Pulse Signal Research Articles

Spatial Selection-Based Intelligent N-OFDM Signal Processing in Wireless Communication Systems

The method of joint processing of pulses and OFDM (N-OFDM) signals is proposed. The corresponding analytical relations for the lower Cramer-Rao boundary on the dispersion of OFDM (N-OFDM) signals amplitude ratings in the presence of sources of pulsed radiation are obtained. Using mathematical modeling properties and limitations of the demodulation method of OFDM (N-OFDM) signals in the background of impulse signals in the integrated radar and telecommunication systems are established. It is determined that the use of the angular distance between the pulsed and OFDM signals sources at a value that is not less than 0.75 widths of the secondary beam of the digital antenna array pattern does not affect the accuracy of the OFDM signal amplitudes. The same applies to the active interferences.

ON THE FEATURES OF REFLECTION OF SHEAR ELASTIC WAVE PULSES FROM A VERTICAL CRACK

A computer simulation of the characteristics of pulse signals of shear waves reflected from the edge of a vertical crack coming to the surface of the control object and a bottom crack using radiated pulses of various lengths with narrow, medium width and wide spectra was carried out. Within the limits of changing the calculation parameters, a feature of pulse reflection is established – the ratio of the maxima of the envelope pulses when reflected from a crack coming to the surface of the OK and the bottom crack is approximately 3.40 (10.6 dB), which coincides with the corresponding ratio of the maxima of the spectra. Based on the results of calculations of pulse shapes with frequency spectrum of different widths when waves are reflected from a vertical crack, the recommendation is justified not to use long pulses with narrow spectra with reduced beam resolution in the time of flight diffraction method.

Enhanced Model of Hybrid Controller for Smooth Switching of Energy Sources Used in Electric Vehicle Application

The sharing of load current to battery and ultracapacitor (UC) of the multiple energy storage structure (MESS) according to the vehicle dynamics is the main obstacle in the electric vehicles (EVs) application. In this paper, a control strategy technique is projected, to split the current between two sources based on the EVs requirement. A conventional/intelligent controller is used here to produce pulses to the DC-DC converter's corresponding load on the motor. A math condition-based controller (CBC) is designed by considering four individual math functions based on the speed condition of the motor, which is used to produce regulated pulse signals of the switches present in converters. The combination of CBC plus conventional/intelligent controllers makes a new hybrid controller, to achieve the main objective of the proposed work. The performance of the designed control strategy is investigated with four modes based on changed loads. Two different hybrid controllers CBC plus fuzzy logic (FLC) and CBC with proportional integral derivative (PID), and implemented and a comparative analysis was also made based on different time domain specifications by taking the speed curve as a reference.

Circuit design of a novel front readout circuit for SiC neutron detector with leakage current compensation

Radiation detectors have broad application prospects in environmental radiation monitoring, radiation source identification, biomedical imaging, space exploration, astrophysics, other radiation detection and imaging fields. Among the third generation semiconductors, the properties of 4H-SiC are more suitable for making high-temperature and strong radiation neutron detectors. SiC materials have become a current research hotspot. In this paper a special readout integrated circuit is designed for the extremely weak current pulse signal output by SiC trench neutron detector. A leakage current compensation circuit is designed for the influence of leakage current on charge sensitive amplifier(CSA) output baseline. The noise of CSA output is analyzed and the noise minimization is carried out. The circuit can quickly respond to the input signal and extract the energy and time information. The circuit is designed based on the DB Hitek 0.18μm CMOS process model. The layout design is achieved and the post-simulation is completed. Simulated results show that the equivalent input charge range of the system is about 2fC ∼ 20fC. The charge conversion gain is 88mV/fC. The nonlinear error is within 1.6 %. Moreover, the equivalent noise charge is 22e-. The circuit has the advantages of high gain, high linearity and low noise. Therefore, the circuit can effectively adapt to the characteristics of the charge signal output from SiC trench neutron detectors and amplify the output charge signal.

Simulation of Propagation of Video Pulse Signals of GPR in the Earth’s Lithosphere

Simulation of Propagation of Video Pulse Signals of GPR in the Earth’s Lithosphere

A three-dimensional coupled structure triboelectric nanogenerator for vertical and horizontal mechanical energy harvesting and fitness gait monitoring

Recently, the self-powered monitoring device used for wearable sensors has attracted attention from various industries. It is worth noting that previous self-powered sensors were mostly focused on unidirectional sensing and monitoring, and few sensors can achieve both longitudinal and transverse sensing functions simultaneously. Here, we designed an arched and stacked coupling structure triboelectric nanogenerator (AS-TENG) to harvest horizontal and vertical mechanical energy. Meanwhile, the AS-TENG can simultaneously achieve sensing effects on longitudinal pressure and transverse pulling force. According to the results, the pulling force sensing sensitivity of AS-TENG can reach 2.415 V N−1, and the pressure sensing sensitivity of AS-TENG can arrive at 2.78 V N−1. Furthermore, under longitudinal 6 Hz mechanical motion excitation, the open-circuit voltage (Voc) and short circuit current (Isc) of AS-TENG can reach 28.21 μA and 173.25 V, respectively. The transfer charge (Qsc) of AS-TENG can arrive at 169.7 nC. The AS-TENG can achieve a maximum output power of 2.02 mW at a 3 MΩ load. Moreover, the sensing signal pulse width of AS-TENG can reach 180 ms, which is higher than the traditional arch structure’s 110 ms, indicating the unique advantages of AS-TENG in future fitness monitoring. This study provides a 3D triboelectric multi-directional sensor that will serve the fields of intelligent wearable fitness and sports.

Design of Pulse and Respiratory Signals Detection System

A pulse and respiration synchronous detection system is designed to explore the changes of physiological signals in different situations. The system obtains the corresponding signal through STM32 control pulse and respiratory acquisition circuit, calculates and displays real-time parameters such as heart rate and respiratory rate, and transmits the data to the upper computer for storage in the database. The experimental test results show that the system can monitor pulse and respiratory waveform in different situations, and the waveform is in good condition. Compared with medical pulse oximeter, the error of measured heart rate and blood oxygen concentration is less than 3%, and the error of respiratory rate is less than 5% compared with the actual value, which verifies the accuracy of system signal acquisition. The system is small in size, low in cost, and comfortable to wear, and can be applied in experimental research related to pulse and respiratory signals.

Design and Implementation of a Digital Matched Filter for Square Pulses Signals using FPGA

Design and Implementation of a Digital Matched Filter for Square Pulses Signals using FPGA

Nadifit, data-driven diagnosis: a clinical study for evaluating the significance of traditional Chinese medicine organ patterns through pulse diagnosis (nadi pariksha) for accurate pathology predictions

Background: Pulse diagnosis or nadipariksha, is a traditional diagnostic technique utilized in ayurveda and traditional Chinese medicine, analyzing various pulse characteristics such as force, patterns, rate, and rhythm to discern underlying health conditions. This method integrates TCM's five-element energy levels and Ayurveda's Tridosha levels to accurately identify the root cause of diseases, enabling practitioners to tailor treatments accordingly. In today's fast-paced world, the need for efficient health monitoring is imperative. However, finding expert practitioners proficient in pulse diagnosis is becoming increasingly challenging, necessitating the development of systems capable of providing personalized health insights based on accurate root-cause analysis. Methods: In this study, we compared predicted symptoms derived from objective TCM organ pattern analysis using the Nadifit pulse diagnosis system with subjective clinical assessments of patients' symptoms. TCM organ patterns were determined based on the combination of five elements and their Yin/Yang energy levels. Pulse signals were collected from 105 individuals and compared with clinical evaluations of patients' symptoms. Results: The analysis revealed a high level of agreement between the clinical assessment of symptoms and the predicted organ patterns, with a Kappa coefficient of 0.82. This suggests that objective pulse analysis effectively identifies root causes, aligning with subjective assessments. Conclusions: The findings of this study underscore the validity and reliability of objective pulse analysis in diagnosing health conditions. By demonstrating significant agreement with subjective clinical assessments, this method provides a promising avenue for enhancing diagnostic accuracy and facilitating personalized treatment strategies based on individual health profiles.

Causal connectivity measures for pulse-output network reconstruction: Analysis and applications

The causal connectivity of a network is often inferred to understand network function. It is arguably acknowledged that the inferred causal connectivity relies on the causality measure one applies, and it may differ from the network's underlying structural connectivity. However, the interpretation of causal connectivity remains to be fully clarified, in particular, how causal connectivity depends on causality measures and how causal connectivity relates to structural connectivity. Here, we focus on nonlinear networks with pulse signals as measured output, e.g., neural networks with spike output, and address the above issues based on four commonly utilized causality measures, i.e., time-delayed correlation coefficient, time-delayed mutual information, Granger causality, and transfer entropy. We theoretically show how these causality measures are related to one another when applied to pulse signals. Taking a simulated Hodgkin-Huxley network and a real mouse brain network as two illustrative examples, we further verify the quantitative relations among the four causality measures and demonstrate that the causal connectivity inferred by any of the four well coincides with the underlying network structural connectivity, therefore illustrating a direct link between the causal and structural connectivity. We stress that the structural connectivity of pulse-output networks can be reconstructed pairwise without conditioning on the global information of all other nodes in a network, thus circumventing the curse of dimensionality. Our framework provides a practical and effective approach for pulse-output network reconstruction.

Magnetic-field oscillation model of pulsar radio emission: prediction of an observable effect

Abstract Since the discovery of pulsars, the rotating-lighthouse model has been the choice of model to explain the radiation pulsation of pulsars. After discovering that some main sequence stars (e.g. CU Virginis) and ultracool dwarfs (e.g. TVLM 513-46546) also behave like pulsars, the lighthouse model was again adopted to explain their pulse signals. Our research found that if we use the magnetic-field oscillation (MO) model, we can explain the pulse radiation results better regardless of whether its source is a neutron star, a main-sequence star or an ultracool dwarf. We propose a verifiable prediction that can be used to evaluate the MO model. Our prediction is that there is a 90○ phase lag between the magnetic field and radio signal of TVLM 513-46546, and the zero-crossing point of the magnetic field is the moment when the direction of the light’s circular polarization is reversed. No new observations are needed to check this prediction, but certain existing data needs to be re-mined.

A robust non-contact heart rate estimation from facial video based on a non-parametric signal extraction model

Remote photoplethysmography (rPPG) is a non-contact method to extract heart rate (HR) pulse signals from facial videos. However, challenges persist due to head motion disturbances and ambient illumination variations. To address these issues, a novel non-parametric signal extraction model is proposed for HR estimation using the webcam camera. We first select the better-quality RGB signal from the divided face regions through the ranking of signal-to-noise ratio (SNR). Then, we use blind source separation and skin reflection modeling to eliminate the effect of ambient illumination. Finally, we employ a non-parametric signal extraction model named circulant singular spectrum analysis (CiSSA), with frequency-based decomposition and energy-driven reconstruction, to extract the HR-related pulse signal effectively. To evaluate the performance of our method, we conducted the validation experiments on three datasets, including two public datasets (UBFC and PURE dataset) and one self-collected dataset (ILVA dataset). Our method outperformed significantly on all three datasets, achieving Mean Absolute Deviation (MAD) of 2.42, 1.36, and 2.84 bpm, Root Mean Square Error (RMSE) of 1.89, 2.24, and 3.58 bpm, and Pearson Correlation Coefficients (PCC) of 0.98, 0.98, and 0.93, respectively. The experimental results demonstrate that our method achieves comparable performance, particularly in scenarios involving severe head motion disturbances and variations in ambient illumination.

Research on the Mechanism of Flow-Induced Vibration in the Cooling System of a Double Crystal Monochromator

To investigate the mechanism of flow-induced vibrations in the cooling system of a double crystal monochromator (DCM), this paper utilizes a multi-physics numerical simulation approach, employing ANSYS and FLUENT platforms to simulate the flow state of liquid nitrogen in the cooling system and explore the amplitude response of the DCM. Initially, simulations were conducted to examine the flow state of liquid nitrogen with varying frequency and amplitude pulsations. Subsequently, modal analysis was employed to investigate the amplitude response of the DCM in the pitch direction vibrations under pulsating excitation. Finally, this research investigated the influence of high heat load-induced liquid nitrogen boiling on a DCM. The results indicate that pipe resistance is the fundamental cause of vibration induced by pulsating excitation. Low-frequency excitation enhances the amplification factor of DCM vibration. In contrast, due to the rapid conversion of fluid kinetic energy to pressure potential energy, high-frequency excitation increases the pulsation amplitude in the pipe. Additionally, there is a linear relationship between the amplitude of liquid nitrogen velocity fluctuations and the response amplitude of a DCM. The slug flow formed after liquid nitrogen boiling generates low-frequency pulse signals, and intermittent fluid impacts cause significant vibrations in the DCM. These research findings provide a reference for the analysis and design of ultra-high-stability DCM cooling systems.

A Coherent Integration Method for Moving Target Detection in Frequency Agile Signal-Based Passive Bistatic Radar

In this paper, the possibility of improving target detection performance in passive bistatic radar by exploiting a frequency agile (FA) signal is investigated, namely frequency agile signal-based passive bistatic radar (FAPBR) coherent integration. Since the carrier frequency of each pulse signal is agile, FAPBR coherent integration suffers from the problems of random range and Doppler phase fluctuations. To tackle these challenges, a novel FA signal coherent integration target detection scheme for PBR is proposed. In particular, the phase quadratic difference principle is presented for eliminating Doppler phase hopping. Then, frequency rearrangement is adopted to compensate for random range phase fluctuation while obtaining the high-range-resolution profiles (HRRPs) of the detecting target. Further, we innovatively present a sliding-range ambiguity decoupling (S-RAD) method to remove the range ambiguity effect in the case of the high pulse repetition frequency (HPRF). Compared with the existing methods, the proposed method can effectively mitigate Doppler phase hopping without requiring prior target velocity information, offering improved coherent integration performance in frequency agile signals with reduced computational complexity. Moreover, it successfully corrects the range ambiguity issue caused by HPRF. Finally, a series of simulation results are presented to demonstrate the effectiveness of the proposed algorithm.

Method for the Statistical Analysis of the Signals Generated by an Acquisition Card for Pulse Measurement

This article shows a method for the statistical analysis of signals. Firstly, this method was applied to analyze the processing of signs generated by an acquisition card for pulse measurement using the synchronous demodulation method. The application of the method allowed the study of each signal consisting of a descriptive statistical analysis, followed by the analysis of the trend and dynamics of the movement using the augmented Dickey–Fuller test and Hurst exponent, respectively. Secondarily, the method presented here supported the comparison between the pulse signals obtained by synchronous demodulation and plethysmography methods. In addition, the residuals from the pulse comparison of both methods were analyzed. To quantify the differences between the signals, these were compared using the mean-squared error, the root-mean-square error, the mean absolute error, the mean error, the mean absolute percentage error, and the mean percentage error. After this research, it was possible to analyze the signals knowing characteristics such as the following: the presence of normal, exponential, lognormal, and uniform distributions, stationary trend, and dynamic movement anti-persistent. The novelty that this article proposes is the use of concepts traditionally used in the study of time series and models of demand administration, now focused on supporting improvements over the different stages of design and conceptualization of signal processing devices.

Increased safety in periodontal surgery: Doppler ultrasound for detection of relevant palatal blood vessels-A proof-of-concept and cross-sectional study.

To evaluate the suitability of a Doppler ultrasound probe in detecting the greater palatine artery or its greater branches non-invasively. The palatal mucosa of 108 participants (median age 34 years, 51 female) was systematically divided into transversal sectors, each aligning with the positions of the upper molars (M), premolars (P) and canine teeth (C), aiming to facilitate precise and consistent localization of the detected palatal blood vessel across different patients. Blood flow of the palatal blood vessels, presumably, was located by scanning the palatal vault bilaterally using an 8-MHz ultrasound probe linked to a transducer. The distance to the corresponding tooth was measured using a millimetre-scale periodontal probe. Within the regions of M2 to P1, the ultrasound transducer gave a delimitable acoustic pulse signal in 80%-98% of all measurements. The measured median distances between the determined position of the artery and the corresponding teeth ranged from 13 to 15 mm, with smaller distances in the anterior region. In several sectors, the distance was significantly higher for men (C: p = .048; P1: p = .041, M1: p < .01; M2: p = .034). Use of the Doppler ultrasound transducer might be a promising approach to non-invasively detect relevant palatine blood vessels preoperatively. It, therefore, might have the potential to reduce the risk of accidental injury during palatal surgery.

Preserving shape details of pulse signals for video-based blood pressure estimation.

In recent years, imaging photoplethysmograph (iPPG) pulse signals have been widely used in the research of non-contact blood pressure (BP) estimation, in which BP estimation based on pulse features is the main research direction. Pulse features are directly related to the shape of pulse signals while iPPG pulse signals are easily disturbed during the extraction process. To mitigate the impact of pulse feature distortion on BP estimation, it is necessary to eliminate interference while retaining valuable shape details in the iPPG pulse signal. Contact photoplethysmograph (cPPG) pulse signals measured at rest can be considered as the undisturbed reference signal. Transforming the iPPG pulse signal to the corresponding cPPG pulse signal is a method to ensure the effectiveness of shape details. However, achieving the required shape accuracy through direct transformation from iPPG to the corresponding cPPG pulse signals is challenging. We propose a method to mitigate this challenge by replacing the reference signal with an average cardiac cycle (ACC) signal, which can approximately represent the shape information of all cardiac cycles in a short time. A neural network using multi-scale convolution and self-attention mechanisms is developed for this transformation. Our method demonstrates a significant improvement in the maximal information coefficient (MIC) between pulse features and BP values, indicating a stronger correlation. Moreover, pulse signals transformed by our method exhibit enhanced performance in BP estimation using different model types. Experiments are conducted on a real-world database with 491 subjects in the hospital, averaging 60 years of age.

Lightweight Arc Fault Detection Method Based on Adam-Optimized Neural Network and Hardware Feature Algorithm

Arc faults are the main cause of electrical fires according to national fire data statistics. Intensive studies of artificial intelligence-based arc fault detection methods have been carried out and achieved a high detection accuracy. However, the computational complexity of the artificial intelligence-based methods hinders their application for arc fault detection devices. This paper proposes a lightweight arc fault detection method based on the discrimination of a novel feature for lower current distortion conditions and the Adam-optimized BP neural network for higher distortion conditions. The novel feature is the pulse signal number per unit cycle, reflecting the zero-off phenomena of the arc current. Six features, containing the novel feature, are chosen as the inputs of the neural network, reducing the computational complexity. The model achieves a high detection accuracy of 99.27% under various load types recommended by the IEC 62606 standard. Finally, the proposed lightweight method is implemented on hardware based on the STM32 series microcontroller unit. The experimental results show that the average detection accuracy is 98.33%, while the average detection time is 45 ms and the average tripping time is 72–201 ms under six types of loads, which can fulfill the requirements of real-time detection for commercial arc fault detection devices.

Digitalization of Pulse Signal Processing for Ex-Core Instrumentation System in Nuclear Power Plants

Nuclear power plants (NPPs) are globally important sources of clean energy. However, high operation and maintenance (O&amp;M) costs are one of the factors hindering the development of NPPs. In this study, we focused on the development of a digital algorithm for ex-core instrumentation systems (EISs) to reduce O&amp;M costs, given that the digitalization of EISs is not progressing compared with other instrumentation and control systems in NPPs. Specifically, we developed a digital algorithm for pulse signal processing in EISs, which traditionally require a significant amount of hardware and maintenance efforts. Our purposes were to simplify the configuration and reduce the O&amp;M costs associated with pulse signal processing. To validate the algorithm, we used a detector emulator and a research reactor. Additionally, we explored a new approach to reduce the workload associated with a discrimination characteristics test (DCT) in EISs. The results of this study demonstrated that the proposed algorithm is effective in achieving good linearity within ±5% of the span and response performance with a delay time of 5 ms, which are required for EISs. Furthermore, the proposed method for the DCT shows promising results in reducing the time required for the test compared with conventional methods.

Spectral stability of a synchronously pumped optical parametric oscillator with a spatially dispersed beam

This study reports the spectral stability of a synchronously pumped optical parametric oscillator with a spatially dispersed beam. Using this method, broadband phase matching can be realized at any wavelength. However, large spectral fluctuations were observed in the signal pulses. Here, we demonstrate a stable condition under which the signal pulses have no spectral instabilities or pulse-to-pulse fluctuations. This stable condition was found through numerical simulations and confirmed experimentally.