Rejection Filter Research Articles

Solid State Vanadate Laser and 213 nm Rayleigh Rejection Filter Enable Miniaturized Deep Ultraviolet Raman Spectrometers.

A combination of a highly efficient 213 nm Rayleigh rejection filter (RRF) and a miniaturized 213 nm neodymium-doped vanadate laser enables portable deep ultraviolet (UV) Raman spectrometers. We demonstrate the high efficiency of 213 nm RRF manufactured by Green Optics Co., Ltd by utilizing our compact 213 nm vanadate laser to measure high signal-to-noise ratio UV Raman spectra of Teflon and UV resonance Raman (UVRR) spectra of solid ammonium nitrate. We also demonstrate UVRR detection of trace amounts of ammonia formed during ammonium nitrate UV photolysis. We roughly estimate the ammonia UVRR detection limit of ∼10 ng under our experimental conditions.

Design and performance analysis of a novel miniaturized band-stop filter for band rejection in Sub-6 GHz 5G spectrum

This paper introduces an innovative band stop filter specifically designed to reject a sub-6GHz band within the 5 G spectrum. Fabricated on an FR4 substrate with a relative permittivity of 4.4, the filter incorporates a defected ground structure (DGS) and features very compact dimensions of 19 mm × 11 mm × 0.8 mm. The filter design is performed using the High Frequency Structure Simulator (HFSS). Besides, the filter’s equivalent circuit is modeled using the ANSYS circuit editor. A parametric study has been conducted to identify the optimal parameters for the filter’s form and size. The proposed filter exhibits a rejected band of 1.42 GHz, spanning from 2.3 GHz to 3.72 GHz, with a center frequency of 3.18 GHz. Within the rejected band, the S21 value is less than −21.36, and the stop band fractional bandwidth (FBW) is 44.65%. Additionally, the filter demonstrates a negative group delay (NGD) characteristic in the frequency range of 2.97 GHz to 3.35 GHz, with a measured NGD time of −0.42 ns, and a quality factor equal to 2.24. These results underscore the filter’s suitability for applications utilizing frequencies below 2 GHz and above 3 GHz, ensuring efficient functionality.

Analysis, design, and optimization based on genetic algorithms of a highly efficient dual-band rectenna system for radiofrequency energy-harvesting applications

This paper gives an enhanced Rectenna design that operates at dual-band [2.45 and 5.8] GHz in the ISM (Industrial, Scientific, and Medical) band and is printed on an FR4-Epoxy substrate. This Rectenna design includes two proposed sub-designs for the receiving antenna and rectifier circuit based on the microstrip technology. The first sub-design concerns the microstrip patch antenna (MPA) described by its radiating element as a pentagonal, its ground being affected by a defective ground structure technique, and its polarization manner as circular polarization. This MPA design is analyzed, designed, optimized using genetic algorithms (GAs), simulated under CST MWS (i.e., computer simulation technology microwave studio), and confirmed by another software named HFSS (high-frequency structure simulator). The second sub-design concerns the microstrip rectifier circuit (MRC) that contains an input matching network based on a coupled-line impedance transformer strategy to achieve good adaptation between MPA and MRC, voltage doubler converter using an SMS7630 Schottky diode thanks to its high sensitivity, microstrip interdigital capacitor to mitigate the intrinsic losses due to the lumped elements, harmonic rejection filter based on a stepped-impedance low-pass filter to reject the unwanted harmonics generated by the non-linear behavior of SMS7630, and the resistive load that models the consumption of the system to be fed. This MRC is analyzed, designed, optimized using GAs, and simulated under ADS (Advanced Design System). The effectiveness of the proposed MPA is proven in terms of gain equals 3.06 dBi and 4.683 dBi at 2.45 GHz and 5.8 GHz respectively, and efficiency equals 95.13 % and 96.552 % at 2.45 GHz and 5.8 GHz respectively. The proposed MRC is effective in terms of efficiency at a lower input power value of about 97.18 % and 67.93 % at 2.45 GHz and 5.8 GHz respectively.

Polystyrene nanofibers containing ZIF-8 and ZnO nanoparticles as an effective fibrous respiratory mask filter for rejection of air pollutions

Polystyrene nanofibers containing ZIF-8 and ZnO nanoparticles as an effective fibrous respiratory mask filter for rejection of air pollutions

Combining optimal SASS (Sparsity Assisted Signal Smoothing) and notch filters for transient measurement signals denoising of large power generating unit

Denoising and harmonic interference removal from the measurement signal is crucial for accurate parameters calculation of a generating unit model. Determining the actual parameters values requires various unit transient signals data recorded during a well-defined testing procedure. However, the recorded signals usually contain noise and harmonic interferences which are difficult to remove due to a presence of different kinds of discontinuities.The paper presents a proposal of optimal denoising and harmonic interference removal method from transient measurement signals of 200 MW power generating unit. The method combines notch filters for harmonic rejection followed by SASS (Sparsity Assisted Signal Smoothing) algorithm for wideband noise rejection. Parameters of the notch filters as well as the SASS are determined using popular optimization algorithms (simulated annealing, Nelder-Mead simplex and gradient algorithm).Performance of the proposed method is compared to its direct Linear Time-Invariant (LTI) competitors such as low-pass and notch filters alone, notch and low-pass filters combined and to the optimal SASS method alone. The performance evaluation is based on a set of specially generated test signals which are using the developed mathematical model of the signals (to set the level of noise and interferences) as well as the mathematical model of the power generating unit (to provide the reference clean signals). The obtained results confirm that the optimal notch-SASS method might be a valuable noise removal tool for considered class of signals and leads to superior results than the LTI filters or the SASS method alone.

A 46% PAE, 2.4-GHz Two-Stage Class E Power Amplifier Utilizing CMOS 0.13-µm Technology

A wireless device with a long battery life and great sensitivity becomes difficult to develop since there is a huge demand for low-power, low-cost wireless gadgets. The power amplifier (PA) is the most crucial part of radio frequency (RF) transceivers because of its massive power consumption. Consequently, in order to minimize power loss, a very effective and low-power consumption PA is needed. In this paper, high efficiency two-stage CMOS PA designed in 0.13-μm process for 2.4 GHz IoT transmitter applications is presented. The driver stage and power stage are the two stages that make up the two-stage topology of the proposed CMOS PA. To attain high efficiency and great power gain, a class E PA is used at the power stage. The LC matching network at the output is used for harmonic rejection filter at 2.4 GHz with an additional parallel capacitor helps for better harmonic rejection. In addition, a layout has been successfully designed and optimized. All the components in the proposed PA are designed on-chip. The pre-layout and post-layout simulations have been conducted to verify the proposed PA's performance. The pre-layout simulation of the proposed PA can deliver 19.19 dBm output power and 45.2% PAE at 2.0 V power supply into a 50-Ω load. On the other hand, the proposed PA produced an output power of 17.33 dBm and 46% PAE, according to the results of the post-layout simulation with a similar power supply of 2.0 V. The chip area for the proposed layout design is 1.05 mm2.

Dual-polarization pump rejection filter in silicon nitride technology.

On-chip pump rejection filters are key building blocks in a variety of applications exploiting nonlinear phenomena, including Raman spectroscopy and photon-pair generation. Ultrahigh rejection has been achieved in the silicon technology by non-coherent cascading of modal-engineered Bragg filters. However, this concept cannot be directly applied to silicon nitride waveguides as the comparatively lower index contrast hampers the suppression of residual light propagating in the orthogonal polarization, limiting the achievable rejection. Here, we propose and demonstrate a novel, to the best of our knowledge, strategy to overcome this limitation based on non-coherent cascading of the modal- and polarization-engineered Bragg filters. Based on this concept, we experimentally demonstrate a rejection exceeding 60 dB for both polarizations, with a bandwidth of 4.4 nm. This is the largest rejection reported for silicon nitride Bragg gratings supporting both polarizations.

Nonlinear Kalman filter for gyroscopic and accelerometer noise rejection of an unmanned aerial vehicle control strategy

This study addresses timing issues inherent in traditional proportional-integral-derivative (PID) controllers for drone angle control and introduces an innovative solution, the adaptive PID flight controller, aimed at optimizing PID gains for improved performance in terms of speed, accuracy, and stability. To enhance the controller's robustness against noise and accurately estimate the system's state, a Kalman filter is incorporated. This filtering mechanism is designed to reject noise and provide precise state estimation, thereby contributing to the overall effectiveness of the adaptive PID flight controller in managing altitude dynamics for unmanned aerial vehicles (UAVs). The comparative methodology evaluates three configurations: a single PID controller for all three angles, two PID controllers dedicated to pitch/roll and yaw angles separately, and three PID sub-controllers for each angle (pitch, roll, and yaw). The study seeks to identify the most effective PID configuration in terms of stability, responsiveness, and accuracy while highlighting the added benefits of noise rejection and state estimation through the Kalman filter. This integrated approach showcases innovation and effectiveness, introducing a comprehensive solution not explored in previous research.

Full C- and L-band covered second-order OAM mode generator based on a thinned helical long-period fiber grating

A full C- and L-band covered second-order orbital-angular-momentum (OAM) mode generator has been proposed and experimentally demonstrated, which is realized by using a helical long-period fiber grating (HLPG) but inscribed in a thinned four-mode fiber. By optimizing the design of grating period and fiber diameter of the proposed HLPG, an ultra-broadband rejection filter with a depth of ∼23 dB, a bandwidth of ∼156 nm @-10 dB (ranging from 1522 nm to 1678 nm) and a bandwidth of ∼58 nm @-20 dB (ranging from 1574 nm to 1632 nm), has been successfully obtained as a typical sample. To the best of our knowledge, this is the first demonstration of such ultra-broadband second-order OAM mode generator by using only one fiber component, i.e., the thinned HLPG. In addition, the proposed generator is less polarization-dependent and less temperature-sensitive than those of the conventional HLPGs, which is believed to be considerably helpful to find potential applications of the device itself in wavelength division multiplexing (WDM) and OAM mode division multiplexing (MDM) optical fiber communication systems.

On-chip ultra-high rejection and narrow bandwidth filter based on coherency-broken cascaded cladding-modulated gratings

Bragg filters are of essential importance for chip-scale photonic systems. However, the implementation of filters with sub-nanometer bandwidth and rejection beyond 70 dB is hindered by the high index contrast of the silicon-on-insulator platform, which makes filters prone to fabrication imperfections. In this paper, we propose to combine coherency-broken cascading architecture and cladding modulation to circumvent the intrinsic limitation. The cascading architecture effectively prevents the accumulation of phase errors, while the cladding modulation offers additional design freedom to reduce the coupling coefficient. A bimodal Bragg filter with a testing-equipment-limited rejection level of 74 dB and a 40 dB bandwidth of 0.44 nm is experimentally demonstrated. The minimum feature size is 90 nm, which significantly relieves the fabrication constraints.

Fast Coincidence Filter for Silicon Photomultiplier Dark Count Rate Rejection.

Silicon Photomultipliers find applications across various fields. One potential Silicon Photomultiplier application domain is neutrino telescopes, where they may enhance the angular resolution. However, the elevated dark count rate associated with Silicon Photomultipliers represents a significant challenge to their widespread utilization. To address this issue, it is proposed to use Silicon Photomultipliers and Photomultiplier Tubes together. The Photomultiplier Tube signals serve as a trigger to mitigate the dark count rate, thereby preventing undue saturation of the available bandwidth. This paper presents an investigation into a fast and resource-efficient method for filtering the Silicon Photomultiplier dark count rate. A low-resource and fast coincident filter has been developed, which removes the Silicon Photomultiplier dark count rate by using as a trigger the Photomultiplier Tube input signals. The architecture of the coincidence filter, together with the first results obtained, which validate the effectiveness of this method, is presented.

A 2.4 GHz Wide-Range CMOS Current-Mode Class-D PA with HD2 Suppression for Internet of Things Applications.

Short-range Internet of Things (IoT) sensor nodes operating at 2.4 GHz must provide ubiquitous wireless sensor networks (WSNs) with energy-efficient, wide-range output power (POUT). They must also be fully integrated on a single chip for wireless body area networks (WBANs) and wireless personal area networks (WPANs) using low-power Bluetooth (BLE) and Zigbee standards. The proposed fully integrated transmitter (TX) utilizes a digitally controllable current-mode class-D (CMCD) power amplifier (PA) with a second harmonic distortion (HD2) suppression to reduce VCO pulling in an integrated system while meeting harmonic limit regulations. The CMCD PA is divided into 7-bit slices that can be reconfigured between differential and single-ended topologies. Duty cycle distortion compensation is performed for HD2 suppression, and an HD2 rejection filter and a modified C-L-C low-pass filter (LPF) reduce HD2 further. Implemented in a 28 nm CMOS process, the TX achieves a wide POUT range of from 12.1 to -31 dBm and provides a maximum efficiency of 39.8% while consuming 41.1 mW at 12.1 dBm POUT. The calibrated HD2 level is -82.2 dBc at 9.93 dBm POUT, resulting in a transmitter figure of merit (TX_FoM) of -97.52 dB. Higher-order harmonic levels remain below -41.2 dBm even at 12.1 dBm POUT, meeting regulatory requirements.

Fast and Perfect Sampling of Subgraphs and Polymer Systems

We give an efficient perfect sampling algorithm for weighted, connected induced subgraphs (or graphlets ) of rooted, bounded degree graphs. Our algorithm utilizes a vertex-percolation process with a carefully chosen rejection filter and works under a percolation subcriticality condition. We show that this condition is optimal in the sense that the task of (approximately) sampling weighted rooted graphlets becomes impossible in finite expected time for infinite graphs and intractable for finite graphs when the condition does not hold. We apply our sampling algorithm as a subroutine to give near linear-time perfect sampling algorithms for polymer models and weighted non-rooted graphlets in finite graphs, two widely studied yet very different problems. This new perfect sampling algorithm for polymer models gives improved sampling algorithms for spin systems at low temperatures on expander graphs and unbalanced bipartite graphs, among other applications.

Rejection sampling and agent-based models for data limited fisheries

Many of the world’s fisheries are “data-limited” where the information does not allow precise determination of fish stock status and limits the development of appropriate management responses. Two approaches are proposed for use in data-limited stock management strategy evaluations to guide the evaluations and to understand the sources of uncertainty: rejection sampling methods and the incorporation of more complex socio-economic dynamics into management evaluations using agent-based models. In rejection sampling (or rejection filtering) a model is simulated many times with a wide range of priors on parameters and outcomes are compared multiple filtering criteria. Those simulations that pass all the filters form an ensemble of feasible models. The ensemble can be used to look for robust management strategies, robust to both model uncertainties. Agent-based models of fishery economics can be implemented within the rejection framework, integrating the biological and economic understanding of the fishery. A simple artificial example of a difference equation bio-economic model is given to demonstrate the approach. Then rejection sampling is applied to an agent-based model for the hairtail (Trichiurus japonicas) fishery, where an operating model is constructed with rejection/agent-based methods and compared to known data and analyses of the fishery. The usefulness of information and rejection filters are illuminated and efficacy examined. The methods can be helpful for strategic guidance where multiple states of nature are possible as a part of management strategy evaluation.

Standoff Deep Ultraviolet Raman Spectrometer for Trace Detection.

We developed a state-of-the-art, high-sensitivity, low-stray-light standoff deep-ultraviolet (DUV) Raman spectrometer for the trace detection of resonance Raman-enhanced chemical species. As an excitation source for Raman measurements, we utilized our recently developed, second-generation, miniaturized, diode-pumped, solid-state neodymium-doped gadolinium orthovanadate (Nd:GdVO4) laser that generates quasi-continuous wave 228 nm light. This 228 nm excitation enhances the Raman intensities of vibrations of NOx groups in explosive molecules, aromatic groups in biological molecules, and various aromatic hydrocarbons. Our DUV Raman spectrograph utilizes a custom DUV f/8 Cassegrain telescope with an ∼200 mm diameter primary mirror, high-efficiency DUV transmission gratings, custom DUV mirrors, and a custom 228 nm Rayleigh rejection filter. We utilized our new standoff DUV Raman spectrometer to measure high signal-to-noise ratio spectra of ∼50 μg/cm2 drop-cast explosives: ammonium nitrate (AN), trinitrotoluene, pentaerythritol tetranitrate as well as aromatic biological molecules: lysozyme, tryptophan, tyrosine, deoxycytidine monophosphate, deoxyadenosine monophosphate at an ∼3 m distance within 10-30 s accumulation times. We roughly estimate the average ultraviolet resonance Raman (UVRR) detection limits for the relatively homogeneous drop-cast films of explosives and biological molecules to be ∼1 μg/cm2 when utilizing a continuous raster scanning that averages Raman signal over ∼1 cm2 sample area to avoid quick analyte depletion due to ultraviolet (UV) photolysis. We determined 3 m standoff UVRR detection limits for drop-cast AN films and identified factors impacting UVRR detection limits such as analyte photochemistry and analyte morphology. We found a detection limit of ∼0.5 μg/cm2 for drop-cast AN films on glass substrates when the Raman signal is averaged over ∼0.5 cm2 of sample surface using a continuous raster scan. For a step raster scan, when the probed sample area is limited to the laser spot size, the detection limit is approximately tenfold higher (∼5 μg/cm2) due to the impact of UV photochemistry.

78.8 pJ/b, 100 Mb/s Noncoherent IR-UWB Receiver for Multichannel Neurorecording Implants.

In this article, we present a novel approach for designing a low-power, low-area impulse radio ultra-wideband (IR-UWB) noncoherent receiver capable of achieving a data rate of 100 Mbps. Our proposed receiver demonstrates the ability to demodulate ON-OFF keying pulse streams across the entire lower frequency band defined by the Federal Communication Commission for UWB applications. The key components of the proposed receiver include a reconfigurable differential two-stage low-noise amplifier, a fully differential squarer, narrow-band interface rejection filters, and variable gain baseband amplifiers. These circuits work cohesively to ensure efficient signal reception and processing. To validate the performance of the proposed receiver, we implemented the design using TSMC 40-nm CMOS process technology. A short-range communication including a 1.5 cm tissue layer is tested utilizing a typical upconversion UWB transmitter fabricated in the same technology. Remarkably, the proposed receiver achieves a data rate of 100 Mbps with an impressively low energy efficiency of 78.8 pJ/b and occupies an area of 0.705 mm2. The compact size, remarkable energy efficiency, and high data rate capabilities of the proposed receiver meet the stringent requirements of neural recording implants.

Investigating population-specific epilepsy detection from noisy EEG signals using deep-learning models

“Epilepsy is a chronic brain disorder that affects people of all ages. The cause of epilepsy is often unknown and its effect in different age groups is not yet investigated. The main objective of this study is to introduce a novel approach that successfully detects epilepsy even from noisy EEG signals. In addition, this study also investigates population specific epilepsy detection for providing novel insights. Correspondingly, we utilized the TUH EEG corpus database, publicly available challenging multi-channel EEG database containing detailed patient information. We applied a band-pass filter and manual noise rejection to remove noise and artifacts from EEG signals. We then utilized statistical features and correlation to select channels, and applied different transform analysis methods such as continuous wavelet transform, spectrogram, and Wigner-Ville distribution, with and without ensemble averaging, to construct an image dataset. Afterwards, we used various deep-learning models for general analysis. Our findings suggest that different models such as DenseNet201, DenseNet169, DenseNet121, VGG16, VGG19, Xception, InceptionV3, and MobileNetV2 performed better while using images generated from different approaches in general analysis. Furthermore, we split the dataset into two sections according to age for population analysis. All the models that performed well in the general analysis were used for population analysis, which provided novel insights in epilepsy detection from EEG. Our proposed framework for epilepsy detection achieved 100% accuracy, which outperforms other concurrent methods."

Comparison of a Pre-Trained AI Contouring Model to Unseen Institutional Data

To compare contours generated by a pre-trained, commercial AI model to those manually drawn in house. Previously treated radiotherapy patients (N = 20 per site) for several sites (brain, head & neck, thorax, abdomen, pelvis) with approved structure sets were selected for this retrospective analysis. For the planning CT of each patient, a pre-trained AI model auto-contoured several OARS: bladder, brain, eyes, femurs, kidneys, lenses, mandible, and parotids, etc. A two-step rejection method filtered the results based on unmatched structure names (i.e., contours existing in only one of the two structure sets causing incorrect auto-matching of structure names by the comparison algorithm), and structures with different superior and/or inferior extents. From the remaining contours, DSC (Dice Similarity Coefficient) and HD95% (95th percentile of Hausdorff Distance) were calculated between auto and manually generated contours using vendor-supplied software; median values were then calculated. The entire data set contained 592 structures at the on-set of analysis. After applying the rejection filters, the remaining data had 294 structures; a large portion of filtering was due to unmatched names. Out of these, OARs with contours from at least 10 patients (N>9) were further analyzed to include the 25th and 75th percentile for DSC and HD95%. Results from this analysis (structures with N>9) are presented in the table below, where results of left-right paired structures are combined into one row. The submandibular glands, larynx, and optical nerves (5 < N < 10) all had median DSC < 0.77 while lungs had median DSC > 0.98 (N = 6). Parotids and lenses had poor DSC and HD95% scores and may require significant contour editing to achieve agreement with our clinical conventions. This study highlights the difficulty with retrospective analysis of contours with an external trained model due to variations in the superior/inferior extent of tubular structures such as rectum, cord, esophagus, etc. CONCLUSION: Results are encouraging, given that the pre-trained commercial model has not seen our institutional data. The pre-trained AI contouring model matched very well to manual contours for large volume, higher contrast structures but did not match well for parotids and lenses. Variability in conventions regarding the superior/inferior extent of some structures hinders retrospective comparison with a pre-trained AI model.

Designing cladding mode interference device – a host for sensors and all-fiber inline gain-flattening component and broad-band filter

This article describes how to devise interference and self-imaging of core and cladding modes based devices using dissimilar core concatenated all-fibers. The core diameter mismatch in the structure excites the cladding modes with the core mode that leads to a progressive interference imaging between the cladding modes and the core mode yielding wavelength and refractive index dependent loss. Through a systematic study, we tune the device parameters to gauge temperature and concentration with sensitivity of 0.0713 dB/°C and 0.0372 dB/(% mL/mL) respectively as a high-performance fiber sensor. Next, optimizing the wavelength sensitive parameters of the host configuration, we investigate the transmission characteristics as gain-flattening filters (GFF) of Erbium-doped fiber amplifiers (EDFAs) with maximum gain variations of 0.91 and 0.97 dB, for two different EDFAs respectively over a wavelength band of 33 and 25 nm. Finally, we demonstrate a tunable and two-flattop band rejection filters with rejection band of 14, 26 and 46 nm, respectively.

Ultra-High Peak Rejection, Sub-Gigahertz Narrowband and Bandwidth Tunable Microwave Photonic Filter Based on Silicon Racetrack Resonators

We propose and experimentally demonstrate a notch microwave photonic filter (MPF) with optimized performance (including the sub-gigahertz narrowband, ultra-high rejection ratio and tunable bandwidth) based on two cascaded silicon Mach–Zehnder interferometers (MZI) coupled microring resonators (MRRs). The MRR structure is optimized to obtain a high quality (Q) factor (corresponding to a sub-gigahertz 3dB-bandwidth), adjustable bandwidths and extinction ratios. One ring is designed as the over-coupled state with a π resonant peak phase shift while the other ring performs the under-coupled state with 0 peak phase shift. Under the intensity modulation, an extremely high MPF rejection ratio could be obtained capitalizing the complete interference cancellation technology. Moreover, the MPF bandwidth and central frequency could be flexibly tuned by adjusting the MRR bandwidths and resonant wavelengths, respectively. The experimental results demonstrate the notch MPF response with a narrow 3dB-bandwidth of 185 MHz, an extremely high rejection ratio beyond 70 dB and a 3dB-bandwidth tuning range from 185 MHz to 1.263 GHz. To the best of our knowledge, it is the first time to realize the silicon-based notch narrowband MPFs with the ultra-high rejection ratio (> 70 dB) and a 3dB-bandwidth tuning range from sub-gigahertz to gigahertz level. The proposed silicon-on-insulator-based MPF with competitive performance paves a way for on-chip high-quality microwave signal processing.