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"It is well-established that the window functions play a vital role in digital signal processing. Sometimes, it becomes critical in selecting the right window for a given application. Major applications areas include digital spectral analysis, design of FIR filters, pulse compression radar, and speech signal processing. This book provides complete information on the discrete time window functions used in digital signal processing. It also gives cues on how to choose a window function for particular applications. Topics covered include spectral analysis, use of windows in digital filtering, application of windows in radar, and ringing artifacts applications of the Short Time Fourier Transform (STFT) in speech processing"--
Signal processing --- Digital techniques. --- Digital signal processing --- Digital communications --- Digital electronics --- Computer Engineering --- Digital and Wireless Communication --- Digital Signal Processing --- ENG --- ElectricalEngineering --- SCI-TECH --- COMPUTERSCIENCE --- INFORMATIONSCIENCE --- STM --- digital filtering --- digital signal processing --- radar --- Short Time Fourier Transform --- spectral analysis --- speech processing --- window functions
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Image processing --- Signal processing --- Speech processing systems --- dsp (digital signal processing) --- dtft (discrete time system fourier transform) --- fourieranalyse --- mmse --- spraakcommunicatie (spraaktechnologie) --- spraakfilter --- stft (short time fourier transform) --- wiener filter --- Computational linguistics --- Electronic systems --- Information theory --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers --- Digital signal processing --- Digital communications --- Digital electronics --- Digital image processing --- Digital techniques --- Contains audio-visual material --- Electronics --- Telecommunication technology --- spraaktechnologie --- algoritmen --- communicatietechnologie
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Most metallic components and structures are subjected, in service, to random or variable amplitude loadings. There are many examples: vehicles subjected to loadings and vibrations caused by road irregularity and engine, structures exposed to wind, off-shore platforms undergoing wave-loadings, and so on. Just like constant amplitude loadings, random and variable amplitude loadings can make fatigue cracks initiate and propagate, even up to catastrophic failures. Engineers faced with the problem of estimating the structural integrity and the fatigue strength of metallic structures, or their propensity to fracture, usually make use of theoretical, numerical, or experimental approaches. This reprint collects a series of recent scientific contributions aimed at providing an up-to-date overview of approaches and case studies—theoretical, numerical or experimental—on several topics in the field of fracture, fatigue strength, and the structural integrity of metallic components subjected to random or variable amplitude loadings.
Technology: general issues --- History of engineering & technology --- small cracks --- helicopter flight load spectra --- FALSTAFF flight load spectra --- fatigue crack growth --- surface topography --- optical profilometry --- height digital image correlation --- discontinuous displacements --- triaxial displacements --- fracture analysis --- welded joint --- repair welding thermal shock --- XFEM --- welding linear energy --- high-temperature fatigue --- nickel-based superalloy --- investment casting --- metallography --- turbine blade --- fatigue --- testing systems --- random loadings --- servo-hydraulic --- shaker table --- crack growth --- metallic materials --- plasticity --- crack closure --- spectrum loading --- random loading --- fatigue damage --- power spectral density (PSD) --- spectral methods --- lattice structures --- structural dynamic response --- vibration fatigue testing --- fatigue life prediction --- analytical framework --- fatigue crack --- residual strength --- retardation effect --- nonstationary random loadings --- run test --- short-time Fourier transform --- n/a
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Most metallic components and structures are subjected, in service, to random or variable amplitude loadings. There are many examples: vehicles subjected to loadings and vibrations caused by road irregularity and engine, structures exposed to wind, off-shore platforms undergoing wave-loadings, and so on. Just like constant amplitude loadings, random and variable amplitude loadings can make fatigue cracks initiate and propagate, even up to catastrophic failures. Engineers faced with the problem of estimating the structural integrity and the fatigue strength of metallic structures, or their propensity to fracture, usually make use of theoretical, numerical, or experimental approaches. This reprint collects a series of recent scientific contributions aimed at providing an up-to-date overview of approaches and case studies—theoretical, numerical or experimental—on several topics in the field of fracture, fatigue strength, and the structural integrity of metallic components subjected to random or variable amplitude loadings.
small cracks --- helicopter flight load spectra --- FALSTAFF flight load spectra --- fatigue crack growth --- surface topography --- optical profilometry --- height digital image correlation --- discontinuous displacements --- triaxial displacements --- fracture analysis --- welded joint --- repair welding thermal shock --- XFEM --- welding linear energy --- high-temperature fatigue --- nickel-based superalloy --- investment casting --- metallography --- turbine blade --- fatigue --- testing systems --- random loadings --- servo-hydraulic --- shaker table --- crack growth --- metallic materials --- plasticity --- crack closure --- spectrum loading --- random loading --- fatigue damage --- power spectral density (PSD) --- spectral methods --- lattice structures --- structural dynamic response --- vibration fatigue testing --- fatigue life prediction --- analytical framework --- fatigue crack --- residual strength --- retardation effect --- nonstationary random loadings --- run test --- short-time Fourier transform --- n/a
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Modern computer technology has opened up new opportunities for the development of digital signal processing methods. The applications of digital signal processing have expanded significantly and today include audio and speech processing, sonar, radar, and other sensor array processing, spectral density estimation, statistical signal processing, digital image processing, signal processing for telecommunications, control systems, biomedical engineering, and seismology, among others. This Special Issue is aimed at wide coverage of the problems of digital signal processing, from mathematical modeling to the implementation of problem-oriented systems. The basis of digital signal processing is digital filtering. Wavelet analysis implements multiscale signal processing and is used to solve applied problems of de-noising and compression. Processing of visual information, including image and video processing and pattern recognition, is actively used in robotic systems and industrial processes control today. Improving digital signal processing circuits and developing new signal processing systems can improve the technical characteristics of many digital devices. The development of new methods of artificial intelligence, including artificial neural networks and brain-computer interfaces, opens up new prospects for the creation of smart technology. This Special Issue contains the latest technological developments in mathematics and digital signal processing. The stated results are of interest to researchers in the field of applied mathematics and developers of modern digital signal processing systems.
digital filter --- finite field algebra --- conversion device --- module --- memory device --- residue --- feedback regulation --- digital signal analysis --- control efficacy --- residue number system --- redundant residue number system --- modular division --- fraction --- algorithm --- mathematical models of digital signal processing --- digital filtering --- maximum correntropy --- impulsive noise --- sparse channel estimation --- discrete wavelet transform --- medical imaging --- 3D image processing --- quantization noise --- harmonic wavelets --- classification --- kNN-algorithm --- deep neural networks --- machine learning --- Fourier transform --- short-time Fourier transform --- wavelet transform --- spectrogram --- confusion matrix --- ROC curve --- 3D model --- prosthetic design --- orientation --- positioning --- reconstruction --- speech enhancement --- adaptive filter --- microphone array --- sub-band processing --- filter bank --- posture classification --- skeleton detection --- motion capture --- exercise classification --- virtual rehabilitation --- wood defect --- CNN --- ELM --- genetic algorithm --- detection
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Modern computer technology has opened up new opportunities for the development of digital signal processing methods. The applications of digital signal processing have expanded significantly and today include audio and speech processing, sonar, radar, and other sensor array processing, spectral density estimation, statistical signal processing, digital image processing, signal processing for telecommunications, control systems, biomedical engineering, and seismology, among others. This Special Issue is aimed at wide coverage of the problems of digital signal processing, from mathematical modeling to the implementation of problem-oriented systems. The basis of digital signal processing is digital filtering. Wavelet analysis implements multiscale signal processing and is used to solve applied problems of de-noising and compression. Processing of visual information, including image and video processing and pattern recognition, is actively used in robotic systems and industrial processes control today. Improving digital signal processing circuits and developing new signal processing systems can improve the technical characteristics of many digital devices. The development of new methods of artificial intelligence, including artificial neural networks and brain-computer interfaces, opens up new prospects for the creation of smart technology. This Special Issue contains the latest technological developments in mathematics and digital signal processing. The stated results are of interest to researchers in the field of applied mathematics and developers of modern digital signal processing systems.
Information technology industries --- digital filter --- finite field algebra --- conversion device --- module --- memory device --- residue --- feedback regulation --- digital signal analysis --- control efficacy --- residue number system --- redundant residue number system --- modular division --- fraction --- algorithm --- mathematical models of digital signal processing --- digital filtering --- maximum correntropy --- impulsive noise --- sparse channel estimation --- discrete wavelet transform --- medical imaging --- 3D image processing --- quantization noise --- harmonic wavelets --- classification --- kNN-algorithm --- deep neural networks --- machine learning --- Fourier transform --- short-time Fourier transform --- wavelet transform --- spectrogram --- confusion matrix --- ROC curve --- 3D model --- prosthetic design --- orientation --- positioning --- reconstruction --- speech enhancement --- adaptive filter --- microphone array --- sub-band processing --- filter bank --- posture classification --- skeleton detection --- motion capture --- exercise classification --- virtual rehabilitation --- wood defect --- CNN --- ELM --- genetic algorithm --- detection --- digital filter --- finite field algebra --- conversion device --- module --- memory device --- residue --- feedback regulation --- digital signal analysis --- control efficacy --- residue number system --- redundant residue number system --- modular division --- fraction --- algorithm --- mathematical models of digital signal processing --- digital filtering --- maximum correntropy --- impulsive noise --- sparse channel estimation --- discrete wavelet transform --- medical imaging --- 3D image processing --- quantization noise --- harmonic wavelets --- classification --- kNN-algorithm --- deep neural networks --- machine learning --- Fourier transform --- short-time Fourier transform --- wavelet transform --- spectrogram --- confusion matrix --- ROC curve --- 3D model --- prosthetic design --- orientation --- positioning --- reconstruction --- speech enhancement --- adaptive filter --- microphone array --- sub-band processing --- filter bank --- posture classification --- skeleton detection --- motion capture --- exercise classification --- virtual rehabilitation --- wood defect --- CNN --- ELM --- genetic algorithm --- detection
Choose an application
Most metallic components and structures are subjected, in service, to random or variable amplitude loadings. There are many examples: vehicles subjected to loadings and vibrations caused by road irregularity and engine, structures exposed to wind, off-shore platforms undergoing wave-loadings, and so on. Just like constant amplitude loadings, random and variable amplitude loadings can make fatigue cracks initiate and propagate, even up to catastrophic failures. Engineers faced with the problem of estimating the structural integrity and the fatigue strength of metallic structures, or their propensity to fracture, usually make use of theoretical, numerical, or experimental approaches. This reprint collects a series of recent scientific contributions aimed at providing an up-to-date overview of approaches and case studies—theoretical, numerical or experimental—on several topics in the field of fracture, fatigue strength, and the structural integrity of metallic components subjected to random or variable amplitude loadings.
Technology: general issues --- History of engineering & technology --- small cracks --- helicopter flight load spectra --- FALSTAFF flight load spectra --- fatigue crack growth --- surface topography --- optical profilometry --- height digital image correlation --- discontinuous displacements --- triaxial displacements --- fracture analysis --- welded joint --- repair welding thermal shock --- XFEM --- welding linear energy --- high-temperature fatigue --- nickel-based superalloy --- investment casting --- metallography --- turbine blade --- fatigue --- testing systems --- random loadings --- servo-hydraulic --- shaker table --- crack growth --- metallic materials --- plasticity --- crack closure --- spectrum loading --- random loading --- fatigue damage --- power spectral density (PSD) --- spectral methods --- lattice structures --- structural dynamic response --- vibration fatigue testing --- fatigue life prediction --- analytical framework --- fatigue crack --- residual strength --- retardation effect --- nonstationary random loadings --- run test --- short-time Fourier transform --- small cracks --- helicopter flight load spectra --- FALSTAFF flight load spectra --- fatigue crack growth --- surface topography --- optical profilometry --- height digital image correlation --- discontinuous displacements --- triaxial displacements --- fracture analysis --- welded joint --- repair welding thermal shock --- XFEM --- welding linear energy --- high-temperature fatigue --- nickel-based superalloy --- investment casting --- metallography --- turbine blade --- fatigue --- testing systems --- random loadings --- servo-hydraulic --- shaker table --- crack growth --- metallic materials --- plasticity --- crack closure --- spectrum loading --- random loading --- fatigue damage --- power spectral density (PSD) --- spectral methods --- lattice structures --- structural dynamic response --- vibration fatigue testing --- fatigue life prediction --- analytical framework --- fatigue crack --- residual strength --- retardation effect --- nonstationary random loadings --- run test --- short-time Fourier transform
Choose an application
Modern computer technology has opened up new opportunities for the development of digital signal processing methods. The applications of digital signal processing have expanded significantly and today include audio and speech processing, sonar, radar, and other sensor array processing, spectral density estimation, statistical signal processing, digital image processing, signal processing for telecommunications, control systems, biomedical engineering, and seismology, among others. This Special Issue is aimed at wide coverage of the problems of digital signal processing, from mathematical modeling to the implementation of problem-oriented systems. The basis of digital signal processing is digital filtering. Wavelet analysis implements multiscale signal processing and is used to solve applied problems of de-noising and compression. Processing of visual information, including image and video processing and pattern recognition, is actively used in robotic systems and industrial processes control today. Improving digital signal processing circuits and developing new signal processing systems can improve the technical characteristics of many digital devices. The development of new methods of artificial intelligence, including artificial neural networks and brain-computer interfaces, opens up new prospects for the creation of smart technology. This Special Issue contains the latest technological developments in mathematics and digital signal processing. The stated results are of interest to researchers in the field of applied mathematics and developers of modern digital signal processing systems.
Information technology industries --- digital filter --- finite field algebra --- conversion device --- module --- memory device --- residue --- feedback regulation --- digital signal analysis --- control efficacy --- residue number system --- redundant residue number system --- modular division --- fraction --- algorithm --- mathematical models of digital signal processing --- digital filtering --- maximum correntropy --- impulsive noise --- sparse channel estimation --- discrete wavelet transform --- medical imaging --- 3D image processing --- quantization noise --- harmonic wavelets --- classification --- kNN-algorithm --- deep neural networks --- machine learning --- Fourier transform --- short-time Fourier transform --- wavelet transform --- spectrogram --- confusion matrix --- ROC curve --- 3D model --- prosthetic design --- orientation --- positioning --- reconstruction --- speech enhancement --- adaptive filter --- microphone array --- sub-band processing --- filter bank --- posture classification --- skeleton detection --- motion capture --- exercise classification --- virtual rehabilitation --- wood defect --- CNN --- ELM --- genetic algorithm --- detection
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Nondestructive testing and evaluation (NDT&E) is one of the most important techniques for determining the quality and safety of materials, components, devices, and structures. NDT&E technologies include ultrasonic testing (UT), magnetic particle testing (MT), magnetic flux leakage testing (MFLT), eddy current testing (ECT), radiation testing (RT), penetrant testing (PT), and visual testing (VT), and these are widely used throughout the modern industry. However, some NDT processes, such as those for cleaning specimens and removing paint, cause environmental pollution and must only be considered in limited environments (time, space, and sensor selection). Thus, NDT&E is classified as a typical 3D (dirty, dangerous, and difficult) job. In addition, NDT operators judge the presence of damage based on experience and subjective judgment, so in some cases, a flaw may not be detected during the test. Therefore, to obtain clearer test results, a means for the operator to determine flaws more easily should be provided. In addition, the test results should be organized systemically in order to identify the cause of the abnormality in the test specimen and to identify the progress of the damage quantitatively.
Technology: general issues --- History of engineering & technology --- composites --- multi-scale --- embedded damage --- non-destructive testing --- photoacoustic --- ultrasonic representation --- terahertz --- coded-aperture imaging --- convolution neural network (CNN) --- fast image reconstruction --- nondestructive evaluation --- acoustic nonlinearity parameter --- indirect method --- laser ultrasound --- fully non-contact --- surface acoustic wave --- UWB-PPM --- UWB-OOK --- buried objects --- nondestructive environment --- Levenberg-Marquardt method --- textured surface anomaly detection --- computer vision --- deep learning --- attention mechanism --- adaptive fusion --- power quality disturbances --- long short term memory --- convolutional neural network --- short time Fourier transform --- leaky Lamb wave --- semi-analytical finite element (SAFE) --- waveguide sensor --- finite-width plate --- waveguide plate --- width modes --- spatial beating --- Rayleigh-Sommerfeld integral (RSI) --- weld cracks --- eddy current nondestructive testing --- gradiently relative magnetic permeability --- heat affected zone --- austenitic stainless steel --- circulating fluidized bed combustion boiler --- water-cooled wall tube --- magnetic sensor array --- magnetic flux density --- flexible ultrasonic probe --- neutron irradiation embrittlement --- reactor pressure vessel --- magnetic nondestructive evaluation --- micromagnetic multiparameter microstructure and stress analysis 3MA --- magnetic adaptive testing --- 3D imaging of metal grains --- non-destructive testing methods --- stacking images --- SA106 carbon steel --- terahertz waves --- refractive index --- thickness measurement --- Shim stock films --- composite materials --- reflection mode --- neutron radiography --- Bragg-edge imaging --- gas tungsten arc welding (GTAW) --- low transformation temperature (LTT) steel --- austenite-to-martensite transformation --- Debye-Waller factor --- composites --- multi-scale --- embedded damage --- non-destructive testing --- photoacoustic --- ultrasonic representation --- terahertz --- coded-aperture imaging --- convolution neural network (CNN) --- fast image reconstruction --- nondestructive evaluation --- acoustic nonlinearity parameter --- indirect method --- laser ultrasound --- fully non-contact --- surface acoustic wave --- UWB-PPM --- UWB-OOK --- buried objects --- nondestructive environment --- Levenberg-Marquardt method --- textured surface anomaly detection --- computer vision --- deep learning --- attention mechanism --- adaptive fusion --- power quality disturbances --- long short term memory --- convolutional neural network --- short time Fourier transform --- leaky Lamb wave --- semi-analytical finite element (SAFE) --- waveguide sensor --- finite-width plate --- waveguide plate --- width modes --- spatial beating --- Rayleigh-Sommerfeld integral (RSI) --- weld cracks --- eddy current nondestructive testing --- gradiently relative magnetic permeability --- heat affected zone --- austenitic stainless steel --- circulating fluidized bed combustion boiler --- water-cooled wall tube --- magnetic sensor array --- magnetic flux density --- flexible ultrasonic probe --- neutron irradiation embrittlement --- reactor pressure vessel --- magnetic nondestructive evaluation --- micromagnetic multiparameter microstructure and stress analysis 3MA --- magnetic adaptive testing --- 3D imaging of metal grains --- non-destructive testing methods --- stacking images --- SA106 carbon steel --- terahertz waves --- refractive index --- thickness measurement --- Shim stock films --- composite materials --- reflection mode --- neutron radiography --- Bragg-edge imaging --- gas tungsten arc welding (GTAW) --- low transformation temperature (LTT) steel --- austenite-to-martensite transformation --- Debye-Waller factor
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Non-invasive biomedical sensors for monitoring physiological parameters from the human body for potential future therapies and healthcare solutions. Today, a critical factor in providing a cost-effective healthcare system is improving patients' quality of life and mobility, which can be achieved by developing non-invasive sensor systems, which can then be deployed in point of care, used at home or integrated into wearable devices for long-term data collection. Another factor that plays an integral part in a cost-effective healthcare system is the signal processing of the data recorded with non-invasive biomedical sensors. In this book, we aimed to attract researchers who are interested in the application of signal processing methods to different biomedical signals, such as an electroencephalogram (EEG), electromyogram (EMG), functional near-infrared spectroscopy (fNIRS), electrocardiogram (ECG), galvanic skin response, pulse oximetry, photoplethysmogram (PPG), etc. We encouraged new signal processing methods or the use of existing signal processing methods for its novel application in physiological signals to help healthcare providers make better decisions.
Medical equipment & techniques --- movement intention --- brain–computer interface --- movement-related cortical potential --- neurorehabilitation --- phonocardiogram --- machine learning --- empirical mode decomposition --- feature extraction --- mel-frequency cepstral coefficients --- support vector machines --- computer aided diagnosis --- congenital heart disease --- statistical analysis --- convolutional neural network (CNN) --- long short-term memory (LSTM) --- emotion recognition --- EEG --- ECG --- GSR --- deep neural network --- physiological signals --- electroencephalography --- Brain-Computer Interface --- multiscale principal component analysis --- successive decomposition index --- motor imagery --- mental imagery --- classification --- hybrid brain-computer interface (BCI) --- home automation --- electroencephalogram (EEG) --- steady-state visually evoked potential (SSVEP) --- eye blink --- short-time Fourier transform (STFT) --- convolution neural network (CNN) --- human machine interface (HMI) --- rehabilitation --- wheelchair --- quadriplegia --- Raspberry Pi --- image gradient --- AMR voice --- Open-CV --- image processing --- acoustic --- startle --- reaction --- response --- reflex --- blink --- mobile --- sound --- stroke --- EMG --- brain-computer interface --- myoelectric control --- pattern recognition --- functional near-infrared spectroscopy --- z-score method --- channel selection --- region of interest --- channel of interest --- respiratory rate (RR) --- Electrocardiogram (ECG) --- ECG derived respiration (EDR) --- auscultation sites --- pulse plethysmograph --- biomedical signal processing --- feature selection and reduction --- discrete wavelet transform --- hypertension --- movement intention --- brain–computer interface --- movement-related cortical potential --- neurorehabilitation --- phonocardiogram --- machine learning --- empirical mode decomposition --- feature extraction --- mel-frequency cepstral coefficients --- support vector machines --- computer aided diagnosis --- congenital heart disease --- statistical analysis --- convolutional neural network (CNN) --- long short-term memory (LSTM) --- emotion recognition --- EEG --- ECG --- GSR --- deep neural network --- physiological signals --- electroencephalography --- Brain-Computer Interface --- multiscale principal component analysis --- successive decomposition index --- motor imagery --- mental imagery --- classification --- hybrid brain-computer interface (BCI) --- home automation --- electroencephalogram (EEG) --- steady-state visually evoked potential (SSVEP) --- eye blink --- short-time Fourier transform (STFT) --- convolution neural network (CNN) --- human machine interface (HMI) --- rehabilitation --- wheelchair --- quadriplegia --- Raspberry Pi --- image gradient --- AMR voice --- Open-CV --- image processing --- acoustic --- startle --- reaction --- response --- reflex --- blink --- mobile --- sound --- stroke --- EMG --- brain-computer interface --- myoelectric control --- pattern recognition --- functional near-infrared spectroscopy --- z-score method --- channel selection --- region of interest --- channel of interest --- respiratory rate (RR) --- Electrocardiogram (ECG) --- ECG derived respiration (EDR) --- auscultation sites --- pulse plethysmograph --- biomedical signal processing --- feature selection and reduction --- discrete wavelet transform --- hypertension
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