53 results about "Spectral amplitude" patented technology

The invention discloses a bridge health monitoring method and system based on artificial intelligence, and relates to the technical field of bridge monitoring, and the method comprises the steps: building a bridge finite element physical model based on a bridge geometric model; and performing modal analysis and strain energy analysis based on a finite element physical model, determining key nodes based on an analysis result to generate sensor candidate nodes, and optimizing the sensor layout by using a genetic algorithm. According to the method, on the basis of bridge design parameters, a finite element analysis model is used for building a physical model for a bridge, sensitive areas in the bridge are converted into key monitoring nodes according to modal analysis and strain energy analysis, and sensor layout is optimized according to the key monitoring nodes in combination with a genetic algorithm, so that high-quality data acquisition is achieved; the monitoring efficiency is maximized, the cost is reduced, and dynamic damage characteristic indexes in the bridge are comprehensively extracted by calculating parameters such as the frequency spectrum amplitude, the damping ratio and the strain energy change.

The invention discloses a self-adaptive threshold SAMP reconstruction method for a power quality disturbance signal. According to the method, a compression observation value is obtained by constructing a random Gaussian observation matrix, and sparse representation is carried out on an original signal by using discrete Fourier transform. In the iterative reconstruction process, the spectrum amplitude difference is introduced for the first time to serve as an adaptive termination basis, and automatic adaptation of different noise levels and different disturbance characteristics is achieved in combination with a dynamic threshold update function. According to the method, the problems of traditional SAMP sparseness overestimation and redundant iteration are effectively avoided, and the calculation load is remarkably reduced. Compared with an OMP method, an original SAMP method and the like, the method has the advantages that the number of iterations can be reduced by 30%-60%, the reconstruction signal-to-noise ratio is increased by 2-5 dB, the root-mean-square error is reduced by 10%-25%, higher robustness and real-time performance are achieved in power quality disturbance signal reconstruction, and the method is quite suitable for scenes such as compressed sampling, edge calculation and high-speed signal reconstruction in a power quality monitoring system.

The invention belongs to the technical field of bearing fault detection, and particularly relates to a bearing fault feature rapid extraction method. According to the method, the optimal model order can be adaptively selected by utilizing autoregression model decomposition and combining RKSR optimization indexes, effective separation of steady-state signals and residual signals is ensured, so that fault features are easier to detect, the risk of false alarm and missing alarm is reduced, and the fault detection accuracy is improved by stripping the steady-state part for multiple times through a self-nested iteration residual strategy. According to the method, weak fault features hidden in noise at the initial stage are gradually accumulated and displayed, so that early faults are diagnosed in time, random pulses and other interference signals are effectively inhibited by adopting an improved spectrum amplitude modulation algorithm, the whole fault extraction process can still be stably operated under complex working conditions and high background noise conditions, and the fault extraction efficiency is improved. In combination with a fast spectrum kurtosis processing method, key spectrum features can be extracted from conditioned signals in a short time, and the requirements of real-time monitoring and fault early warning are met.

The invention discloses a self-adaptive broadband measurement method and system suitable for a power distribution automation terminal, and the method comprises the steps: carrying out windowing FFT calculation, determining a coarse frequency based on a frequency spectrum amplitude, carrying out the judgment of a dense spectrum, carrying out windowing ZoomFFT calculation under a dense spectrum condition, carrying out the multi-spectral-line interpolation calculation, and carrying out the calculation of the multi-spectral-line interpolation. And finally, extracting electrical quantity broadband frequency components needing to be measured and corresponding amplitudes and phases thereof through frequency spectrum sorting. According to the method, the frequency resolution is adaptively changed for calculation according to the spectral characteristics of the electrical quantity, the dense harmonic and inter-harmonic detection is realized, the operation cost is lower, and the engineering use value is good.

The invention relates to the technical field of photoacoustic measurement, and particularly provides measuring equipment and a frequency estimation method and a denoising method of equipment noise therein, the frequency estimation method comprises the following steps: controlling pump light and probe light to irradiate a first sample to be measured, the pump light generating ultrasonic waves on the surface of the first sample to be measured, the detection light is reflected by the surface of the first to-be-detected sample to form first detection signal light; acquiring a first photoacoustic time domain signal formed by the first detection signal light; removing a non-noise signal and a random noise signal in the first photoacoustic time domain signal to obtain a first time domain noise signal; performing time-frequency transformation on the first time-domain noise signal to obtain a first noise spectrum; and determining the frequency of the equipment noise according to the spectrum amplitude of the first noise spectrum. Thus, the device noise in the photoacoustic signal can be removed in a targeted manner according to the frequency of the device noise subsequently, and compared with a traditional overall noise removal manner, the signal-to-noise ratio and the measurement sensitivity can be improved.

The subject matter of the invention relates to a method for the automatic technical diagnosis of rotating machines, including detection of faults in rotating machines, in particular vibration measurements of rotating machines by the automatic detection of changes in the signals of machine vibration. The method consists in that monitoring and diagnosis are performed in terms of identifying both the assemblies or parts of an object of the rotating machine subjected to the diagnosis, in such a way that vibration data are recorded in the form of a vibration signal from at least one vibration sensor (2) mounted on the housing of the mechanical elements of the rotating machine (1), wherein each subsequent vibration signal is recorded at the same length and at the same sampling frequency. Then, collected vibration signals are processed in a vibration data acquisition unit (3) equipped with a reductive-redundant mechanism (4) by means of which the vibration signal is modified by calculating the values of spectral components in the domain of frequency or orders and the values are segmented relative to subsequent tested spectral resolutions on the basis of current scale of class intervals. Then, an averaged spectrum is calculated and added to the state matrix and a statistical measure of the comparison of spectral amplitudes is calculated for individual class intervals at the standard score measure and the procedure is repeated for each tested spectral resolution in the range from the value equal to the inverse of the vibration signal length to half the sampling frequency. Finally, the results of the vibration growth index are saved, then are sorted from the highest to the lowest value thus allowing the potential occurrence of a fault to be determined in terms of identifying both a specific assembly or part of the rotating machine (1).

The invention provides an infrared image super-resolution method based on a conditional diffusion model, and belongs to the technical field of infrared image super-resolution reconstruction. The method comprises the following steps: adding noise to a high-resolution infrared image to construct a diffusion process; splicing the noisy image, the low-resolution infrared image and the visible light image in a channel dimension, and inputting the spliced image into a U-Net encoder to extract multi-scale fusion features; the decoder recovers the spatial resolution through layer-by-layer up-sampling in combination with jump connection, and meanwhile, structural features of a low-resolution image and texture features of a visible light image are introduced into each layer to carry out spatial condition modulation, so that cross-modal stable guidance is realized; and constructing a joint objective function including denoising loss, frequency domain phase consistency loss and spectrum amplitude constraint loss, and optimizing network parameters through back propagation. According to the method, complementary information of infrared and visible light images can be fully fused, and the problems of insufficient detail recovery and artifact generation of an existing method are effectively solved.

The invention discloses a fabric texture fidelity rendering method and system based on a scanned image and a target color number, and solves the technical problems of poor color perception consistency and texture detail loss. The method comprises the steps of preprocessing a standardized input image through illumination compensation, performing double-space color mapping in an LAB color space, partitioning the image by adopting K-means clustering according to texture features of a gray-level co-occurrence matrix, establishing a color mapping function containing global mapping transformation and local adaptive adjustment, and adaptively determining a fusion coefficient according to regional variance; decomposing the image into a base layer and a detail layer by adopting guide filtering, and performing spectrum constraint on the detail layer to ensure that the spectrum amplitude is consistent with the original; extracting material parameters such as a normal map, a roughness map and a metallity map; according to the method, fabric texture details are completely reserved while color perception consistency is guaranteed, rendering reality is improved, batch processing of multiple groups of target color numbers is supported, and the method is suitable for application scenes such as costume design, e-commerce display and virtual fitting.

A construction method of a deep learning-based pipeline leakage detection and denoising model: performing signal modulation on clean signals and noise signals in different proportions to obtain noisy signals; performing short-time Fourier transform (STFT) on the clean signals to extract spectral amplitudes of the clean signals, and using absolute values of the spectral amplitudes of the clean signals as target samples; performing STFT on the noisy signals to obtain spectral amplitudes of the noisy signals, calculating absolute values of the spectral amplitudes of the noisy signals, correcting the absolute values of the spectral amplitudes of the noisy signals, and using the corrected spectral amplitudes as training samples; normalizing amplitudes of the training samples and the target samples, and then inputting the amplitudes into a denoising convolutional encoding-decoding neural network for training; and optimizing the trained denoising convolutional encoding-decoding neural network to obtain a pipeline leakage detection and denoising model.

A measurement system for use in optical metrology, the measurement system which includes a control system configured and operable to carry out the following: (i) receive raw measured data generated by a measurement unit that is configured and operable for performing normal-incidence spectral interferometric measurements on a sample and generating the raw measured data indicative of spectral interferometric signals measured on the sample for a number of different optical path differences (OPDs) between sample and reference arms using infrared wavelengths; (ii) extract, from the raw measured data, a portion of spectral interferometric signals describing variation of signal intensity with a change of an optical path difference OPD during interferometric measurements, said portion of the spectral interferometric signals being independent of interferometric signals returned from a bottom portion of the sample in response to said illuminating electromagnetic field; and (iii) directly determine, from the extracted portion of the spectral interferometric signals, both spectral amplitude and phase of reflection of the illuminating electromagnetic field from the top portion of the sample, thereby enabling to determine a measured spectral signature characterizing the top portion of the sample.

A method, decoder, and program code for controlling a concealment method for a lost audio frame is provided. A first audio frame and a second audio frame of the received audio signal are decoded to obtain modified discrete cosine transform (MDCT) coefficients. Values of a first spectral shape based upon the MDCT coefficients decoded from the first audio frame decoded and values of a second spectral shape based upon MDCT coefficients decoded from the second audio frame decoded are determined, the spectral shapes each comprising a number of sub-bands. The values of the spectral shapes and frame energies of the first audio frame and second audio frame are transformed into representations of FFT based spectral analyses. A transient condition is detected based on the representations of the FFTs. Responsive to detecting the transient condition, the concealment method is modified by selectively adjusting a spectrum magnitude of a substitution frame spectrum.

The invention belongs to the technical field of distributed optical fiber sensing, and relates to an anti-distortion distributed optical fiber sensing method and system based on array phase spectrum demodulation, an ultra-weak reflection optical fiber Bragg grating array is used as a sensing optical fiber, a series of reflection peaks with the signal-to-noise ratio higher than that of RBS are generated, a reflection peak sequence is formed, and the beat frequency signal spectrum amplitude is increased. A discrete beat frequency signal with frequency domain distortion output by an OFDR sensing system is converted to a frequency domain through Fourier transform of a symmetric window function to obtain a corresponding discrete frequency spectrum, and characteristic parameters such as amplitude and phase of a reflection peak sequence in the frequency spectrum are tracked and extracted; and then frequency correction factors of the reflection peak sequence in all measurement periods are calculated by using an amplitude interpolation correction method to obtain a corrected accurate array phase spectrum, and phase difference and strain calculation are performed to realize multi-point quasi-distributed strain demodulation for suppressing frequency domain distortion such as Doppler frequency shift and the like. The frequency resolution limitation caused by the fence effect is broken, and the fidelity of the frequency domain distortion signal is recovered.

The invention provides a real-time speech enhancement method and system based on dual-stage spectral subtraction and dual-mask fusion, and relates to the technical field of speech signal processing, and the method comprises the steps: respectively carrying out the framing, windowing and short-time Fourier transform of a left channel mixed signal and a right channel noise reference signal, obtaining a complex frequency spectrum and an amplitude spectrum of the left channel signal and an amplitude spectrum of the right channel noise reference signal; and performing noise estimation by adopting a first noise multiplication factor based on the amplitude spectrum of the right channel noise reference signal to obtain a noise estimation spectrum, and performing constraint spectrum subtraction on the amplitude spectrum of the left channel signal to obtain voice amplitude estimation of a first stage. According to the method, effective suppression of TTS noise and real-time speech enhancement are realized through framing windowing and frequency domain conversion in combination with over-estimation spectrum subtraction and double-mask fusion through two-stage gain application and time domain reconstruction.

The application discloses a kind of vehicle diesel engine piston ring wear state monitoring method, storage medium and device, it is related to diesel engine state monitoring field, the method includes defining the measured point sensitivity characteristic value for representing the attenuation amount of measured point energy relative to acoustic emission source energy, and determining multiple acoustic emission source positions and measured point positions for installing acoustic emission sensor on cylinder cover;Drive acoustic emission sensor at acoustic emission source to produce excitation, the measured point sensitivity characteristic value between each measured point and acoustic emission source is calculated, determine the measured point for carrying out fault identification among all measured points, as detection measured point;Acoustic emission signal of detection measured point is obtained when piston is located in set position during diesel engine operation, the PSD spectral amplitude of acoustic emission signal is calculated, and compared with the fault threshold under different fault states of piston ring, realize piston ring fault determination.The application can realize the accuracy and effectiveness of piston ring fault diagnosis.

The present invention provides an adaptive background noise detection method, comprising: S1, obtaining a sound signal within a background noise detection interval; S2, performing a fast Fourier transform on each frame of the sound signal to estimate the spectral amplitude of the sound signal; S3, performing a steady-state statistical analysis on the spectral amplitude of the sound signal to calculate the change in the spectral amplitude of the sound signal; S4, performing a dynamic statistical analysis on the spectral amplitude of the sound signal to calculate the change in the spectral variance of the spectral amplitude of the sound signal; S5, determining whether the sound signal is background noise according to the change in the spectral amplitude of the sound signal and the change in the spectral variance of the spectral amplitude of the sound signal. The present invention discriminates whether it is background noise through the spectral signal characteristics of the sound signal, can make timely adjustments according to the changes in the detected environmental noise, and has a high detection accuracy.

The invention discloses a screen shooting image moire quantification method and device and a storage medium, which are used for improving the compensation precision of a display screen. Acquiring a sub-pixel unit image of the display screen to be tested; performing brightness compensation processing on the sub-pixel unit image to generate an expected brightness compensation image; generating a compensation graph frequency spectrum amplitude image according to the brightness compensation image; generating a stripe frequency band sensing image according to the visual distance and the pixel pitch corresponding to the target color channel; carrying out region division on the frequency spectrum amplitude image of the compensation graph; standard deviations of the elliptical region and the plurality of elliptical ring regions are calculated, and a region standard deviation set is generated; filling a blank image with the standard deviation in the regional standard deviation set to generate a first elliptical ring standard deviation image; performing frequency domain filtering on the first elliptical ring standard deviation image by using the stripe frequency band sensing image to generate a first frequency domain filtering image; and generating a first moire quantization value corresponding to the brightness compensation image according to the compensation image frequency spectrum amplitude image and the first frequency domain filtering image.

The invention relates to the technical field of intelligent sensors, in particular to an insulator defect evaluation method based on vibration acoustics, and the method comprises the steps: analyzing the amplitude difference between each non-backbone component and an acoustic signal, and the discrete degree of all amplitudes in each non-backbone component, determining the noise influence degree according to the number difference between all the non-backbone components and all the backbone components; determining a signal characteristic value based on the proportion of the average frequency spectrum amplitude of each backbone component in the average frequency spectrum amplitude of the acoustic signal and the random fluctuation degree of all the amplitudes in each backbone component, and determining the disturbance degree in combination with the sound influence degree; and based on the confusion degree and the disturbance degree of the acoustic signal, denoising the acoustic signal by adopting a wavelet function so as to evaluate the defect of the insulator. According to the invention, through adaptive denoising, environmental noise interference is suppressed, and the accuracy and reliability of insulator defect evaluation are improved.

The invention discloses a frequency estimation method for judging an interpolation direction based on a phase difference, which belongs to the technical field of radar signal processing and comprises the following steps of: performing FFT (Fast Fourier Transform) on an original signal of an LFMCW (Linear Frequency Modulated Continuous Wave) radar transmitting signal, finding out positions of a maximum value and a second maximum value corresponding to a frequency spectrum amplitude, solving a phase at a spectral line, comparing the phase difference and judging the interpolation direction. According to the method, the Rife algorithm is improved, interpolation direction judgment is carried out through the phase difference between the maximum spectral line and the second maximum spectral lines adjacent to the two sides, better anti-noise performance is achieved, relatively high stability is achieved, and the problem of interpolation direction misjudgment is avoided.

The invention discloses a multifunctional audio processing method, device and system, and relates to the technical field of audio processing, and the method comprises the steps: calculating spectrum amplitude data from a spectrogram of an audio signal; selecting an audio processing function needing to be executed, and outputting control signals and instructions required by each module for realizing the audio processing function; inputting the audio signal or the spectrum amplitude data into a neural network accelerator, and transmitting the weight and bias parameters of a pre-trained neural network model corresponding to the audio processing function to a multiply-accumulate array and each storage module in the neural network accelerator; and decomposing, equivalently and optimizing various operators in the neural network model according to the instruction, so that the various operators are converted into calculations which can be executed by the neural network accelerator, and then the various executable operators are utilized to calculate the audio signal or the spectrum amplitude data according to the weight and the bias parameter to obtain a processing result of the audio processing function. The audio processing efficiency can be improved.

The invention discloses a gas leakage detection method and system based on laser speckle imaging, and the method comprises the steps: irradiating the outer wall surface of a to-be-monitored region with laser beam expansion to form laser speckles, and continuously collecting a plurality of monitoring speckle images of the to-be-monitored region; segmenting the monitored speckle image and the corresponding original speckle image without leakage into a plurality of sub-windows, and calculating the frequency spectrum amplitude and the frequency spectrum phase of each sub-window; calculating a correlation coefficient between the two sub-windows according to the spectrum amplitudes and the spectrum phases of the sub-windows corresponding to the original speckle image and the monitoring speckle image; marking the sub-windows in the monitoring speckle image corresponding to all the correlation coefficients smaller than a preset threshold value as gas leakage coarse positioning areas; and for each pixel point in the leakage coarse positioning area, calculating a pixel-level imaging operator of the pixel point, and taking the pixel point corresponding to the maximum pixel-level imaging operator as a gas leakage point.

The invention discloses a joint inversion three-dimensional quality factor method, which comprises the following steps of: acquiring average attenuation travel time through an initial three-dimensional quality factor (Q value) and an average attenuation travel time formula, and acquiring a theoretical frequency spectrum amplitude at the frequency by combining a plurality of initial values including corner frequency, field effect, low-frequency amplitude and frequency and an amplitude formula; converting the displacement frequency spectrum amplitude in the frequency domain into an observation frequency spectrum amplitude in a natural logarithm domain, and obtaining a residual vector formula in combination with a theoretical frequency spectrum amplitude; a formula obtained after meshing of the seismic wave three-dimensional propagation speed and the initial Q value in the average attenuation travel time formula is substituted into a residual vector formula, smooth constraint and damping parameters are added to obtain a new residual vector formula, and the new residual vector formula is solved to obtain a value of a parameter disturbance quantity; superposing the values to the plurality of initial values to obtain a plurality of new initial values of the next round of iteration; and substituting the initial three-dimensional Q value back to a residual vector formula to obtain a residual vector, and taking the new initial three-dimensional Q value as a target three-dimensional Q value when a difference value between the residual vector and the amplitude meets a condition.

The invention belongs to the technical field of carbon dioxide concentration detection, and particularly relates to a multi-frequency modulation anti-interference carbon dioxide concentration detection method based on a photoacoustic effect. Comprising the following steps: S1, enabling infrared light with a certain wavelength to pass through CO2 gas to be detected; s2, periodically modulating the infrared heat source, and flashing according to pulses with different frequencies in the modulation stage; and S3, collecting a sound wave signal through a high-sensitivity MIC, extracting an MIC frequency spectrum amplitude characteristic value, and calculating the CO2 concentration according to a fitting formula of the calibration curve. A traditional fixed frequency modulation mode is broken through, and environment vibration noise is effectively separated through multi-frequency combination.

The application discloses a kind of traceable pressure sensor dynamic response calibration method based on absorption spectrum reference pressure input, in shock tube is driven section tail end wall position arrangement to be calibrated pressure sensor, and set optical measurement window in reflected shock action area, synchronous acquisition pressure sensor output signal and absorption spectrum signal;Absorption spectrum signal is preprocessed and spectral line fitting, calculate the gas temperature and collision broadening coefficient after reflected shock wave, and reference pressure amplitude P5 after reflected shock wave is obtained accordingly;Pressure amplitude P1 before incident shock wave is measured using pressure gauge after metrological calibration;According to P1, P5 and pressure mutation time t0 Reference pressure step input signal based on Heaviside step function is constructed;Reference pressure step input signal and pressure sensor output signal are processed, and the ratio of the spectral amplitude of the two is used as the sensitivity of the pressure sensor at the corresponding frequency;Error source in the process of calculating reference pressure amplitude, pressure mutation time and sensitivity is evaluated and calculated, and the sensitivity calibration result of pressure sensor is obtained.The application can obtain the sensitivity characteristics and its uncertainty of pressure sensor.

The present application is applicable to the field of signal processing technology, and provides a signal enhancement method, device, OPA laser radar and storage medium. The signal enhancement method includes: obtaining a first frequency spectrum corresponding to each of N difference frequency signals for the target detection object, wherein the first frequency spectrum includes a spectrum serial number and a spectrum amplitude corresponding to the spectrum serial number, where N is an integer greater than 1; performing a dot multiplication operation on the spectrum amplitudes with the same spectrum serial number in the N first frequency spectra to obtain a second frequency spectrum with a signal-to-noise ratio of #imgabs0#, where x1 is the signal-to-noise ratio of a single first frequency spectrum; and determining the frequency of the difference frequency signal based on the second frequency spectrum. The present application can improve the accuracy of the frequency measurement results of the difference frequency signal.

The present application relates to the field of signal denoising, and provides a PPG signal light-weight diffusion denoising method, system, device and medium, which comprises generating reference noise and obtaining a pure signal to obtain a reference signal; the pure signal is added with noise to obtain a diffusion noise signal; a multi-scale one-dimensional convolution structure is constructed, the diffusion noise signal and the reference signal are respectively convolved through the multi-scale one-dimensional convolution structure to obtain a double-branch feature sequence; light-weight attention calculation is performed on the double-branch feature sequence to obtain an updated double-branch feature sequence, multi-layer residual fusion and noise prediction are performed on the updated double-branch feature sequence to obtain a noise prediction result; the diffusion noise prediction loss, the average spectral amplitude difference and the waveform form loss of the noise prediction result are calculated to obtain a prediction loss, and the target prediction model is obtained through training according to the prediction loss, and the PPG signal is denoised through the target prediction model.

The invention discloses a hyperspectral diffraction imaging device, system and method based on blind coding, and relates to the technical field of hyperspectral coherent diffraction imaging.The method comprises the steps that a hyperspectral light beam emitted by a light source is transmitted to a mask plate through a reflector after being subjected to beam expanding, focusing and collimation; controlling the mask plate to move from the first position to the second position, so that the mask plates at different positions before and after movement have overlapped areas along the light path direction, and obtaining a diffraction image of each lamination scanning position; and according to the diffraction image, performing joint reconstruction on the unknown mask plate, the spectrum and the imaging object by using a broadband phase reconstruction algorithm based on multi-parameter constraint to obtain amplitude and phase information of the reconstructed mask plate, the spectrum and the imaging object so as to complete hyperspectral illumination coherent diffraction imaging. According to the method disclosed by the invention, multi-spectrum amplitude-phase-spectrum joint reconstruction of the hyperspectrum under low-time coherent illumination can be realized by utilizing laminated scanning under the condition that codes are unknown.

A method for recovering missing spectral amplitude and phase information of an input real, positive valued image or signal possibly carried by incoherent or coherent waves.

The present application relates to the technical field of data processing, and discloses an ion concentration analysis method and system. The method includes: collecting spectral data at multiple monitoring points in the hydroxide ion chamber to obtain an original spectral data set for each monitoring point; respectively performing spectral amplitude, shape, and information difference measurement on the original spectral data set to obtain comprehensive spectral feature data for each monitoring point; inputting the comprehensive spectral feature data of each monitoring point into a preset partial least squares regression model for ion concentration prediction to obtain ion concentration prediction data for each monitoring point; inputting the ion concentration prediction data of each monitoring point into a preset integrated cost-sensitive deep neural network model for ion concentration anomaly detection to obtain a target ion concentration anomaly detection result. The present application improves the accuracy of ion concentration detection in the hydroxide ion chamber.

A method for generating an audio scene in a binaural spatialization system, comprising a step of providing a set of primary auditory transfer functions, relating to the left and right ears of individuals, recorded from a set of N individuals; a preliminary preparation step, with conversion to logarithmic values ​​and symmetrization of the spectral amplitude; a step of smoothing the spectral amplitude by binaural relative deviation, normalization for a reference direction (θ0,Φ0) with average across subjects, with flattening of the amplitudes on the ipsilateral side on a frontal cap (CF); a step of evaluating the mean interaural delay; and a step of generating a set of reprocessed transfer functions to generate an audio scene in real time using a binaural rendering engine, with one or more point audio sources at prescribed position(s). Figure from the abstract: Fig. 6

A measurement system for use in optical metrology, the measurement system which includes a control system configured and operable to carry out the following: (i) receive raw measured data generated by a measurement unit that is configured and operable for performing normal-incidence spectral interferometric measurements on a sample and generating the raw measured data indicative of spectral interferometric signals measured on the sample for a number of different optical path differences (OPDs) between sample and reference arms using infrared wavelengths; (ii) extract, from the raw measured data, a portion of spectral interferometric signals describing variation of signal intensity with a change of an optical path difference OPD during interferometric measurements, said portion of the spectral interferometric signals being independent of interferometric signals returned from a bottom portion of the sample in response to said illuminating electromagnetic field; and (iii) directly determine, from the extracted portion of the spectral interferometric signals, both spectral amplitude and phase of reflection of the illuminating electromagnetic field from the top portion of the sample, thereby enabling to determine a measured spectral signature characterizing the top portion of the sample.