Adaptive Pulse Research Articles

Multi-source information fused loose particle localization and material identification method for sealed electronic equipment

Sealed electronic equipment are1 an important component of aerospace defense systems, and loose particles pose a significant threat to their reliable operation. Loose particle detection is crucial. For sealed electronic equipment with large scale and complex structure, loose particle detection should not only include the judgment of existence, but also obtain location and material information to facilitate the cleaning and control work. In this paper, the authors proposed a multi-source information fused loose particle localization and material identification method. Firstly, the equipment model was designed, the loose particle samples were made, and loose particle signals were collected. Secondly, the two-stage adaptive energy threshold pulse extraction algorithm was newly proposed to extract effective pulses, and the threshold-judgement-search pulse matching algorithm was improved to match the effective pulse groups. Next, spectrograms were transformed from effective pulses to create the localization and material image set. The time-domain, frequency-domain and gray-level co-occurrence matrix features were used to construct the joint feature library. Then, the channel-weighting feature selection method was used to create the localization and material data set. Finally, PReLU-VGG19-Plus was trained on the localization and material image set to obtain the optimal localization and material neural network, while parameter-optimized XGBoost was trained on the localization and material data set to obtain the optimal localization and material classifier. On this basis, combined with the triple majority voting process, the combined localization and material framework were constructed. Extensive test results show that, the location-identification achieved by combined localization framework and the material-identification accuracy achieved by combined material framework are all 100%. The feasibility, stability, and superiority of the method proposed in this paper have been fully verified. It is an important supplement to the existing loose particle detection research, providing important reference for signal detection and classification research in similar fields, and effectively improving the reliability of sealed electronic equipment.

Multi-receptor skin with highly sensitive tele-perception somatosensory.

The limitations and complexity of traditional noncontact sensors in terms of sensitivity and threshold settings pose great challenges to extend the traditional five human senses. Here, we propose tele-perception to enhance human perception and cognition beyond these conventional noncontact sensors. Our bionic multi-receptor skin employs structured doping of inorganic nanoparticles to enhance the local electric field, coupled with advanced deep learning algorithms, achieving a ΔV/Δd sensitivity of 14.2, surpassing benchmarks. This enables precise remote control of surveillance systems and robotic manipulators. Our long short-term memory-based adaptive pulse identification achieves 99.56% accuracy in material identification with accelerated processing speeds. In addition, we demonstrate the feasibility of using a two-dimensional (2D) sensor matrix to integrate real object scan data into a convolutional neural network to accurately discriminate the shape and material of 3D objects. This promises transformative advances in human-computer interaction and neuromorphic computing.

Fat Suppression in Distal Extremity 3-T MRI Using Spectral Heterogeneity Adaptive Radiofrequency Pulses.

Background Conventional chemical shift selective (CHESS) fat suppression may fail in distal extremity MRI due to sensitivity to field inhomogeneities. Purpose To develop a patient-specific fat-suppression method for distal extremity 3-T MRI by exploiting the spectral heterogeneity adaptive radiofrequency pulse (SHARP) technique and to compare it to fat suppression with CHESS. Materials and Methods SHARP uses the routinely acquired frequency spectrum at MRI calibration to adapt the frequency range and time-bandwidth product of the fat-suppression pulse. In this prospective study, fat suppression by SHARP was assessed by numerical simulations, phantom experiments, and imaging in 15 asymptomatic participants who underwent ankle, foot, and hand (in superman and hand-by-the-side positions) MRI using SHARP, CHESS, and reference standard (short-tau inversion recovery or Dixon) techniques. Three readers ranked the MRI scans from 1 (best) to 3 (worst) regarding fat-suppression homogeneity. The added value of SHARP was defined as the difference between the proportions of images where SHARP outranked CHESS and where CHESS outranked SHARP. Friedman, Wilcoxon signed rank, and χ2 tests were used to compare in vivo data. Results At numerical simulations, SHARP showed 0% water and 62%-70% fat suppression, whereas CHESS showed 2% water and 57% fat suppression. Phantom data demonstrated lower fat-suppression inhomogeneity indexes with Dixon (1.0%) and SHARP (2.4%) compared with CHESS (10.7%). In 15 participants (mean age, 38.5 years ± 12.8 [SD]; six female participants), mean ranking by readers of fat homogeneity in the reference technique (ankle, foot, hand in superman position, and hand-by-the-side position: 1.02, 1.02, 1.03, and 1.06, respectively) was higher than those with SHARP (1.39, 1.46, 1.50, and 1.66, respectively), which were higher than those with CHESS (1.64, 1.80, 1.61, and 1.80, respectively) (all P < .001). The added value of SHARP was highest for images in the foot (389 of 1158; 33.6%; P < .001 vs other joints), followed by the ankle (247 of 971 [25%]; P < .001 vs both hand positions), and lowest for hand-by-the-side and hand in superman positions (158 of 1223; [13%] and 133 of 1193 [11%], respectively; P = .18). Conclusion SHARP provided more homogeneous fat suppression than CHESS. © RSNA, 2024 Supplemental material is available for this article.

Robust Electrothermal Switching of Optical Phase‐Change Materials through Computer‐Aided Adaptive Pulse Optimization

Electrically tunable optical devices present diverse functionalities for manipulating electromagnetic waves by leveraging elements capable of reversibly switching between different optical states. This adaptability in adjusting their responses to electromagnetic waves after fabrication is crucial for developing more efficient and compact optical systems for a broad range of applications, including sensing, imaging, telecommunications, and data storage. Chalcogenide‐based phase‐change materials (PCMs) have shown great promise due to their stable, nonvolatile phase transition between amorphous and crystalline states. Nonetheless, optimizing the switching parameters of PCM devices and maintaining their stable operation over thousands of cycles with minimal variation can be challenging. Herein, the critical role of PCM pattern as well as electrical pulse form in achieving reliable and stable switching is reported on, extending the operational lifetime of the device beyond 13000 switching events. To achieve this, a computer‐aided algorithm that monitors optical changes in the device and adjusts the applied voltage in accordance with the phase transformation process is developed, thereby significantly enhancing the lifetime of these reconfigurable devices. The findings reveal that patterned PCM structures show significantly higher endurance compared to blanket PCM thin films.

Adaptive pulse shaping for OFDM RadCom systems in highly dynamic scenarios

Due to the spectrum and complexity efficiency, the integrated radar and communications (RadCom) systems have been widely favored, in which orthogonal frequency division multiplexing (OFDM) is the most popular signal to conduct the two functions simultaneously. However, an unoptimized pulse could suffer from severe inter-carrier interference (ICI) and high out-of-band emission (OOBE), which greatly degrades the system performance. In this paper, we introduce the pulse shaping scheme dedicated to RadCom systems, in which both transmitter and receiver can adaptively design pulses with the assistance of radar estimation. We first optimize the transmitting pulse with the weighted sum of signal-to-interference-plus-noise ratio (SINR) and OOBE by employing the popular genetic algorithm. Then, we design an improved-matched pulse at the receiver for maximizing the SINR with the fmincon solver. In this way, they both utilize the readily available radar information and keep the pulse optimal even in highly dynamic scenarios, which makes the most of RadCom systems while avoiding the overhead of channel estimation and feedback. Simulations prove the feasibility of proposed scheme and reveal that the radar image and communications SINR stay close to their optimum in most cases with much lower OOBE. An improved-matched pulse can further improve the communications performance when severe ICI occurs compared with a matched pulse.

Fusion of Infrared and Visible Light Images Based on Improved Adaptive Dual-Channel Pulse Coupled Neural Network

Fusion of Infrared and Visible Light Images Based on Improved Adaptive Dual-Channel Pulse Coupled Neural Network

Piezoelectric energy harvesting interface with fast open-circuit voltage sampling

This paper presents a piezoelectric energy harvesting interface with fast open-circuit voltage (VOC) sampling and a wide operating frequency range. The fractional open-circuit voltage (FOCV) method is the primary method for maximum power point tracking (MPPT) in energy harvesting systems, due to its easy implementation and relatively low cost. For this method to be efficient, it is necessary to shorten the time required for VOC sampling. To minimize power loss due to VOC sampling, a novel technique is proposed that is capable of sampling the VOC within a time shorter than half a cycle by using an adaptive tracking pulse instead of conventional fixed ones. We also present a peak detector design technique that can operate across a broad frequency spectrum and adapt to diverse vibration scenarios. The proposed technique reduces the duty cycle of the tracking pulse to 0.42%, which is 3.7 times smaller than the conventional 1.56%. The proposed circuit, designed using a 0.35μm complementary metal oxide semiconductor (CMOS) process, consumes just 94nA at 100Hz, 3V VOC, and a 1kΩ load. In a 2~4V VOC range and a 15~500Hz frequency range, the MPPT efficiency exceeds 95%, peaking at 99.9%, and the power efficiency remains over 93%, reaching a maximum of 97.7%.

Adaptive radar pulse detection design based on difference of box filter

AbstractPrecise radar pulse detection is the premise of electronic support measures. A constant false alarm rate (CFAR) detection algorithm based on difference of box (DOB) filter is proposed to realise low‐complexity and environment‐adaptive radar pulse detection, and the principle behind the proposed algorithm is revealed. Specifically, the DOB filter is adopted to extract the rising edges and falling edges of radar pulses, and the signal variation law of probability density functions (PDFs) during the process of DOB filter are first theoretically analysed. Based on the derived PDFs, dynamic detection threshold and fixed threshold factor for the proposed CFAR algorithm based on DOB filter are deduced to detect the presence of radar pulses. Furthermore, the closed‐form expression of the detection probability is derived. Simulations and on‐board field programmable gate arrays implementation verify the superiority of the proposed CFAR algorithm based on DOB filter. Simulation results show that the proposed algorithm performs well in detecting various types of pulse signals, the detection probability ≥99% on condition that the signal‐to‐noise ratio ≥3 dB and false alarm probability = 10−8. Moreover, the proposed CFAR algorithm based on DOB filter can deal with both singular pulses and pulse on pulse signals.

Reliability Improvement in Vertical NAND Flash Cells Using Adaptive Incremental Step Pulse Programming (A-ISPP) and Incremental Step Pulse Erasing (ISPE)

Reliability Improvement in Vertical NAND Flash Cells Using Adaptive Incremental Step Pulse Programming (A-ISPP) and Incremental Step Pulse Erasing (ISPE)

Review of High Voltage Pulsed Power Supplies and Power Electronics in Pulse Power Generation

Recently, pulse-shaped power supplies have become more popular. Pulsed power is versatile and useful as a supply method since it can take several shapes and has many pulse characteristics. The release of electrons, protons, and neutrons from an atom and the synthesis of molecules to generate ions or other molecules require a lot of immediate energy. Pulsed power is needed for decomposition, molecular fusion and material joining, radiation generation (e.g., electrons, lasers, radar), explosive processes for concrete recycling, wastewater and exhaust gas treatment, and material surface treatments. Industrial and environmental applications require pulsed power, which requires efficient and adaptive pulse modulators. Higher-quality repeating pulses are needed for plasma fusion and laser weapons. Marx Generators, Magnetic Pulse Compressors, Pulse Forming Networks, and Multistage Blumlein Lines have several uses. Pulse modulators use spark gap and hydrogen thyratron gas/magnetic switching technologies for their high voltage tolerance and low-rise times. These creatures are inefficient, unreliable, repetitious, and short-lived. These devices are heavy, bulky, and expensive. Solid-state switching technology can replace conventional devices, improving pulse supply. High-frequency switching repeats the pulsed power supply. These items are compact, efficient, affordable, reliable, and durable. Solid-state transistor applications may not meet switch voltage ratings and rise time constraints. Various power electronics configurations can produce solid-state high-voltage pulses.

Adaptive Pulse Wave Extraction Method for Radial Artery Video

Adaptive Pulse Wave Extraction Method for Radial Artery Video

Gated recurrent unit predictor model-based adaptive differential pulse code modulation speech decoder

Speech coding is a method to reduce the amount of data needs to represent speech signals by exploiting the statistical properties of the speech signal. Recently, in the speech coding process, a neural network prediction model has gained attention as the reconstruction process of a nonlinear and nonstationary speech signal. This study proposes a novel approach to improve speech coding performance by using a gated recurrent unit (GRU)-based adaptive differential pulse code modulation (ADPCM) system. This GRU predictor model is trained using a data set of speech samples from the DARPA TIMIT Acoustic-Phonetic Continuous Speech Corpus actual sample and the ADPCM fixed-predictor output speech sample. Our contribution lies in the development of an algorithm for training the GRU predictive model that can improve its performance in speech coding prediction and a new offline trained predictive model for speech decoder. The results indicate that the proposed system significantly improves the accuracy of speech prediction, demonstrating its potential for speech prediction applications. Overall, this work presents a unique application of the GRU predictive model with ADPCM decoding in speech signal compression, providing a promising approach for future research in this field.

Research on SiC Speed Controller for High‐Voltage Distributed Electric Propulsion System

The shift towards green aviation necessitates the adoption of all‐electric aircraft, marking an essential trend in the aviation industry. Distributed propulsion systems enhance aircraft flexibility and reliability, synchronously reducing performance demands and costs of single propulsion units compared to centralized propulsion system. The high reliability and lightweight characteristics of brushless DC motors have made them increasingly popular in distributed propulsion systems. Despite its advantage which helps to build efficient aircraft aerodynamic layout, there are more cables in the distributed propulsion system, which accounts for most of the weight of the aircraft. To address this, all‐electric aircraft utilizes high‐voltage power supply to reduce the current, so it uses SiC MOSFETs as power devices to improve its efficiency and heat dissipation. The speed controller in all‐electric aircraft determines the efficiency and reliability of the propulsion unit. However, the traditional high‐voltage speed controller poses challenges for aircraft maintenance because of high cost. Therefore, this paper emphasizes the significance of designing a low‐cost, high‐performance speed controller for all‐electric aircraft. Challenges such as circuit interference, battery voltage fluctuation, and sampling noise affecting the high‐voltage controller during operation are solved, respectively. First, to address the likelihood of mutual interference in the bridge arm, a self‐bootstrapping voltage reduction drive mode is designed to turn off SiC MOSFET and enhance circuit anti‐interference. Second, to solve the challenge of wide battery voltage fluctuation range and inconsistent controller output, an adaptive pulse width modulation (PWM) regulation mode for battery voltage is proposed, ensuring stable controller output. Finally, to counteract the impact of the comparator threshold on zero‐crossing sampling, an electrical angle delay method based on delay compensation is designed to improve the efficiency of the brushless DC motor during operation. Experimental results show that the three solutions proposed in this paper are helpful to improve the anti‐interference, stability, and efficiency of the controller in the high‐voltage distributed electric propulsion system and contribute to reduce the cost and weight in the propulsion unit.

Advanced lifting wavelet transform and V‐degree polynomial‐based channel estimation in MIMO‐GFDM

SummaryThe future generation of wireless communications systems uses the generalized frequency division multiplexing (GFDM) due to its viable candidate waveform to perform multiple user scheduling. It is a non‐orthogonal waveform susceptible to intercarrier and intersymbol interference (ISI); still, it offers flexible pulse shaping that enhances the efficiency of user scheduling. Here, to accomplish spatial diversity, the multiple‐input multiple‐output (MIMO) is incorporated with GFDM to enhance the performance; there is also an extra inter‐antenna interference problem that limits the model's performance. The issue concerning inter‐antenna interference can be resolved by adopting pilot‐based information transfer. The detection of a signal at the receiver based on the minimum mean square error has the issue of computational complexity while enhancing the estimation quality of a detector. Hence, a low‐complexity channel estimation technique is proposed in this research using the V‐degree polynomial‐based channel estimation technique, wherein the cubic order computation is reduced to square order. Also, the proposed adaptive pulse shaping technique, wherein the filter coefficient is optimized using the gazelle optimization algorithm (GOA) to provide optimal pulse shaping filter parameters by employing bit error rate (BER) as the objective function. The performance of a proposed V‐degree polynomial‐based channel estimation is analyzed based on various assessment measures like BER and MSE and acquired the minimal values of 5.75E‐05 and 2.07E‐05, respectively.

Range Sidelobe Iterative Suppression Algorithm for Extended Target with Non-Grid Multiple Scattering Points

This paper concentrates on extended targets to suppress high sidelobes in non-grid multiple scattering points. Notice that the problem essentially resolves the high sidelobes of the non-grid multiple scatterers after locating positions; we proposed a novel iterative algorithm based on an adaptive pulse compression algorithm on the basis of an off-grid position estimation. First, the grid offsets of the multiple scattering points through decoherence and super-resolution techniques are estimated by employing an enhanced MUSIC algorithm. Then, an optimization model is constructed for the non-grid multiple scattering points of the target. Finally, a sidelobe suppression algorithm based on the minimum mean square error (MMSE) criterion is presented. Numerical results reveal that the proposed algorithm can achieve better estimation performance on the offsets of the non-grid multiple scattering points, while it suppresses range sidelobes effectively.

Self-Adaptive PDLC Control Strategy With Smart Light Intensity Adjustment Using Photovoltaic-Thermoelectric Hybrid Energy Supply Technology

As an electronically controlled glass whose transmittance varies with voltage, polymer dispersed liquid crystal (PDLC) has the advantages of good privacy, high transmittance, fast response speed, and good heat shielding performance. It can be applied to electronically controlled building windows. However, PDLC needs to consume extra power, and electronically controlled PDLC has not yet been integrated with intelligent home environment control. In this paper, we proposed an adaptive variable voltage step-size fast control algorithm in Field Programmable Gate Array (FPGA)-based home environment control system, which is powered by photovoltaic-thermoelectric (PV-TEG) hybrid sources. The power supply voltage of the PDLC can be dynamically changed through the adaptive Pulse width modulation (PWM) duty cycle adjustment technology to realize intelligent transmittance control, thereby improving the indoor lighting environment. Experimental results show that by applying the proposed algorithm, the indoor temperature is reduced by 2°C, and the adaptive and stable regulation of the optimal indoor illumination of 500 Lux can be completed in less than 2.5 seconds. This paper provides a feasible solution for the low-energy intelligent integrated control and monitoring of the modern home environment.

Adaptive Delta Modulation Simulation and Analysis Using MatLab

&#x0D; &#x0D; &#x0D; &#x0D; The system for converting analog signals to digital signals has become a necessity, considering that the tools currently used are digital computers. One of the analog-to-digital conversion systems is the delta modulation system. In delta modulation, only one bit is used to encode each change in the input signal, where a rising signal is encoded into a one bit and a falling signal is encoded into a zero bit. This can save the bit rate which, when transmitted over the transmission channel, can save the transmission bandwidth, and when stored in computer storage media, can save storage space. However, if the slope of the signal rises and falls sharply, the delta modulation system cannot follow these signal changes, which is called slope overload. To overcome this problem, an adaptive delta modulation system was developed that has variable or adaptive pulse height for both one and zero bits. In this paper, a comparison between the delta modulation system and the adaptive delta modulation system using MatLab application will be simulated and analyzed. From the simulation results, it can be seen that the adaptive delta modulation system is able to overcome slope overload compared to the delta modulation system.&#x0D; &#x0D; &#x0D; &#x0D;

Atlas-Based Adaptive Hadamard-Encoded MR Spectroscopic Imaging at 3T.

This study aimed to develop a time-efficient method of acquiring simultaneous, dual-slice MR spectroscopic imaging (MRSI) for the evaluation of brain metabolism. Adaptive Hadamard-encoded pulses were developed and integrated with atlas-based automatic prescription. The excitation profiles were evaluated via simulation, phantom and volunteer experiments. The feasibility of γ-aminobutyric acid (GABA)-edited dual-slice MRSI was also assessed. The signal between slices in the dual-band MRSI was less than 1% of the slice profiles. Data from a homemade phantom containing separate, interfacing compartments of creatine and acetate solutions demonstrated ~0.4% acetate signal contamination relative to the amplitude in the excited creatine compartment. The normalized signal-to-noise ratios from atlas-based acquisitions in volunteers were found to be comparable between dual-slice, Hadamard-encoded MRSI and 3D acquisitions. The mean and standard deviation of the coefficients of variation for NAA/Cho from the repeated volunteer scans were 8.2% ± 0.8% and 10.1% ± 3.7% in the top and bottom slices, respectively. GABA-edited, dual-slice MRSI demonstrated simultaneous detection of signals from GABA and coedited macromolecules (GABA+) from both superior grey and deep grey regions of volunteers. This study demonstrated a fully automated dual-slice MRSI acquisition using atlas-based automatic prescription and adaptive Hadamard-encoded pulses.

A Protocol for Digitalized Collection of Traditional Chinese Medicine(TCM) Pulse Information Using Bionic Pulse Diagnosis Equipment.

Pulse diagnosis equipment used in Traditional Chinese Medicine (TCM) has long been developed for collecting pulse information and in TCM research. However, it is still difficult to implement pulse taking automaticallyorefficiently in clinical practice. Here, we present a digital protocol for TCM pulse information collection based on bionic pulse diagnosis equipment, which ensures high efficiency, reliability and data integrity of pulse diagnosis information. A four-degree-of-freedom pulse taking platform together with a wrist bracket can satisfy the spatial positioning and angle requirements for individually adaptive pulse acquisition. Three-dimensional reconstruction of a wrist surface and an image localization model are combined to provide coordinates of the acquisition position and detection direction automatically. Three series elastic joints can not only simulate the TCM pulse taking method that "Three fingers in a straight line, the middle finger determining the 'Guan' location and finger pulp pressing on the radial artery," but also simultaneously carry out the force-controlled multi-gradient pressing process. In terms of pulse information integrity, this proposed protocol can generate rich pulse information, including basic individual information, pulse localization distribution, multi-gradient dynamic pulse force time series, and objective pulse parameters, which can help establish the fundamental data sets that are required as the pulse phenotype for subsequent comprehensive analysis of pulse diagnosis. The implementation of this scheme is beneficial to promote the standardization of the digitalized collection of pulse information, the effectiveness of detecting abnormal health status, and the promotion of the fundamental and clinical research of TCM, such as TCM pulse phenomics.

A novel medical image fusion method based on multi-scale shearing rolling weighted guided image filter.

Medical image fusion is a crucial technology for biomedical diagnoses. However, current fusion methods struggle to balance algorithm design, visual effects, and computational efficiency. To address these challenges, we introduce a novel medical image fusion method based on the multi-scale shearing rolling weighted guided image filter (MSRWGIF). Inspired by the rolling guided filter, we construct the rolling weighted guided image filter (RWGIF) based on the weighted guided image filter. This filter offers progressive smoothing filtering of the image, generating smooth and detailed images. Then, we construct a novel image decomposition tool, MSRWGIF, by replacing non-subsampled shearlet transform's non-sampling pyramid filter with RWGIF to extract richer detailed information. In the first step of our method, we decompose the original images under MSRWGIF to obtain low-frequency subbands (LFS) and high-frequency subbands (HFS). Since LFS contain a large amount of energy-based information, we propose an improved local energy maximum (ILGM) fusion strategy. Meanwhile, HFS employ a fast and efficient parametric adaptive pulse coupled-neural network (AP-PCNN) model to combine more detailed information. Finally, the inverse MSRWGIF is utilized to generate the final fused image from fused LFS and HFS. To test the proposed method, we select multiple medical image sets for experimental simulation and confirm its advantages by combining seven high-quality representative metrics. The simplicity and efficiency of the method are compared with 11 classical fusion methods, illustrating significant improvements in the subjective and objective performance, especially for color medical image fusion.