby increasing the efficiency of using a limited radio frequency range. The Object of Research is a method of bandpass filtering with permutations, which allows forming complex signals ensembles of large volume. Objective. The Objective is to determine the optimal cross-correlation properties for the formation of complex signals ensembles of large volume with a low level of multiple access interference. Method. The work has the study results of cross-correlation properties of complex signals ensembles obtained by applying the filtered elements permutation method. The formation of complex signals ensembles is based on pseudo-random sequences with improved cross-correlation properties in the time domain. Bandpass filtering is applied to such sequences, and the number of filter bands is determined based on the calculation of the frequency spectrum utilization coefficient. The filter band optimal width determination is based on a comparison of the maximum emissions of the side lobes values of the of cross-correlation function of signals from the elements number in the involved sequences. The signals obtained by frequency bands allocating are characterized by a difference in form in the minimal similarity condition. In order to reduce the multiple access interference impact, the frequency components transfer obtained by spectral filtering to the common frequency range is carried out. After that, the signals are transferred using the full search method. As a result, it was obtained all possible combinations of signal pairs permutations. The use of permutations in the complex signals ensemble formation can significantly increase the ensemble volume. The signals generated by frequency filtering, to which the transfer to the common frequency band and their subsequent permutation was applied, are subjected to correlation analysis based on the calculation of the maximum emissions values of the side lobes of the cross-correlation function. Comparative characteristic of cross-correlation properties of developed signals with known signals prove that signals generated based on pseudo-random sequences with improved cross-correlation properties have a much larger ensembles volume, are formed on the basis of simple algorithms that don’t require significant computing resources and have satisfactory cross-correlation characteristics. The use of bandpass filtering method with permutation allows the formation of large-volume ensembles whose signals differ inform, and the combination of different frequency bands reduces the vulnerability to multiple access interference. Results. Due to the software implementation of the bandpass filtering method with permutations, the comparison of crosscorrelation properties of nonlinear sequences, M-sequences, multiphase signals and developed signals based on sequences with improved cross-correlation properties was performed. In estimating the levels of maximum emissions of side lobes of the cross-correlation function, it was found that the generated signals obtained by bandpass filtering with permutations deteriorate cross-correlation characteristics by increasing the pulse duration proportional to the decrease in signal frequency band, but their value satisfies the minimal similarity condition, used in cognitive telecommunications systems. Conclusions. The study of the signals cross-correlation properties proves the effectiveness of the developed bandpass filtering with permutations method. The generated signals have cross-correlated characteristics no worse than ensembles based on known signals. At this level of maximum emissions of the side lobes of the cross-correlation function of the developed signals is 7–12% less than the known signals. Thus, the method of bandpass filtering with permutations can be used to increase the efficiency of radio frequency resource use of both existing and advanced cognitive telecommunication networks of wireless access based on systems with code division multiplexing.

Modal properties identification of damped bridge using improved vehicle scanning method

This paper is concerned with an improved Vehicle Scanning Method (VSM) for modal properties identification of bridges with allowances for damping and road roughness. Owing to the bridge damping, signals are small and degrade over time and may be corrupted by the road roughness. In order to enhance VSM in reading these weak signals, an appropriately tuned elliptic filter is employed instead of the conventional bandpass filter, such as the Butterworth filter. The VSM is improved further by adopting the recently developed Moving Internal Node Element (MINE) method that can furnish more accurate predictions of the higher natural frequencies of the bridge. Illustrative example problems involving undamped and damped bridges with or without road roughness are presented to show the superiority of the improved VSM over conventional VSM that uses a standard bandpass filter and finite element method for analysis. It will be shown herein that the improved VSM can identify the higher mode shapes even with a bridge damping ratio of 3% and standard road roughness, whereas the existing VSM could not do so.

Synthesis of lumped‐element dual‐band bandpass filters with independently controllable bandwidth

In this article, a novel synthesis method for lumped-element dual-band bandpass filters (DBPFs) with independently controllable bandwidth is proposed. The proposed lumped-element DBPF exhibits the advantages including two passbands with independently controllable bandwidth, arbitrary frequency ratio, availability for different lowpass prototypes, and compact size below 6 GHz. This design theory is based on the equivalents of dual-band J-inverters and LC resonators which combines generalized dual-band resonators theory with independently controllable bandwidth. A dual-band bandpass frequency transformation and four circuit conversions are derived. For demonstration, three cases of DBPF with different bandwidths, frequency ratios, and orders are designed, fabricated, and measured. The simulated and measured results have a good agreement, validating the proposed synthesis theory.

Temperature-Compensated High-Sensitivity Relative Humidity Sensor Based on Band-Pass Filtering and Vernier Effect

Temperature-compensated high-sensitivity relative humidity (RH) sensor based on bandpass filtering and Vernier effect is proposed. The sensor with Vernier effect is formed by the cascading single-mode fiber (SMF)-hollow-core fiber (HCF)-SMF structure and coated with sensitive film at the end. While improving the RH sensitivity based on the Vernier effect, the method of bandpass filtering is used to separate the spectrum of the sensing cavity and the envelope to obtain their respective spectrum, and the problem of temperature disturbance is solved by the sensitivity coefficient matrix. Experiments show that the sensitivity of the humidity can reach 1.454 nm/% RH when the humidity rises from 35% RH to 85% RH. The stability and the response time of the sensor are also discussed.

Imaging Complex Subsurface Structures for Geothermal Exploration at Pirouette Mountain and Eleven-Mile Canyon in Nevada

Accurate imaging of subsurface complex structures with faults is crucial for geothermal exploration because faults are generally the primary conduit of hydrothermal flow. It is very challenging to image geothermal exploration areas because of complex geologic structures with various faults and noisy surface seismic data with strong and coherent ground-roll noise. In addition, fracture zones and most geologic formations behave as anisotropic media for seismic-wave propagation. Properly suppressing ground-roll noise and accounting for subsurface anisotropic properties are essential for high-resolution imaging of subsurface structures and faults for geothermal exploration. We develop a novel wavenumber-adaptive bandpass filter to suppress the ground-roll noise without affecting useful seismic signals. This filter adaptively exploits both characteristics of the lower frequency and the smaller velocity of the ground-roll noise than those of the signals. Consequently, this filter can effectively differentiate the ground-roll noise from the signal. We use our novel filter to attenuate the ground-roll noise in seismic data along five survey lines acquired by the U.S. Navy Geothermal Program Office at Pirouette Mountain and Eleven-Mile Canyon in Nevada, United States. We then apply our novel anisotropic least-squares reverse-time migration algorithm to the resulting data for imaging subsurface structures at the Pirouette Mountain and Eleven-Mile Canyon geothermal exploration areas. The migration method employs an efficient implicit wavefield-separation scheme to reduce image artifacts and improve the image quality. Our results demonstrate that our wavenumber-adaptive bandpass filtering method successfully suppresses the strong and coherent ground-roll noise in the land seismic data, and our anisotropic least-squares reverse-time migration produces high-resolution subsurface images of Pirouette Mountain and Eleven-Mile Canyon, facilitating accurate fault interpretation for geothermal exploration.

High selective wideband bandpass filter with mixed-coupled resonators

Novel electric and magnetic mixed-coupled resonators and a general design method for high selective wideband bandpass filters are presented in this paper. Transmission zeros are introduced in the filters for high selectivity, and the location of the transmission zeros can be adjusted without passband characters changing. To verify the design method, an eighth-order mixed-coupled filter is designed, fabricated and measured; the measured results show higher rejection compared with the conventional interdigital filters. Good agreements are obtained between simulated and measured results.

Direct Synthesis Method for Dual-Band Bandpass Filters With Wide Fractional Bandwidth Range and Center Frequency Ratio

This brief proposes a direct synthesis method for dual-band filters based on frequency transformations. This method can synthesize dual-band bandpass filters (BPFs) with a large range of fractional bandwidth (8.5%-56%) and at the same time, wide center frequency ratio (2-4). A novel circuit conversion scheme is proposed to ease the difficulty of implementing complex circuit and reduce the sensitivity of S parameters to the values of the circuit elements significantly (The influence of 20% fluctuation of inductance on S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">11</sub> is within 5dB). In order to prove the validity of the proposed method, a 3 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rd</sup> -order narrowband dual-band BPF with center frequencies of 1 GHz and 2 GHz (small frequency ratio) and a 5 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> -order wideband dual-band BPF with center frequencies of 0.5 GHz and 2 GHz (large frequency ratio) are designed and fabricated, the simulated and measured results have good agreement.