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Phasor approach refers to a method which is used for vectorial representation of sinusoidal waves like alternating currents and voltages or electromagnetic waves. The amplitude and the phase of the waveform is transformed into a vector where the phase is translated to the angle between the phasor vector and X-axis and the amplitude is translated to vector length or magnitude. In this concept the representation and the analysis becomes very simple and the addition of two wave forms is realized by their vectorial summation.
In Fluorescence lifetime and spectral imaging, phasor can be used to visualize the spectra and decay curves. [1] [2] In this method the Fourier transformation of the spectrum or decay curve is calculated and the resulted complex number is plotted on a 2D plot where the X-axis represents the real component and the Y-axis represents the imaginary component. This facilitates the analysis; each spectrum and decay is transformed into a unique position on the phasor plot which depends on its spectral width or emission maximum or to its average lifetime. Importantly, the analysis is fast and provides a graphical representation of the measured curve.
If we have decay curve which is represented by an exponential function with lifetime of τ:
Then the Fourier transformation at frequency ω of (normalized to have area under the curve 1) is represented by the Lorentz function:
This is a complex function and drawing the imaginary versus real part of this function for all possible lifetimes will be a semicircle where the zero lifetime is located at (1,0) and the infinite lifetime located at (0,0). By changing the lifetime from zero to infinity the phasor point moves along a semicircle from (1,0) to (0,0). This suggest that by taking the Fourier transformation of a measured decay curve and mapping the result on the phasor plot the lifetime can be estimated from the position of the phasor on the semicircle.
Explicitly, the lifetime can be measured from the magnitude of the phasor as follow:
This is a much faster approach than methods where fitting is used to estimate the lifetime.
The semicircle represents all possible single exponential fluorescent decays. When the measured decay curve consists of a superposition of different mono-exponential decays, the phasor falls inside the semicircle depending on the fractional contributions of the components. For a bi-exponential case with lifetimes τ1 and τ2, all phasor values fall on a line connecting the phasors of τ1 and τ2 on the semicircle, and the distance from the phasor to τ1 determines the fraction α. Therefore, the phasor values of the pixels of an image with two lifetime components are distributed on a line connecting the phasors of τ1 and τ2. Fitting a line through these phasor points with slope (v) and interception (u) , will give two intersections with the semicircle that determine the lifetimes τ1 and τ2: [3]
This is a blind solution for unmixing two components based on their lifetimes, provided that the fluorescence decays of the individual components show a single exponential behavior.
For a system with discrete number of gates and limited time window the phasor approach needs to be adapted. The equation for reference semicircle is changed to: [4]
Where K is the number of gates and T is the total measurement window. The average lifetimes are calculated by: And for a binary case after fitting a line through the data set of phasors and finding the slope (v) and interception (u) the lifetimes are calculated by:
In a non-ideal and real situations, the measured decay curve is the convolution of the instrument response (the laser pulse distorted by system) with an exponential function which makes the analysis more complicated. A large number of techniques have been developed to overcome to this problem, but in phasor approach this is simply solved by the fact that the Fourier transformation of a convolution is the product of Fourier transforms. This allows to take into account the effect of instrument response by taking the Fourier transformation of instrument response function and dividing the total phasor to instrument response transformation.
Similar to the temporal phasor, the Fourier transform of a spectrum can be used to create a phasor. Consider a Gaussian spectrum with zero spectral width and a changing emission maximum from channel zero to K; the phasor rotates on a circle from small angles to larger angles. This corresponds to the shift theorem of Fourier transforms. Changing the spectral width from zero to infinity moves the phasor toward the center. This means that the phasor for the background signal, which can be considered a spectrum with infinite spectral width, is located at the center of the phasor with coordinates (0,0).
One of the interesting properties of the phasor approach is its linearity, where the superposition of different spectra or decay curves can be analyzed through the vectorial superposition of individual phasors. This is demonstrated in the figure, where adding two spectra with different emission maxima results in a phasor that lies on a line connecting the individual phasors. In a ternary system, adding three spectra results in a triangle formed by the phasors of the individual spectra or decays.
For a system which has three different components and different spectra are shown, the phasor of the pixels with different fractional intensities fall inside a triangle where the vertices are made up by phasor of pure components. The fractional intensities then can be estimated by measuring the area of the triangle that each phasor makes with the phasor of pure vertex.
This feature is noteworthy because there is a one-to-one correspondence between the pixels in an image and their phasors on the phasor plot, determined by their spectrum or decay curve. Phasors corresponding to pixels with similar temporal-spectral properties cluster in specific regions of the phasor plot. This characteristic provides a method for categorizing image pixels based on their temporal-spectral properties. By selecting a region of interest on the phasor plot, a reciprocal transformation can be applied, projecting the selected phasors back onto the image. This process enables basic image segmentation.
In signal processing, group delay and phase delay are functions that describe in different ways the delay times experienced by a signal’s various sinuoidal frequency components as they pass through a linear time-invariant (LTI) system.
Pink noise, 1⁄f noise, fractional noise or fractal noise is a signal or process with a frequency spectrum such that the power spectral density is inversely proportional to the frequency of the signal. In pink noise, each octave interval carries an equal amount of noise energy.
A chirp is a signal in which the frequency increases (up-chirp) or decreases (down-chirp) with time. In some sources, the term chirp is used interchangeably with sweep signal. It is commonly applied to sonar, radar, and laser systems, and to other applications, such as in spread-spectrum communications. This signal type is biologically inspired and occurs as a phenomenon due to dispersion. It is usually compensated for by using a matched filter, which can be part of the propagation channel. Depending on the specific performance measure, however, there are better techniques both for radar and communication. Since it was used in radar and space, it has been adopted also for communication standards. For automotive radar applications, it is usually called linear frequency modulated waveform (LFMW).
In signal processing, the power spectrum of a continuous time signal describes the distribution of power into frequency components composing that signal. According to Fourier analysis, any physical signal can be decomposed into a number of discrete frequencies, or a spectrum of frequencies over a continuous range. The statistical average of any sort of signal as analyzed in terms of its frequency content, is called its spectrum.
A resistor–capacitor circuit, or RC filter or RC network, is an electric circuit composed of resistors and capacitors. It may be driven by a voltage or current source and these will produce different responses. A first order RC circuit is composed of one resistor and one capacitor and is the simplest type of RC circuit.
The short-time Fourier transform (STFT) is a Fourier-related transform used to determine the sinusoidal frequency and phase content of local sections of a signal as it changes over time. In practice, the procedure for computing STFTs is to divide a longer time signal into shorter segments of equal length and then compute the Fourier transform separately on each shorter segment. This reveals the Fourier spectrum on each shorter segment. One then usually plots the changing spectra as a function of time, known as a spectrogram or waterfall plot, such as commonly used in software defined radio (SDR) based spectrum displays. Full bandwidth displays covering the whole range of an SDR commonly use fast Fourier transforms (FFTs) with 2^24 points on desktop computers.
The step response of a system in a given initial state consists of the time evolution of its outputs when its control inputs are Heaviside step functions. In electronic engineering and control theory, step response is the time behaviour of the outputs of a general system when its inputs change from zero to one in a very short time. The concept can be extended to the abstract mathematical notion of a dynamical system using an evolution parameter.
In system analysis, among other fields of study, a linear time-invariant (LTI) system is a system that produces an output signal from any input signal subject to the constraints of linearity and time-invariance; these terms are briefly defined in the overview below. These properties apply (exactly or approximately) to many important physical systems, in which case the response y(t) of the system to an arbitrary input x(t) can be found directly using convolution: y(t) = (x ∗ h)(t) where h(t) is called the system's impulse response and ∗ represents convolution (not to be confused with multiplication). What's more, there are systematic methods for solving any such system (determining h(t)), whereas systems not meeting both properties are generally more difficult (or impossible) to solve analytically. A good example of an LTI system is any electrical circuit consisting of resistors, capacitors, inductors and linear amplifiers.
Fluorescence-lifetime imaging microscopy or FLIM is an imaging technique based on the differences in the exponential decay rate of the photon emission of a fluorophore from a sample. It can be used as an imaging technique in confocal microscopy, two-photon excitation microscopy, and multiphoton tomography.
The Havriliak–Negami relaxation is an empirical modification of the Debye relaxation model in electromagnetism. Unlike the Debye model, the Havriliak–Negami relaxation accounts for the asymmetry and broadness of the dielectric dispersion curve. The model was first used to describe the dielectric relaxation of some polymers, by adding two exponential parameters to the Debye equation:
Fluorescence correlation spectroscopy (FCS) is a statistical analysis, via time correlation, of stationary fluctuations of the fluorescence intensity. Its theoretical underpinning originated from L. Onsager's regression hypothesis. The analysis provides kinetic parameters of the physical processes underlying the fluctuations. One of the interesting applications of this is an analysis of the concentration fluctuations of fluorescent particles (molecules) in solution. In this application, the fluorescence emitted from a very tiny space in solution containing a small number of fluorescent particles (molecules) is observed. The fluorescence intensity is fluctuating due to Brownian motion of the particles. In other words, the number of the particles in the sub-space defined by the optical system is randomly changing around the average number. The analysis gives the average number of fluorescent particles and average diffusion time, when the particle is passing through the space. Eventually, both the concentration and size of the particle (molecule) are determined. Both parameters are important in biochemical research, biophysics, and chemistry.
In ultrafast optics, spectral phase interferometry for direct electric-field reconstruction (SPIDER) is an ultrashort pulse measurement technique originally developed by Chris Iaconis and Ian Walmsley.
The stretched exponential function is obtained by inserting a fractional power law into the exponential function. In most applications, it is meaningful only for arguments t between 0 and +∞. With β = 1, the usual exponential function is recovered. With a stretching exponentβ between 0 and 1, the graph of log f versus t is characteristically stretched, hence the name of the function. The compressed exponential function has less practical importance, with the notable exception of β = 2, which gives the normal distribution.
The method of reassignment is a technique for sharpening a time-frequency representation by mapping the data to time-frequency coordinates that are nearer to the true region of support of the analyzed signal. The method has been independently introduced by several parties under various names, including method of reassignment, remapping, time-frequency reassignment, and modified moving-window method. The method of reassignment sharpens blurry time-frequency data by relocating the data according to local estimates of instantaneous frequency and group delay. This mapping to reassigned time-frequency coordinates is very precise for signals that are separable in time and frequency with respect to the analysis window.
Resonance fluorescence is the process in which a two-level atom system interacts with the quantum electromagnetic field if the field is driven at a frequency near to the natural frequency of the atom.
Fluorescence cross-correlation spectroscopy (FCCS) is a spectroscopic technique that examines the interactions of fluorescent particles of different colours as they randomly diffuse through a microscopic detection volume over time, under steady conditions.
The open-circuit time constant (OCT) method is an approximate analysis technique used in electronic circuit design to determine the corner frequency of complex circuits. It is a special case of zero-value time constant (ZVT) method technique when reactive elements consist of only capacitors. The zero-value time (ZVT) constant method itself is a special case of the general Time- and Transfer Constant (TTC) analysis that allows full evaluation of the zeros and poles of any lumped LTI systems of with both inductors and capacitors as reactive elements using time constants and transfer constants. The OCT method provides a quick evaluation, and identifies the largest contributions to time constants as a guide to the circuit improvements.
In physics and engineering, the time constant, usually denoted by the Greek letter τ (tau), is the parameter characterizing the response to a step input of a first-order, linear time-invariant (LTI) system. The time constant is the main characteristic unit of a first-order LTI system. It gives speed of the response.
The perturbed γ-γ angular correlation, PAC for short or PAC-Spectroscopy, is a method of nuclear solid-state physics with which magnetic and electric fields in crystal structures can be measured. In doing so, electrical field gradients and the Larmor frequency in magnetic fields as well as dynamic effects are determined. With this very sensitive method, which requires only about 10–1000 billion atoms of a radioactive isotope per measurement, material properties in the local structure, phase transitions, magnetism and diffusion can be investigated. The PAC method is related to nuclear magnetic resonance and the Mössbauer effect, but shows no signal attenuation at very high temperatures. Today only the time-differential perturbed angular correlation (TDPAC) is used.
Spectral interferometry (SI) or frequency-domain interferometry is a linear technique used to measure optical pulses, with the condition that a reference pulse that was previously characterized is available. This technique provides information about the intensity and phase of the pulses. SI was first proposed by Claude Froehly and coworkers in the 1970s.