553 results about "Pulse (signal processing)" patented technology

The invention discloses a high-speed multi-photon detection system and method. The system comprises a detector and a signal processing circuit, wherein the detector is composed of a window plated with a photoelectric cathode, a micro-channel plate stack and an anode; a plurality of incident photons are converted into a plurality of photoelectrons by the photoelectric cathode, and the photoelectrons are converted into electron cloud by the micro-channel plate stack; the incident electron cloud is divided into multiple paths by three layers of staggered metal strip electrodes of the anode, and charge collection is carried out to obtain charge short pulses of each layer of electrode; the signal processing circuit converts the charge short pulses transmitted by the three layers of electrodes into digital pulse signals, obtains the centroid coordinates of the electron cloud from the digital pulse signals as the abscissa value, the ordinate value and the verification value of the incident photon position, combines the abscissa value, the ordinate value and the verification value based on the screening condition to obtain the target two-dimensional coordinates, and finally obtains the target two-dimensional coordinates. And transmitting to a terminal for imaging display. According to the invention, a plurality of synchronous photons can be detected, the overall counting rate of the detector is greatly improved, and the detection efficiency is improved.

The invention is applied to the field of mechanical fault diagnosis signal processing, and particularly provides a pulse neural network mechanical fault diagnosis method based on STFT dimension transformation, and the method comprises the steps: collecting a one-dimensional mechanical vibration signal, carrying out the wavelet decomposition, carrying out the wavelet reconstruction of a low-frequency component and a denoised high-frequency component, and carrying out the wavelet reconstruction of the low-frequency component and the denoised high-frequency component; obtaining a denoised one-dimensional vibration signal; performing short-time Fourier transform, and converting the time-frequency two-dimensional matrix into a time-frequency two-dimensional matrix; inputting the time-frequency two-dimensional matrix into an improved HH threshold neuron model, carrying out Poisson sparse coding on the time-frequency two-dimensional matrix, and only carrying out pulse response on signal significant features; constructing a suprathreshold coding convolutional network with residual connection, inputting a sparse coding matrix, training by adopting an unsupervised learning rule based on STDP, and adaptively adjusting a network synaptic weight; and inputting to a trained above-threshold coding convolutional network, and obtaining pulse emission activity of neurons of an output layer through network forward propagation to determine a fault diagnosis result.

The invention discloses a wearable cardiovascular pressure early warning system, which relates to the technical field of wearable medical health monitoring and comprises wearable equipment, and a signal acquisition module, a signal processing module, a posture self-adaptive module and a communication module which are integrated in the wearable equipment. The signal acquisition module comprises a photoelectric volume pulse wave sensor and an inertial measurement unit and is used for acquiring physiological signals and motion data of a user; the signal processing module is used for extracting pulse wave characteristics based on the signals and judging the motion state and the body position state of the user in combination with data of the inertial measurement unit so as to realize pulse-by-pulse blood pressure estimation and cardiovascular pressure trend analysis; the posture self-adaption module identifies user postures through deep learning and dynamically selects a compensation algorithm according to different postures, so that the signal accuracy is improved. According to the invention, continuous, non-invasive and dynamic monitoring of cardiovascular pressure is realized, and long-term and convenient health state monitoring and risk early warning service can be provided for users.

The invention relates to a naked eye 3D binocular image acquisition and real-time processing system based on hardware synchronous triggering, and belongs to the technical field of image processing and three-dimensional display. According to the system, a hardware synchronous triggering mechanism is adopted, a time sequence synchronous control unit is used for sending a synchronous pulse signal to a binocular image sensor, and strict synchronization of left and right viewpoint image acquisition is ensured. The image signal processing unit processes collected original data, the stereo parallax correction module performs epipolar correction, and the sub-pixel interleaving module generates a composite view frame according to grating parameters of the display terminal. The system realizes high-speed data transmission through a double-buffer direct memory access DMA mechanism. The problems of visual tearing and weak stereoscopic impression caused by asynchronous binocular image acquisition in the prior art are solved, nanosecond-level synchronization precision is realized, optical crosstalk is reduced, and smoothness and comfort of stereoscopic display are ensured.

The invention discloses a full-localization ultra-high-speed multi-channel ADC (Analog to Digital Converter) acquisition and processing platform, and relates to the technical field of signal processing. The platform comprises a high-stability clock distribution calibration module, a synchronous acquisition and pulse injection module, a pulse detection and integer deviation module, a coarse-grained translation alignment module, a sub-sampling phase extraction module, a fractional delay interpolation alignment module, a hierarchical storage and flow control module and a high-speed interface synchronous output module. Multi-channel sampling clock synchronization is realized through FPGA dynamic phase adjustment; performing coarse-grained translation by injecting calibration pulses to detect integer deviation, extracting a sub-sampling phase difference, and adopting fractional delay filtering to realize sub-sampling precision alignment; hierarchical storage and intelligent flow control are carried out according to priorities, and synchronous data flow is output through a domestic high-speed interface; through a full-flow domestic chip and a synchronous correction technology, sub-sampling precision alignment and hierarchical flow control output of a multi-channel ADC at an ultrahigh sampling rate are realized.

The invention discloses an unmanned aerial vehicle countering method and countering device for radio detection, and relates to the field of signal processing, and the method comprises the steps: scanning and capturing a transient radio frequency pulse signal through a radio frequency receiving array, carrying out the time-frequency domain conjoint analysis, constructing a signal intensity space distribution matrix, and extracting a parameter set; matching with a protocol feature library, identifying an unmanned aerial vehicle remote control link protocol type, and calculating an unmanned aerial vehicle position and a threat level in combination with a signal time difference of arrival and a frequency difference; generating adaptive interference signal parameters according to the protocol type and the threat level; the method comprises the following steps: generating a directional beam through a two-dimensional phased-array antenna, focusing the position of an unmanned aerial vehicle to transmit an interference signal, monitoring signal intensity change and protocol response delay in real time, calculating a communication suppression ratio, and iteratively optimizing an interference strategy until a suppression threshold is reached. The method has the advantages that efficient and accurate signal capture and interference are realized through multi-channel radio frequency detection, accurate positioning and adaptive interference technologies, and the countering efficiency and adaptability are remarkably improved.

The invention relates to the technical field of signal processing, and provides a time domain waveform reproduction signal smooth processing method, which is used for detecting the fatigue durability of automobile parts in a vehicle vibration acquisition system, and comprises the following steps: S1, obtaining the initial impedance of the automobile parts and multiple frames of to-be-reproduced signals; s2, calculating a first frame first driving signal, and smoothing the first driving signal to form a target driving signal; s3, calculating and generating a first driving signal of a corresponding frame based on the to-be-reproduced signal of each subsequent frame and the updated impedance corresponding to the previous stage in sequence, and forming a target driving signal; and S4, performing stress analysis on the multi-frame response signals, quantifying the damage accumulation process of the automobile part under the simulated working condition, and evaluating the fatigue durability of the automobile part. According to the invention, the generation of response pulses can be avoided, and the signal waveform reproduction precision is improved, so that the accuracy of fatigue durability detection of automobile parts is improved.

The application discloses an improved radar two-dimensional ambiguity resolution method for multi-targets, comprising the following steps: arranging point trail data after radar signal processing according to pulse repetition period from small to large; constructing a reference lookup table for resolving range ambiguity based on the arranged data; constructing a reference lookup table for resolving velocity ambiguity based on the arranged data; traversing all the frequency combinations of radar transmission, selecting N groups from M groups of frequency for multi-target pairing; obtaining a range pairing table based on the reference lookup table for resolving range ambiguity, calculating the standard deviation between rows of the range pairing table, and solving the real range of targets; obtaining a velocity pairing table based on the reference lookup table for resolving velocity ambiguity, calculating the standard deviation between rows of the velocity pairing table, and solving the real velocity of targets; and merging and processing output target data. The application can solve the problem that the traditional one-dimensional set method cannot meet the real-time requirement when the number of targets is large and the ambiguity is large.

An endoscopic imaging system for use in a light deficient environment includes an imaging device having a tube, one or more image sensors, and a lens assembly including at least one optical elements that corresponds to the one or more image sensors. The endoscopic system includes a display for a user to visualize a scene and an image signal processing controller. The endoscopic system includes a light engine having an illumination source generating one or more pulses of electromagnetic radiation and a lumen transmitting one or more pulses of electromagnetic radiation to a distal tip of an endoscope.

The invention discloses a digital electroencephalograph, and belongs to the technical field of brain-computer interface signal processing. An electroencephalogram signal processor of the digital electroencephalograph acquires digital neural signals of a plurality of channels for a target object, wherein the digital neural signals comprise LFP signals and pulse signals; performing feature extraction on the two signals based on a unified time window and a sliding step length, and integrating a time-aligned feature matrix into a first fusion feature tensor; performing dynamic normalization processing on the first fusion feature tensor, wherein the statistical magnitude is updated along with the change of the input data; and n parallel LSTM networks are used to decode the normalized second fusion feature tensor to obtain n decoding results of different dimensions, the n LSTM networks are mutually independent, and each LSTM network has an independent optimizer and an independent parameter. According to the method, multi-modal features can be aligned in time, signal drift is compensated, decoding robustness is improved, and inter-task optimization decoupling and personalized training are achieved through independent parameters and an optimizer.

The application relates to the technical field of signal processing, data representation and classification, and discloses a radar signal spectrum clustering sorting method based on SOM anchor point extraction and graph fusion, which comprises the following steps: configuring a radar signal sorting cluster number and a radar pulse parameter, obtaining a normalized radar pulse data set, taking each normalized radar pulse in the radar pulse data set as a node, and constructing a KNN graph of the radar pulse; extracting an anchor point of the normalized radar pulse data set based on SOM, calculating the similarity between the extracted SOM anchor point and all nodes, obtaining a similarity matrix, and constructing an anchor graph adjacency matrix based on the similarity matrix, namely an adaptive anchor graph; weightedly fusing the KNN graph and the adaptive anchor graph to obtain a fusion graph; and performing spectrum clustering sorting based on the radar signal sorting cluster number and the fusion graph to obtain a sorting result. The application breaks through the limitation that a classical radar sorting clustering algorithm can only utilize distance information and density information, and improves the sorting performance under complex radar pulse distribution conditions.

The invention discloses an indoor navigation positioning precision improving method and system based on a filtering algorithm, and relates to the technical field of signal processing. The method comprises the following steps: suppressing signal fluctuation and multipath interference by adopting a Bluetooth positioning technology in combination with a segmented power law regression model and Kalman filtering; ultrasonic-assisted positioning is introduced, the distance is calculated through the time difference between pulses and Bluetooth, and the anti-interference capability is improved in cooperation with temperature correction and spectral analysis; multi-mode dynamic fusion is carried out, when shielding is little, Bluetooth positioning is corrected through high-precision ultrasonic waves, when shielding is serious, Bluetooth data is smoothed through moving average, and positioning coordinates are optimized in combination with a least square method; a base station and a reference object are marked through a vector map, the position of a terminal is dynamically displayed, and positioning reliability is visually presented through an error semitransparent circle; a positioning base station array, a mobile terminal and a rear-end processing module are integrated, and low-power-consumption multi-mode fusion positioning is achieved. The method reduces the positioning error in a complex indoor environment, and is suitable for scenes such as personnel / equipment real-time tracking.

The invention discloses an analog signal pulse encoding device based on event driving and an analog signal processing method, and the device comprises a signal conditioning module which comprises at least one conditioning unit, and the conditioning unit is used for receiving an analog signal, carrying out the front-end analog conditioning of the signal, and outputting an analog conditioning signal; the threshold comparison module is connected with the signal conditioning module and is used for carrying out threshold detection on the analog conditioning signal according to a set threshold and then outputting a threshold comparison signal; the event triggering module is connected with the threshold comparison module and is used for triggering a pulse event signal corresponding to the analog conditioning signal according to the threshold comparison signal; and the pulse coding module is connected with the event triggering module and is used for converting the pulse event signal into a pulse coding signal by adopting a pulse coding mode. According to the invention, by introducing the threshold comparison module and the event trigger module at the front end of the device, invalid sampling can be effectively avoided, a large amount of redundant data can be reduced, and power consumption, communication and storage pressure and burden can be reduced.

The invention relates to a counting system for online detection of electronic special gas granularity. The counting system comprises an optical detection module, a gas path control module, a signal processing module, a man-machine interaction module and a data output module, the optical detection module is used for enabling particulate matters in the electronic special gas to be detected to generate scattered light signals and converting the light signals into electric pulse signals; the gas path control module is in fluid communication with the detection area of the optical detection module and is used for accurately controlling the flow, pressure and flow velocity of the electronic special gas to be detected flowing through the detection area and ensuring that the gas flow is in a laminar flow state; the signal processing module is electrically connected with the optical detection module and the gas path control module and is used for receiving and processing the electric pulse signals, and screening, counting and particle size conversion are carried out on the pulse signals through a preset algorithm so as to obtain the quantity and particle size distribution information of the particulate matters; and meanwhile, a control instruction is sent to the gas path control module.

The invention relates to the technical field of equipment lubricating oil monitoring, in particular to a wear debris electrostatic monitoring method and system based on combination of characteristic mode decomposition and time-frequency images, and an electrostatic sensor monitoring system comprises a sensor shell, an annular copper probe, a polyether-ether-ketone pipeline, a shielding cover, a signal processing circuit and other modules. An insulating pipe in the sensor is a polyether-ether-ketone pipeline, lubricating oil passes through the inside of the polyether-ether-ketone pipeline, and a red copper probe of the sensor is attached to the outer surface of the polyether-ether-ketone pipeline. The method comprises the following steps of: firstly, constructing a signal enhancement model based on characteristic modal decomposition and a kurtosis measurement criterion, and screening out a key modal component with high sparsity for reconstruction by calculating a Gini coefficient of each modal component; further enhancing the signal pulse of the wear debris through modal component optimization reconstruction and a sparse representation model; and finally, identifying the wear debris impact signal based on the continuous wavelet transform time-frequency image to realize real-time monitoring of the wear debris.

The invention discloses a GIS partial discharge fault positioning method based on multi-feature fusion and kernel density estimation optimization, and the method comprises the following steps: collecting a partial discharge original pulse signal, carrying out the signal processing, and outputting a first processing signal; performing adaptive robust baseline determination on the first processing signal, detecting a wave head position based on multi-feature fusion and a dynamic threshold voting mechanism, and outputting a wave head arrival time; carrying out time synchronization matching on the wave head arrival time, and calculating and outputting a preliminary positioning result based on a time difference of arrival method; and accumulating a plurality of preliminary positioning results, performing optimization by adopting a kernel density estimation method, and outputting a final partial discharge fault position. According to the method, impulse noise and white noise are effectively suppressed, stable signals are provided for subsequent processing, the detection precision of the wave head arrival time is remarkably improved, the problem that false detection and missing detection are caused by the fact that a traditional fixed threshold value or a single feature is prone to noise interference is solved, the random error of single-time positioning is greatly compressed to be within 0.07 m from 0.33 m on average, and the overall positioning precision is improved by 80%.

The invention discloses a brain-computer interface-based closed-loop transcranial magnetic stimulation treatment system and method, and the system comprises an electroencephalogram monitoring module which is used for collecting an electroencephalogram signal of a subject in real time; the transcranial magnetic stimulation module is used for transmitting pulse stimulation to a brain target spot of a subject; the control module is in communication connection with the electroencephalogram monitoring module and the transcranial magnetic stimulation module, and the control module is configured to receive the electroencephalogram signals output by the electroencephalogram monitoring module, preprocess the electroencephalogram signals by adopting a signal processing algorithm to remove electromagnetic interference, and send the preprocessed electroencephalogram signals to the transcranial magnetic stimulation module; the signal processing algorithm comprises but is not limited to fast continuous wavelet transform (FCWT) and fast independent component analysis; according to the method, a closed-loop monitoring mechanism is adopted, electroencephalogram oscillation is recognized in real time, stimulation is dynamically triggered, the stimulation opportunity is accurately matched with the brain excitation state, and the treatment pertinence is improved; the signals are preprocessed through FCWT and an algorithm, electromagnetic interference and artifacts are effectively removed, and the accuracy of electroencephalogram oscillation feature extraction is guaranteed.

The application provides a wireless charging device and a foreign matter detection method, device, circuit and equipment thereof. The method comprises the following steps: applying a damping oscillation signal processing circuit to process a damping oscillation signal of a wireless power transmitter to be detected, so as to obtain a corresponding pulse signal; determining two target amplitudes of the damping oscillation signal and a target cycle number between the two target amplitudes according to the pulse signal; determining a current oscillation frequency and a current quality factor of the wireless power transmitter to be detected based on the two target amplitudes and the target cycle number; and determining whether there is foreign matter in the working range of the wireless power transmitter to be detected based on the current oscillation frequency, the current quality factor, a preset standard quality factor and a preset standard oscillation frequency. The application can output a pulse signal accurately reflecting the damping oscillation signal of the wireless power transmitter, so as to calculate the current quality factor and the current oscillation frequency of the wireless power transmitter based on the pulse signal, and realize more accurate foreign matter detection.

The invention relates to the field of voice signal processing, in particular to a multi-language interactive learning system based on voice recognition, which is characterized in that sound waves and mouth shape images are synchronously acquired and discretized by the system, and cross-modal coding is formed after alignment; secondly, the code is injected into a micro-ring photon reserve network through phase modulation to unfold time sequence characteristics, the code is mapped into a quaternion graph to be embedded, and segment boundaries are extracted through a diffusion-pulse coupling method; then, according to a fixed field sequence, encapsulating the quaternion graph embedding and segmentation data into an object mark prompt, inputting the object mark prompt into a low-rank adaptive language model, and generating semantic segmentation data and text transcription; and finally, the adaptive learning module implements sparse gradient updating on the low-rank weight and pulse network by using an integer fractal hash exclusive-or difference mask, and adopts support-query element learning for synchronous iteration after user clarification. According to the system, low-power-consumption, high-precision and second-level accent self-adaptive multi-language voice interaction is realized on the end side.

The invention discloses a phased array radar digital beam forming system, and belongs to the technical field of radar signal processing, and the system comprises a radar central processing and dynamic scheduling subsystem which is used for carrying out the real-time dynamic scheduling control of all subsystems according to external environment parameters; the time sequence synchronous control subsystem is used for receiving a scheduling instruction of the central processing unit and generating a whole-system reference clock and a key time sequence signal; the data transmission and preprocessing subsystem is used for transmitting and preprocessing the data; the long and short pulse cooperative processing and target detection subsystem is used for receiving the preprocessed baseband data stream and executing pulse analysis and target extraction; and the target information extraction and real-time display control interface is used for uploading the processed data in real time and displaying target related information in real time. Through physical complementation of the long and short pulses and extension of the detection distance, full-distance continuous high-precision detection is realized, and through distance-direction dynamic fusion of the long and short pulse data, a distance fault of a traditional scheme is eliminated.

The invention discloses a machine tool cutter service life detection system, which belongs to the technical field of machine tool machining cutter detection, and comprises a magnetic sensor for generating a pulse signal when a tool rest completes a workpiece machining cycle; the signal processing module receives the pulse signal and executes a counting algorithm; the tool wear detection module comprises an optical sensor group for acquiring cutting surface images, a vibration sensor for acquiring vibration signals of a tool rest main shaft, a current sensor for acquiring current fluctuation of a tool feeding motor and an acoustic emission sensor for acquiring acoustic emission energy of a cutting frequency band; the analysis early warning module is used for training a dynamic threshold model based on the feature vector and outputting a wear level; the cutter life prediction module predicts the remaining service life of the cutter; and the execution module outputs a machine tool machining signal according to the tool wear grade and the remaining service life of the tool. According to the invention, various different types of sensors are integrated at the same time for comprehensive wear detection; the problems of single monitoring dimension and low precision in the prior art are solved.

The invention provides signal coding equipment, an imaging system and an imaging method. The signal coding equipment comprises an array waveguide grating, a coding optical fiber, a delay optical fiber and an optical splitter, the array waveguide grating is configured to convert an initial signal emitted by the light source into multiple paths of target signals; the optical splitter is configured to combine multiple paths of target signals and then emit the combined signals; a plurality of paths of coding optical fibers and a plurality of paths of delay optical fibers with different lengths are arranged behind the array waveguide grating, and each path of delay optical fiber is connected to the coding optical fiber of the corresponding coding sequence; the delay optical fiber is configured to delay a transmitted target signal, and the coding optical fiber is configured to perform pulse coding on the transmitted target signal. According to the invention, the original pulse signal is coded by using the sequence code with good orthogonality, so that the signal processing accuracy is improved. And the delay optical fibers are grouped, so that the corresponding channels in each group of channels can be simultaneously transmitted, the signal transmitting time is shortened, the signal processing efficiency is improved, and the point acquisition rate can be improved while the fuzzy distance is expanded.

The invention discloses a fracturing pump multi-cylinder vibration signal processing method and device, equipment, a medium and a product. A vibration data sequence and a key phase pulse signal are obtained, and the vibration data sequence is vibration data collected by a vibration sensor installed between adjacent cylinder bodies of a fracturing pump; the key-phase pulse signals are key-phase pulse signals collected by a phase sensor installed at the crankshaft part of the fracturing pump, then carrying out decorrelation on the vibration data sequence to eliminate the correlation of the vibration data sequence, then carrying out independent analysis on the vibration data sequence after decorrelation, outputting a plurality of vibration data sequences to be matched, and outputting the vibration data sequences to be matched; and finally, based on the key phase pulse signal, matching the plurality of to-be-matched vibration data sequences with the adjacent cylinders to obtain a target vibration data sequence corresponding to each cylinder, so that vibration data with stronger feature information can be extracted while the use amount of sensors is remarkably reduced and the cost and complexity are reduced, and the accuracy of the vibration data is improved. Therefore, the accuracy and timeliness of fault diagnosis of the fracturing pump are effectively improved.

The invention relates to the technical field of signal processing, and discloses a time slot control method and system for an inter-satellite link time division communication system, and the method comprises the steps: carrying out the clock domain crossing synchronization and jitter elimination processing of a pulse per second signal inputted externally, and detecting the validity of the processed pulse per second signal; extracting a time error between a local clock and an external clock based on the second pulse signal after validity detection; performing continuous health detection on the time error to generate a health state indication; performing second-order filtering processing on error information by referring to the health state indication and the time error, taking a processing result as an adjustment amount of a frequency control word of an NCO counter, and driving the NCO counter to generate a time reference; and detecting whether an external pulse per second signal is subjected to slip adjustment or not, and distributing a time slot control signal by using the time reference. Accurate distribution of time information is achieved, misreading of externally input time information is avoided, and the adaptive capacity of the system under different working conditions is improved.

The application discloses a gas extraction water ring vacuum pump fouling degree online detection system and method, relates to the technical field of vacuum pump fouling degree detection, and comprises a sound signal acquisition module, an excitation control module, a parameter sensing module, a signal processing module, a feature compensation module, a fouling inversion module and a model calibration module; the sound signal acquisition module is arranged on the outer wall of the pump body and is used for acquiring structural vibration signals generated in the operation process and outputting original vibration data; the excitation control module is connected with a piezoelectric excitation device and receives the operation state feedback of the sound signal acquisition module, is used for triggering the piezoelectric excitation device to apply high-frequency pulse signals to the pump shell when the suction negative pressure fluctuation is stable and continuously meets the steady-state condition, and synchronously starts the sound signal acquisition module to collect response signals; and the parameter sensing module is used for monitoring the cooling water inlet / outlet temperature and motor current waveform and outputting environmental and operation parameters.

The invention discloses an ultrasonic metering method and a chip thereof. Relates to the field of ultrasonic measurement, and solves the problem that the power consumption is synchronously increased while the measurement precision of an ultrasonic metering chip is improved. The ultrasonic metering method provided by the invention comprises the following steps: generating pulse signals with preset frequency and quantity; transmitting the pulse signal as a first transmitting wave signal from a transmitting end, and meanwhile, taking the first transmitting wave signal as an initial signal; receiving the echo signal from the receiving end, performing signal processing on the echo signal to obtain a filtering signal, taking the filtering signal as a second transmitting wave signal, sending the second transmitting wave signal again from the transmitting end until a preset number of times, and taking the filtering signal with the preset number of times as a termination signal; and obtaining a metering result based on the initial signal and the termination signal. According to the ultrasonic metering method disclosed by the invention, the power consumption can be reduced while the precision of the ultrasonic metering chip is improved.

The application discloses a photoacoustic spectrum signal detection system and a detection method. The system comprises a signal acquisition device and a detection signal processing terminal. The signal acquisition device comprises an ultraviolet pulse laser, a first plano-convex lens, a second plano-convex lens, a focusing objective lens, a refractive prism, a helium-neon laser, an electric displacement platform, a polarization modulation assembly, a light splitting assembly and a differential detector. The photoacoustic spectrum signal detection system uses the specific absorption of cell nuclei to ultraviolet light, obtains a differential detection signal through the differential detector and generates an analysis spectrum. The light sensing assembly collects a light sensing signal of the sample and generates a microscopic image. The detection system can realize photoacoustic spectrum analysis of a cell nucleus level micro-sized absorber, thereby obtaining a high-resolution analysis spectrum and a microscopic image reflecting the physical properties inside the cell nuclei. The label-free and non-staining photoacoustic spectrum signal detection does not need staining and can save detection time, and the accuracy of cell detection on biological samples is improved.

The present invention belongs to the field of radar signal processing and analysis technology and discloses a method for estimating the number of code elements within a pulse of a phase-coded radar signal. For an input baseband digital signal, the instantaneous frequency is calculated and processed, and the number of code elements corresponding to the peak amplitude correlation value is searched to obtain the optimal number of code elements. The method primarily includes calculating the unfolded phase of the input signal and filtering it using a differential filter to obtain the instantaneous frequency; removing average frequency deviation, edges, outliers, and low-value processing, creating corresponding reference data, calculating amplitude correlation values, and searching for the number of code elements corresponding to the maximum correlation value. This method is not limited to the type of phase-coded signal or the frequency deviation of the pulse and can also adapt to situations where pulse edge estimation is inaccurate. The instantaneous frequency can be obtained by filtering using a differential filter or by instantaneous phase differential. The subsequent process remains the same, and the number of code elements can still be estimated. The calculation speed is fast and engineering implementation is convenient.

The invention provides a mental stress analysis method and equipment based on pulse waves. The method is applied to physiological signal processing. The method comprises the following steps: acquiring a pulse wave signal of a target object, wherein the pulse wave signal is a signal acquired by pulse wave acquisition equipment; extracting pulse rate change information from the pulse wave signal by using a window function with the length of 0, so as to obtain a forward pulse rate; reversely correcting a problem pulse rate in the forward pulse rate by adopting a path growth mode to obtain a target pulse rate; performing forward heartbeat point search on the target pulse rate, and performing reverse correction on the heartbeat point to obtain a heartbeat interval; calculating a heart rate variability parameter according to the heartbeat interval; and calculating the heart rate variability parameter by using a pre-constructed mental stress model to obtain a mental stress parameter. According to the invention, mental stress monitoring with low burden, high reliability and high accuracy is realized.