Search Results (1,232)

In this study, a novel synthesis method for bandpass filters is proposed. The method relies on Richard’s transform and avoids approximations in circuit realizations. Thus, proper frequency responses are obtained for bandpass filters with bandwidths ranging from narrow to wide. In the presented approach, a method for removing the input and output inverters/transformers is proposed and is used to show how classic parallel-coupled resonator filters can be designed using the proposed method. Also, a degree of freedom is introduced that allows the overall impedance level of the fabricated filter to be tuned, which is used to tune the frequency response of the filter to the theoretical one. Both narrow-band and wideband solutions in terms of impedance inverter realization are discussed in the paper. The theoretical investigations are confirmed by an experimental realization of two bandpass filters with parallel-coupled shorted resonators. Full article

Kinesthetic motor imagery (KMI), the mental rehearsal of a motor task without its actual performance, constitutes one of the most common techniques used for brain–computer interface (BCI) control for movement-related tasks. The effect of neural injury on motor cortical activity during execution and imagery remains under investigation in terms of activations, processing of motor onset, and BCI control. The current work aims to conduct a post hoc investigation of the event-related potential (ERP)-based processing of KMI during BCI control of anthropomorphic robotic arms by spinal cord injury (SCI) patients and healthy control participants in a completed clinical trial. For this purpose, we analyzed 14-channel electroencephalography (EEG) data from 10 patients with cervical SCI and 8 healthy individuals, recorded through Emotiv EPOC BCI, as the participants attempted to move anthropomorphic robotic arms using KMI. EEG data were pre-processed by band-pass filtering (8–30 Hz) and independent component analysis (ICA). ERPs were calculated at the sensor space, and analysis of variance (ANOVA) was used to determine potential differences between groups. Our results showed no statistically significant differences between SCI patients and healthy control groups regarding mean amplitude and latency (p < 0.05) across the recorded channels at various time points during stimulus presentation. Notably, no significant differences were observed in ERP components, except for the P200 component at the T8 channel. These findings suggest that brain circuits associated with motor planning and sensorimotor processes are not disrupted due to anatomical damage following SCI. The temporal dynamics of motor-related areas—particularly in channels like F3, FC5, and F7—indicate that essential motor imagery (MI) circuits remain functional. Limitations include the relatively small sample size that may hamper the generalization of our findings, the sensor-space analysis that restricts anatomical specificity and neurophysiological interpretations, and the use of a low-density EEG headset, lacking coverage over key motor regions. Non-invasive EEG-based BCI systems for motor rehabilitation in SCI patients could effectively leverage intact neural circuits to promote neuroplasticity and facilitate motor recovery. Future work should include validation against larger, longitudinal, high-density, source-space EEG datasets. Full article

Model-based sensorless control of interior permanent-magnet synchronous motors (IPMSMs) typically employs an estimation observer with embedded position information, followed by a position extraction process. Although a type-2 phase-locked loop (PLL) is widely adopted for position and speed extraction, it suffers from steady-state tracking errors under variable-speed operation, leading to torque bias in IPMSM torque control. To mitigate this issue, this paper first proposes an adaptive bandpass full-order observer in the stationary reference frame. Subsequently, a Kalman filter (KF)-based compensation strategy is introduced for the PLL to eliminate tracking errors while maintaining system stability. Experimental validation on a 300 kW platform confirms the effectiveness of the proposed sensorless torque control algorithm, demonstrating significant reductions in position error and torque fluctuations during acceleration and deceleration. Full article

In this paper, we study the classification problem of short-time-window steady-state visual evoked potentials (SSVEPs) and propose a novel deep convolutional network named EEGResNet based on the idea of residual connection to further improve the classification performance. Since the frequency-domain features extracted from short-time-window signals are difficult to distinguish, the EEGResNet starts from the filter bank (FB)-based feature extraction module in the time domain. The FB designed in this paper is composed of four sixth-order Butterworth filters with different bandpass ranges, and the four bandwidths are 19–50 Hz, 14–38 Hz, 9–26 Hz, and 3–14 Hz, respectively. Then, the extracted four feature tensors with the same shape are directly aggregated together. Furthermore, the aggregated features are further learned by a six-layer convolutional neural network with residual connections. Finally, the network output is generated through an adaptive fully connected layer. To prove the effectiveness and superiority of our designed EEGResNet, necessary experiments and comparisons are conducted over two large public datasets. To further verify the application potential of the trained network, a virtual simulation of brain computer interface (BCI) based quadrotor control is presented through V-REP. Full article

Electrohydrodynamic (EHD) printing offers mask-free, high-resolution deposition across a broad range of ink viscosities, yet combining void-free filling of high-aspect-ratio through-glass vias (TGVs) with ultrafine drop-on-demand (DOD) line printing on the same platform requires balancing conflicting requirements: for example, high field strengths to drive ink into deep and narrow vias; sufficiently high ink viscosity to prevent gravity-induced leakage; and stable meniscus dynamics to avoid satellite droplets and charge accumulation on the glass surface. By coupling electrostatic field analysis with transient level-set simulations, we establish a dimensionless regime map that delineates stable cone-jetting regime; these predictions are validated by high-speed imaging and surface profilometry. Operating within this window, the platform achieves complete, void-free filling of 200 µm × 1.52 mm TGVs and continuous 10 µm-wide traces in a single print pass. Demonstrating its capabilities, we fabricate transparent Ku-band substrate-integrated waveguide antennas on borosilicate glass: the printed vias and arc feed elements exhibit a reflection coefficient minimum of −18 dB at 14.2 GHz, a −10 dB bandwidth of 12.8–16.2 GHz, and an 8 dBi peak gain with 37° beam tilt, closely matching full-wave predictions. This physics-driven, all-in-one EHD approach provides a scalable route to high-performance, glass-integrated RF devices and transparent electronics. Full article

This study comprehensively compares the performance of two non-destructive testing (NDT) techniques—active thermography (AT) and digital shearography (DS)—for identifying various damage types in composite structures. Three distinct composite specimens were inspected: a carbon-fiber-reinforced polymer (CFRP) plate with flat-bottom holes, an aluminum honeycomb core sandwich plate with a circular skin-core disbond, and a CFRP plate with two low-energy impacts damage. The research highlights the significant role of post-processing methods in enhancing damage detectability. For AT, algorithms such as fast Fourier transform (FFT) for temperature phase extraction and principal component thermography (PCT) for identifying significant temperature components were employed, generally making anomalies brighter and easier to locate and size. For DS, a novel band-pass filtering approach applied to phase maps, followed by summing the filtered maps, remarkably improved the visualization and precision of damage-induced anomalies by suppressing background noise. Qualitative image-based comparisons revealed that DS consistently demonstrated superior performance. The sum of DS filtered phase maps provided more detailed and precise information regarding damage location and size compared to both pulsed thermography (PT) and lock-in thermography (LT) temperature phase and amplitude. Notably, DS effectively identified shallow flat-bottom holes and subtle imperfections that AT struggled to clearly resolve, and it provided a more comprehensive representation of the impacts damage location and extent. This enhanced capability of DS is attributed to the novel phase map filtering approach, which significantly improves damage identification compared to the thermogram post-processing methods used for AT. Full article

This article investigates how to exploit the high-frequency mmWave for 5G-advanced and beyond, which requires new filters for the wide bandpass and its multi-sub-band. Based on the substrate-integrated waveguide (SIW), spoof surface plasmon polariton (SSPP), and metastructures, like complementary split-ring resonators (CSRRs), the development of a wide bandpass filter and a multi-sub-band filter is proposed, along with an experimental realization to verify the model. The upper and lower cutoff frequencies of the wide bandpass are controlled through an SIW-SSPP structure, whereas the corresponding wide bandpass and its multi-sub-band filters are designed through incorporating new metastructures. The frequency range of 24.25–29.5 GHz, which covers the n257, n258, and n261 bands for 5G applications, was selected for verification. The basic SIW-SSPP wide bandpass structure of 24.25–29.5 GHz was designed first. Then, by incorporating an Archimedean spiral configuration, the insertion loss within the passband was reduced from 1 dB to 0.5 dB, while the insertion loss in the high-frequency stopband was enhanced from 40 dB to 70 dB. Finally, CSRRs were integrated to effectively suppress undesired frequency components within the bandpass, thereby achieving multi-sub-band filters with low insertion losses with a triple-sub-band filter of 0.5 dB, 0.7 dB, and 0.8 dB in turn. The experimental results showed strong agreement with the design scheme, thereby confirming the rationality of the design. Full article

An external power build-up cavity of a line-narrowed 407-nm laser diode for Raman gas analysis was demonstrated to possess good gas detection capabilities. By employing an ordinary laser diode without anti-reflection coating or and a bandpass interference filter in an external cavity resonance, the laser linewidth was narrowed by resonant optical feedback, and tens of watts of external cavity power were built up. The coupling mechanism between the semiconductor laser and the external cavity are discussed, as well as the noise background in the experimental results. The Raman spectrum of ambient air was analyzed, achieving a methane detection limit of 1 ppm. Full article

Effective fault feature extraction and classification methods serve as the foundation for achieving the efficient fault diagnosis of planetary gearboxes. Considering the vibration signals of planetary gearboxes that contain both symmetrical and asymmetrical components, this paper proposes a novel feature extraction method integrating an adaptive multi-bandpass filter (AMBPF) and refined composite multi-scale fuzzy entropy (RCMFE). And a dream optimization algorithm (DOA)–least squares support vector machine (LSSVM) is also proposed for fault classification. Firstly, the AMBPF is proposed, which can effectively and adaptively separate the meshing frequencies, harmonic frequencies, and their sideband frequency information of the planetary gearbox, and is combined with RCMFE for fault feature extraction. Secondly, the DOA is employed to optimize the parameters of the LSSVM, aiming to enhance its classification efficiency. Finally, the fault diagnosis of the planetary gearbox is achieved by the AMBPF, RCMFE, and DOA-LSSVM. The experimental results demonstrate that the proposed method achieves significantly higher diagnostic efficiency and exhibits superior noise immunity in planetary gearbox fault diagnosis. Full article

Computational imaging spectrometers using broad-bandpass filter arrays with distinct transmission functions are promising implementations of miniaturization. The number of filters is limited by the practical factors. Compressed sensing is used to model the system as linear underdetermined equations for hyperspectral imaging. This paper proposes the following method: parallel dictionary reconstruction and fusion for spectral recovery in computational imaging spectrometers. Orthogonal systems are the dictionary candidates for reconstruction. According to observation of ground objects, the dictionaries are selected from the candidates using the criterion of incoherence. Parallel computations are performed with the selected dictionaries, and spectral recovery is achieved by fusion of the computational results. The method is verified by simulating visible-NIR spectral recovery of typical ground objects. The proposed method has a mean square recovery error of ≤1.73 × 10⁻⁴ and recovery accuracy of ≥0.98 and is both more universal and more stable than those of traditional sparse representation methods. Full article

Background: Biomechanical and neuromuscular differences between falls and recoveries have been well-studied; however, the cortical correlations remain unclear. Using mobile brain imaging via electroencephalography (EEG), we examined differences in sensorimotor beta frequencies between falls and recoveries during an unpredicted slip in walking. Methods: We recruited 22 young adults (15 female; 18–35 years) who experienced a slip (65 cm) during walking. Raw EEG signals were band-pass filtered, and independent component analysis was performed to remove non-neural sources, eventually three participants were excluded due to excessive artifacts. Peak beta power was extracted from three time-bins: 400 milliseconds pre-, 0–150 milliseconds post and 150–300 milliseconds post-perturbation from the midline (Cz) electrode. A 2 × 3 Analysis of Covariance assessed the interaction between time-bins and group on beta power, followed by Independent and Paired t-tests for between and within-group post hoc comparisons. Results: All participants (n = 19) experienced a balance loss, seven experienced a fall. There was a time × group interaction on beta power (p < 0.05). With no group differences pre-perturbation, participants who experienced a fall exhibited higher beta power during 0–150 milliseconds post-perturbation than those who recovered (p < 0.001). However, there were no group differences in beta power during 150–300 milliseconds post-perturbation. Conclusions: Young adults exhibiting a greater increase in beta power during the early post-perturbation period experienced a fall, suggesting a higher cortical error detection due to a larger mismatch in the expected and ongoing postural state and greater cortical dependence for sensorimotor processing. Our study results provide an overview of the possible cortical governance to modulate slip-fall/recovery outcomes. Full article

This paper presents a symmetry-driven broadband circularly polarized magnetoelectric dipole antenna with bandpass filtering response, where the principle of symmetry is strategically employed to enhance both radiation and filtering performance. The antenna’s circular polarization is achieved through a symmetrical arrangement of two orthogonally placed metallic ME dipoles combined with a phase delay line, creating balanced current distributions for optimal CP characteristics. The design further incorporates symmetrical parasitic elements—a pair of identical inverted L-shaped metallic structures placed perpendicular to the ground plane at −45° relative to the ME dipoles—which introduce an additional CP resonance through their mirror-symmetric configuration, thereby significantly broadening the axial ratio bandwidth. The filtering functionality is realized through a combination of symmetrical modifications: grid slots etched in the metallic ground plane and an open-circuited stub loaded on the microstrip feed line work in tandem to create two radiation nulls in the upper stopband, while the inherent symmetrical properties of the ME dipoles naturally produce a radiation null in the lower stopband. This comprehensive symmetry-based approach results in a well-balanced bandpass filtering response across a wide operating bandwidth. Experimental validation through prototype measurement confirms the effectiveness of the symmetric design with compact dimensions of 0.96${\lambda }_0$ × 0.55${\lambda }_0$ × 0.17${\lambda }_0$ (${\lambda }_0$ is the wavelength at the lowest operating frequency), demonstrating an impedance bandwidth of 66.4% (2.87–5.05 GHz), an AR bandwidth of 31.9% (3.32–4.58 GHz), an average passband gain of 5.5 dBi, and out-of-band suppression levels of 11.5 dB and 26.8 dB at the lower and upper stopbands, respectively, along with good filtering performance characterized by a gain-suppression index (GSI) of 0.93 and radiation skirt index (RSI) of 0.58. The proposed antenna is suitable for satellite communication terminals requiring wide AR bandwidth and strong interference rejection in L/S-bands. Full article

To obtain a flat top shaped passband in a conventional thin-film-based optical bandpass filter (OBF), it needs a large number of constitutional layers of thin films, which makes the film deposition systems more complicated and accumulates errors in film growth. A flat top and polarization-independent optical bandpass filter structure is proposed based on experimentally verified polarization independency in the form of a prism-pair coupled planar optical waveguide (POW). The POW is composed of two waveguide stacks, which consists of nine planar thin-film layers. Theoretical simulations show that the flat band top spans about 5 nm with transmittance over 97.8%. The passband is designed to be centered at 632.8 nm, the He-Ne laser wavelength, and the FWHM (full width at half maximum) bandwidth is about 35 nm. Within 0.5° tuning for the incident angle of the light, the passband could be shifted within 50 nm, while its transmittance fluctuates only less than 1% and the passband shape distorts only slightly. This type of OBF is potentially applicable in various fields of optical and laser spectroscopies. Full article

Quadcolor cameras with conventional RGB channels were studied. The fourth channel was designed to improve the estimation of the spectral reflectance and chromaticity from the camera signals. The RGB channels of the quadcolor cameras considered were assumed to be the same as those of the Nikon D5100 camera. The fourth channel was assumed to be a silicon sensor with an optical filter (band-pass filter or notch filter). The optical filter was optimized to minimize a cost function consisting of the spectral reflectance error and the weighted chromaticity error, where the weighting factor controls the contribution of the chromaticity error. The study found that using a notch filter is more effective than a band-pass filter in reducing both the mean reflectance error and the chromaticity error. The reason is that the notch filter (1) improves the fit of the quadcolor camera sensitivities to the color matching functions and (2) provides sensitivity in the wavelength region where the sensitivities of RGB channels are small. Munsell color chips under illuminant D65 were used as samples. Compared with the case without the filter, the mean spectral reflectance rms error and the mean color difference (ΔE₀₀) using the quadcolor camera with the optimized notch filter reduced from 0.00928 and 0.3062 to 0.0078 and 0.2085, respectively; compared with the case of using the D5100 camera, these two mean metrics reduced by 56.3%. Full article

As a core component of machining tools and vehicles, the load-bearing and transmission performance of rolling bearings is directly related to product processing quality and driving safety, highlighting the critical importance of fault detection. To address the nonlinearity, non-stationary modulation, and low signal-to-noise ratio (SNR) observed in bearing vibration signals, we propose a fault feature extraction method based on spectral kurtosis and Hilbert envelope demodulation. First, spectral kurtosis is employed to determine the center frequency and bandwidth of the signal adaptively, and a bandpass filter is constructed to enhance the characteristic frequency components. Subsequently, the envelope spectrum is extracted through the Hilbert transform, allowing for the precise identification of fault characteristic frequencies. In the fault diagnosis stage, a multidimensional feature vector is formed by combining the kurtosis index with the amplitude ratios of inner/outer race characteristic frequencies, and fault pattern classification is accomplished using a Least-Squares Support Vector Machine (LS-SVM). To evaluate the effectiveness of the proposed method, experiments were conducted on the bearing datasets from Case Western Reserve University (CWRU) and the Machine Failure Prevention Technology (MFPT) Society. The experimental results demonstrate that the proposed method surpasses other comparative approaches, achieving identification accuracies of 95% and 100% for the CWRU and MFPT datasets, respectively. Full article