Weak Pulse Signal Research Articles

Ultrasensitive Wearable Pressure Sensors with Stress-Concentrated Tip-Array Design for Long-Term Bimodal Identification.

The great challenges for existing wearable pressure sensors are the degradation of sensing performance and weak interfacial adhesion owing to the low mechanical transfer efficiency and interfacial differences at the skin-sensor interface. Here, an ultrasensitive wearable pressure sensor is reported by introducing a stress-concentrated tip-array design and self-adhesive interface for improving the detection limit. A bipyramidal microstructure with various Young's moduli is designed to improve mechanical transfer efficiency from 72.6% to 98.4%. By increasing the difference in modulus, it also mechanically amplifies the sensitivity to 8.5V kPa-1 with a detection limit of 0.14Pa. The self-adhesive hydrogel is developed to strengthen the sensor-skin interface, which allows stable signals for long-term and real-time monitoring. It enables generating high signal-to-noise ratios and multifeatures when wirelessly monitoring weak pulse signals and eye muscle movements. Finally, combined with a deep learning bimodal fused network, the accuracy of fatigued driving identification is significantly increased to 95.6%.

Weak signal detection method based on nonlinear differential equations

With the rapid development of computer network technology, it is often necessary to collect weak signals to collect favorable information. The development of signal detection technology is ongoing; however, various issues arise during the detection process. These issues include low efficiency and a high signal noise threshold. However, many problems will be encountered in the process of detection. In order to solve these problems, the nonlinear chaos theory is introduced to detect signals, and the simulation experiments of weak pulse signals and weak partial discharge signals are carried out respectively. The experimental results showed that the detection effect was remarkable in the quasi periodic state, and it had a good detection effect for weak pulse signals. At a signal-to-noise ratio of -25 dB, double coupling system, two-way ring coupling system, and single ring coupling system displayed detection success rates exceeding 98%. Meanwhile, the detection success rate of the strong coupling system was only 12%. Even at a noise signal ratio as low as -40 dB, the dual coupling system still maintained a detection success rate above 80%. The simulation results of partial discharge signal detection showed that there was a high fluctuation only at 2 ms, and the rest was basically stable at about 0 V, indicating that the system had a strong suppression effect on Gaussian white noise. When comparing the simulation results of the detection of the new chaotic system and the double coupling system, it was found that the new chaotic system has a superior impact in detecting weakly attenuated partial discharge signals. Through analysis of the system’s dynamic behavior, the research confirms its rich dynamic characteristics and sheds light on the reasons for phase state mutation and missed detection. The noise system is utilized for comparing the performance of various systems, with the goal of enhancing the system’s detection capability.

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.

Study on weak sound signal separation and pattern recognition under strong background noise in marine engineering

The extraction of weak acoustic signals under strong background noise is of great significance in the applications of target identification and localization. In this paper, the pulse signal with high randomness is set as the weak signal sound source, random noise and sine sound are used as the background noise. Under the condition of a signal-to-noise ratio of −20 dB, combined with blind source separation and neural network methods, the collected observation signals are subjected to weak sound signal separation and recognition research. The optimization method of centralization and scaling processing is used to eliminate the unfavorable influence of the uncertainty of the separated signal amplitude caused by the blind source separation method on the pattern recognition. The recognition result is verified by the combination of “weak impulse acoustic signal” and “random noise signal,” and the output vector (0.99 0.01 0.01) approaches (1 0 0), which is recognized as impulse acoustic signal. By combining blind source separation and neural network methods, the separation and identification of weak pulse signals under the condition of a signal-to-noise ratio of −20 dB can be achieved.

Weak pulse signal detection method based on improved strongly coupled oscillators

A strongly coupled oscillator can be used to detect weak pulse signals and recover waveforms, but its detection frequency of weak pulse signal is limited by the system’s built-in frequency. With a fixed built-in frequency, the system can only effectively detect and recover pulse signals in a certain frequency range, and waveform distortion occurs when pulse signals of higher frequencies are detected. In this work, the relationship between the built-in frequency of the coupled oscillator and the frequency detection range of weak pulse signal is analyzed, and two kinds of improved strongly coupled oscillator structures are proposed to extend the frequency detection range of weak pulse signals. By introducing the nonlinear restoring force coupling term, the nonlinear restoring force strongly coupled oscillator can effectively retain the high-frequency component of the signal, and can also better retain the signal characteristics when the pulse signal is input at a higher frequency. By introducing the Van der Pol-Duffing oscillator, the two-oscillator strong coupling system strengthens the stability of the internal structure of the system, and also achieves the effect of expanding the frequency detection range of the pulse signal. In addition, based on the variable iteration step size and frequency correlation of chaos detection, a method of detecting unknown frequency pulse signals is proposed. Instead of changing the built-in frequency of the system for frequency scanning, the method of changing the iteration step size is used. And using the frequency correlation of chaos detection, the correlation coefficient of the received signal and the recovered signal is compared with the correlation coefficient of the pure noise input case, then the pulse signals can be effectively detected based on the apparent difference between the two correlation coefficients. It is verified by simulation experiments that the proposed method can effectively detect the pulse signal of unknown frequency, and the proposed improved strong coupling oscillator has a greater performance improvement than that of the strong coupling oscillator.

Single‐Photon Based Three‐Party Quantum Secure Direct Communication with Identity Authentication

AbstractMultipartite quantum secure direct communication (MQSDC) enables multiple message senders to simultaneously and independently transmit secret messages to a message receiver through quantum channels without sharing keys. Existing MQSDC protocols all assume that all the communication parties are legal, which is difficult to guarantee in practical applications. In this study, a single‐photon based three‐party QSDC protocol with identity authentication is proposed. In the protocol, the message receiver first authenticates the identity of two practical message senders. Only when the identity authentication is passed, the legal message senders can encode their messages by the hyper‐encoding technology. In theory, two bits of messages can be transmitted to the message receiver in a communication round. The protocol can resist the external attack and internal attack, and guarantee the security of the transmitted messages and the identity codes of each legal message sender. The secret message capacity of the protocol is simulated with two‐decoy‐state method. The maximal communication distance between any two communication parties can reach 31.75 km with weak signal and decoy state pulses. The three‐party QSDC protocol can be extended to a general MQSDC protocol and has important application in the further practical MQSDC field.

High-speed real-time periodic weak pulse signal detection with simplified phase-weighted stacking.

Phase-weighted stacking (PWS) is an efficient noise reduction technique widely used in exploration seismology. It uses the coherence of the instantaneous phase to enhance signals by reducing incoherent noise. However, the high computational cost makes it difficult to apply PWS for the real-time detection of weak signals with high repetition frequency. This paper proposes a novel simplified PWS method with low computational complexity. The complex plane is divided into four quadrants, and the instantaneous phases in the same quadrant are simplified to the same phase. Based on the proposed method combined with a one-bit analog-to-digital converter, a novel field-programmable gate array-based high-speed real-time periodic weak pulse signal detection technique is presented. A prototype is implemented to verify the proposed technique. For weak pulse signals with an input signal-to-noise ratio (SNR) of -21 dB to -15 dB for 2500 cycles, the results obtained show that the simplified PWS algorithm can improve the SNR of the coherently integrated signals by about 10-15 dB with a latency of about 2 µs.

Dielectric modulation strategy of carbon nanotube field effect transistors based pressure sensor: towards precise monitoring of human pulse

Continuous monitoring of arterial pulse has great significance for detecting the early onset of cardiovascular disease and assessing health status, while needs pressure sensors with high sensitivity and signal-to-noise ratio (SNR) to accurately capture more health information concealed in pulse waves. Field effect transistors (FETs) combined with the piezoelectric film is an ultrahigh sensitive pressure sensor category, especially when the FET works in the subthreshold regime, where the signal enhancement effect on the piezoelectric response is the most effective. However, controlling the work regime of FET needs extra external bias assistance which will interfere with the piezoelectric response signal and complicate the test system thus making the scheme difficult to implement. Here, we described a gate dielectric modulation strategy to match the subthreshold region of the FET with the piezoelectric output voltage without external gate bias, finally enhancing the sensitivity of the pressure sensor. A carbon nanotube field effect transistor and polyvinylidene fluoride (PVDF) together form the pressure sensor with a high sensitivity of 7 × 10−1 kPa−1 for a pressure range of 0.038–0.467 kPa and 6.86 × 10−2 kPa−1 for a pressure range of 0.467–15.5 kPa, SNR, and the ability to continuously monitor pulse in real-time. Additionally, the sensor enables high-resolution detection of weak pulse signals under large static pressure.

Aperiodic stochastic resonance in a biased monostable system excited by different weak aperiodic pulse signals and strong noise

Aperiodic stochastic resonance in a biased monostable system excited by different weak aperiodic pulse signals and strong noise

PSR-LSTM model for weak pulse signal detection

PSR-LSTM model for weak pulse signal detection

Diagnosing the waveform of an ultrashort optical pulse by collinear interferometry

During the high-harmonic generation (HHG) process, information about field interaction with the medium is imprinted in the extreme ultraviolet (XUV) radiation. Here, we present a method for using HHG to diagnose the electric field of an optical pulse under a collinear geometry. When mixing a weak signal pulse with a strong driving pulse collinearly, the far field divergence of the XUV HHG is sensitive to the relative delay between the two pulses, which can be used as an ultrafast subcycle gate to reconstruct the electric field of the signal pulse. This collinear configuration is efficient, easy to operate and avoids artificial high order frequency components in reconstruction as compared to non-collinear schemes.

Pulse Wave Measuring via Fingertip-Like Sensor to Analyze and Identify Pulse-Rate Status

Pulse wave contains detailed information about the human cardiovascular system and is associated with various physiological changes. A fingertip-like pulse sensor based on a piezoresistive sensor was constructed to extract weak pulse signals with lossless performance. In the sensing mechanism, the external force was deformed through the flexible film and transmitted to the Wheatstone bridge to realize the force–electric conversion measurement. The sensor experiments revealed that the sensor’s performance had excellent linearity ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${R}^{2}&gt;0.9999$ </tex-math></inline-formula> ), low hysteresis (<1%), and high sensitivity (0.04 V/kPa). A pulse acquisition device based on pulse measuring was developed and applied to clinical practice for pulse signal measurement. Genuine pulse signals were obtained by removing high-frequency noise and baseline drift from the original pulse signal. A total of 55 volunteers aged 20–85 years with different health conditions were recruited, and eight were previously diagnosed with arrhythmia. Results demonstrated that the pulse period (PP) interval presented three different distribution patterns. Pulse signals obtained at different locations with various pressures showed potential application in digital pulse diagnostics.

Merkel cell-like artificial mechanoreceptor with high sensitivity and high resolution over a wide linear range

Mammalian mechanoreceptors endow the skin with the ability to perceive mechanical stimuli with precision. However, the fabrication of artificial mechanoreceptors with high sensitivity and resolution over a wide linear pressure range remains a key challenge. Herein, an artificial ion mechanoreceptor with the core-shell structured nanofibrous membrane as the sensitive layer is proposed by mimicking the biomechanical receptor. The membrane embeds ionic liquids and poly(vinylidene fluoride-co-hexafluoropropylene) hybrid nanofibers into a thermoplastic polyurethane matrix, enabling a reversible conversion between non-ionic and iontronic sensing modes induced by tactilely triggered ion movements. It exhibits a high sensitivity (32.70 kPa −1 ), a linear response (R 2 ≈ 0.999) over a wide range of 0.04 Pa to 209 kPa, and an ultra-high resolution of 0.035% at 100 kPa (far exceeding the resolution of skin of ∼7%). The receptors are further used to monitoring physiological signals (even weak fingertip pulse signals) and assembled into an array to aid object recognition. • A core-shell structured ionic nanofiber membrane is constructed • The receptor can transform from non-ionic sensing to iontronic sensing under pressure • Good compatibility between high sensitivity and high linearity • High resolution even under high preload pressure By simulating the mechanotransduction mechanism of Merkel cells, Yang et al. fabricate an artificial mechanoreceptor that modulates ion migration under external pressure, which achieves both high sensitivity (32.701 kPa −1 ) and high linearity (R 2 = 0.999). In addition, it maintains 0.035% resolution at a high preload pressure of 100 kPa.

Double-layer robust broad logistic regression for detecting weak pulse signal in chaotic interference

Owing to the extreme complexity of detecting weak signals submerged in chaotic interference, traditional neural network detection methods based on hypothesis testing are difficult to sufficiently portray the data and chaotic noise evolution characterization for achieving high effective training, and the hypothesis test usually has the shortcomings of poor generalization performance. In this article, a double-layer robust broad logistic regression (DRBLR) is proposed to overcome the aforementioned issues and achieve highly accurate detection. The proposed method reconstructs the observation signal into a high-dimensional phase space with fixed-size tuples, and it extracts both the chaotic evolution trend and nonlinear structure from these spatiotemporal sequences by broad enhancement and manifold embedding operation of the Robust Manifold Broad Learning System. After that, the weights in Logistic Regression with two layers can be trained based on the obtained features and their corresponding pulse signal labels. The strategy of the DRBLR model leads to a robust learning paradigm and obtains better generalization performance. Experiments to detect weak pulse signals are conducted using Lorenz and sunspot datasets. Simulation results illustrate that the proposed method can better capture the characteristics of the chaotic interference evolution and effectively detect the weak pulse signal in the chaotic noise background.

Detection of Weak Pulse Signal in Chaotic Noise Based on Improved Brain Emotional Learning Model and PSO-AGA

A model for detecting weak pulse signals in chaotic noise was proposed. Firstly, based on the short-term predictability of chaotic signals, according to Takens’s theorem, the phase space of observed signal was reconstructed. Then, an improved brain emotional learning (BEL) model combined with PSO-AGA was proposed to predict chaotic signals, and the one-step prediction error was obtained. In order to optimize the parameters of the BEL model, an algorithm named PSO-AGA combined with particle swarm optimization and adaptive genetic algorithm was adopted to achieve the balance of global search and local search capabilities. Finally, the hypothesis testing method was used to detect whether there existed the pulse signal from the one-step prediction error. The experiments simulated the Lorenz system and the magnetic storm loop current system. In the Lorenz system, the MAD of BEL-PSO-AGA, BP-NN-PSO-AGA, and Wavelet-NN-PSO-AGA were 0.0022, 0.0142, and 0.0076; the MSE were 8.95 × 1 0 − 6 , 0.00034, and 0.00016; the RMSE were 0.0029, 0.0187, and 0.0128; the running times were 410 s, 792 s, and 721 s; the ACC were 0.999, 0.972, and 0.997; the F1 were 0.984, 0.423, and 0.878. It could be seen that the BEL model had better performance, shorter running time and higher values of the ACC and F1, indicated that the BEL model ran faster and had a better predictive effect. The MAD of BEL-PSO-AGA, BEL-WOA, BEL-AGA, and BEL-PSO were 0.0022, 0.0065, 0.0135, and 0.0071; the MSE were 8.95 × 1 0 − 6 , 0.00013, 0.00029, and 0.00014; the RMSE were 0.0029, 0.0115, 0.0173, and 0.0119; the ACC were 0.999, 0.992, 0.990, and 0.997; the F1 were 0.984, 0.733, 0.451, and 0.878. This indicated that the PSO-AGA also had better performance and higher prediction accuracy. In the magnetic storm loop current system, the experimental results were similar to the Lorenz experiment, which also indicated that the BEL-PSO-AGA model was better. To sum up, the detection results of simulations showed that the proposed model and algorithm could effectively detect weak pulse signals from the chaotic noise.

Detection of Weak Pulse Signal under Chaotic Noise based on Fractional Maximum Correlation Entropy Algorithm

How to improve the detection accuracy of target weak signal is always the difficulty of signal processing. In this paper, based on fractional maximum correlation entropy algorithm and combined with the local linear model, a method for detecting weak pulse signal in chaotic noise background is proposed. Firstly, for the sensitivity of chaotic signal to initial values and short-term predictability, reconstruct the phase space of the observation signal, establish a local linear model, use the fractional maximum correlation entropy algorithm for parameter estimation, and perform a single-step prediction to obtain the prediction error. Then, in order to accurately detect the submerged weak pulse signal, a threshold is given. Finally, the simulation results show that the proposed model in this paper can effectively detect the weak pulse signal under the background of chaotic noise, and it is suitable for signals of different intensities, and the detection speed and accuracy are much better than other models.

Impact of harmonic potential induced nonlinearity on Airy pulse propagation

We numerically investigate the propagation dynamics of truncated Airy pulse in the presence of external harmonic potential. These optical potentials are generated by co-propagating time-dependent strong pump wave that interacts with the weak signal pulse through cross-phase modulation. We demonstrate that Airy pulse trajectory can be manipulated by utilizing a sinusoidal optical potential and soliton shedding is observed in both normal and anomalous group velocity dispersion. The intensity of the emergent soliton depends upon the strength of the potential. Additionally, the potential strength significantly affects the oscillations and temporal position of the peak intensity of the soliton. Further, the impact of the truncation parameter on the Airy pulse accelerating tail and spectrum is explored. Importantly, we have numerically explored the evolution of the temporal chirp of the pulse in various conditions. The temporal chirp is almost zero at the position where the intensity peaks. Also, we show that relative phase of the optical harmonic potential play a vital role in the soliton formation.

Weak Pulse Signal Detection Based on the Broad Learning Method under the Chaotic Background

Weak Pulse Signal Detection Based on the Broad Learning Method under the Chaotic Background

Improving and processing of weak digital pulse signals using a narrow-band noise structure

Improving and processing of weak digital pulse signals using a narrow-band noise structure

DNLS: A Detection Method Based on Normalized Short-Time Fourier Transform-Radon Transform for Low Frequency Sonar Pulse Signal

Under low-frequency background noise environments, due to the characteristics of poor stability and many interference targets of noise, the detection of unknown low-frequency sonar signals faces huge challenge. And sonar pulse signal detection methods based on time domain or frequency domain have the limitation of insufficient detection Signal-to-Noise Ratio (SNR). In order to improve the detection capability of weak sonar pulse signal in low frequency background noise environments, a Detection method based on normalized short-time Fourier transform-Radon transform for Low frequency Sonar pulse signal (DNLS) is proposed, which is a constant false alarm detection method in normalized short-time Fourier transform-Radon transform domain. In DNLS method, after the normalized short-time Fourier transform-Radon transformation, low-frequency noise energy to be dispersed into the entire transformation domain, and the sonar pulse signal energy containing the Linear Frequency Modulation (LFM) component is concentrated at a specific target point in the normalized short-time Fourier transform-Radon transform transformation domain, which can obtain a higher local SNR than the time-domain SNR. Moreover, the specific target point is distinguishable from the background noise, and the impulse signal detection decision is completed by constructing hypothesis test statistics on the target point data. The DNLS method solves the detection problems of low-frequency background such as poor stability, large fluctuations, and more interference. And the method of obtaining the test statistics of the constant false alarm detection, estimating the background noise and calculating the detection threshold is given. Extensive simulation results and actual data processing show that, under the simulation condition, in the minimum detection SNR of LFM, Continuous Wave(CW)-LFM and pulse trains of frequency modulated pulse signals with the same pulse width, compared with the dual-threshold constant false alarm rate energy detection method, the DNLS method is improved by 15dB, 13dB and 4dB, respectively. Under actual data conditions, in the detection of CW-LFM pulse signals with the same pulse width, compared with the double-threshold constant false alarm rate energy detection method, the detection performance of the DNLS method in the case of no ship radiated noise interference and strong radiated noise interference improves by 5dB and 5.5dB, respectively. The data analysis results show that the DNLS method has very good detection performance for LFM, pulse trains of frequency modulated, CW-LFM and other sonar pulse signals at low SNR, and can effectively detect the sonar pulse signals under the background of strong ship radiated noise.