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What is short time fourier transform and what are its properties?
Wiki User
∙ 13y ago
The fractiona lFourier transform (FRFT) is a potent tool to analyze the chirp signal. However,it failsin locating the fractional Fourier domain (FRFD)-frequency contents which is requiredin some applications. The short-time fractional Fourier
transform (STFRFT) is proposed to solve this problem
Wiki User
∙ 13y ago
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What is the difference between fourier series and fourier transform with real life example please?
A Fourier series is a set of harmonics at frequencies f, 2f, 3f etc. that represents a repetitive function of time that has a period of 1/f. A Fourier transform is a continuous linear function. The spectrum of a signal is the Fourier transform of its waveform. The waveform and spectrum are a Fourier transform pair.
What is the need for fourier transform in analog signal processing?
The fourier transform is used in analog signal processing in order to convert from time domain to frequency domain and back. By doing this, it is easier to implement filters, shifters, compression, etc.
Is there away to sort an array of data using the fast Fourier transform and finding the highest lower or average value finding his value or even best his position?
The Fast Fourier Transform is an implementation of the Discrete Fourier Transform. The DFT is a method of processing a time-sampled signal (eg, an audio wave) into a series of sines and cosines. As such, it is not a sorting algorithm, so this question does not make any sense.
For what purpose you use fourier transform in real life?
we use fourier transform to convert our signal form time domain to frequency domain. This tells us how much a certain frequency is involve in our signal. It also gives us many information that we cannot get from time domain. And we can easily compare signals in frequency domain.
Why a signal that is band limited is not time-limited while a signal that is time-limited is not band limited Improve Answer Discuss the question Can a signal be time-limited and band-limited at th?
A band-limited signal is one in which the Fourier transform is zero above a certain frequency. In other words it's a signal that ahas a finite frequency content. The simplest case is a pure sinusoidal signal, whose Fourier transform consists of a delta function centred on the frequency of the signal. A band-limited signal can be reconstructed exactly if it is sampled at at more than twice the maximum frequency present in the signal. A time-limited signal is a signal that is zero above a finite. An example of this would be a short pulse. The reason a signal cannot be both band-limited or time-limited is due to their relationship via the Fourier transform. One can show it is impossible for the Fourier transform of a signal with compact support ie either time or band-limited, to also have compact support. A time-limited signal must have a continuous frequency spectrum existing over all possible frequencies and a band-limited signal can only arise from signal existing for all time. Note this indicates in reality it is impossible to have a truly band-limited signal as it would take infinite time to transmit, but it is nonetheless a useful concept and we can produce nearly band-limited signal to a high degree of accuracy.
Application of fourier transform?
the main application of fourier transform is the changing a function from frequency domain to time domain, laplaxe transform is the general form of fourier transform .
What is the difference between fourier series and fourier transform with real life example please?
A Fourier series is a set of harmonics at frequencies f, 2f, 3f etc. that represents a repetitive function of time that has a period of 1/f. A Fourier transform is a continuous linear function. The spectrum of a signal is the Fourier transform of its waveform. The waveform and spectrum are a Fourier transform pair.
What is the Fourier Transform?
The Fourier transform is a mathematical transformation used to transform signals between time or spatial domain and frequency domain. It is reversible. It refers to both the transform operation and to the function it produces.
How can a composite signal be decomposed?
Spectral analysis of a repetitive waveform into a harmonic series can be done by Fourier analyis. This idea is generalised in the Fourier transform which converts any function of time expressed as a into a transform function of frequency. The time function is generally real while the transform function, also known as a the spectrum, is generally complex. A function and its Fourier transform are known as a Fourier transform pair, and the original function is the inverse transform of the spectrum.
What type of algorithm is fast fourier transform?
A fast fourier transform is an algorithm that converts time or space to frequency, or vice versa. They are mainly used in engineering, math and sciences.
What is the need for fourier transform in analog signal processing?
The fourier transform is used in analog signal processing in order to convert from time domain to frequency domain and back. By doing this, it is easier to implement filters, shifters, compression, etc.
Why Laplace transform is used in analysis of control system why not Fourier?
it is used for linear time invariant systems
Difference between fourier series and z-transform?
Laplace = analogue signal Fourier = digital signal Notes on comparisons between Fourier and Laplace transforms: The Laplace transform of a function is just like the Fourier transform of the same function, except for two things. The term in the exponential of a Laplace transform is a complex number instead of just an imaginary number and the lower limit of integration doesn't need to start at -∞. The exponential factor has the effect of forcing the signals to converge. That is why the Laplace transform can be applied to a broader class of signals than the Fourier transform, including exponentially growing signals. In a Fourier transform, both the signal in time domain and its spectrum in frequency domain are a one-dimensional, complex function. However, the Laplace transform of the 1D signal is a complex function defined over a two-dimensional complex plane, called the s-plane, spanned by two variables, one for the horizontal real axis and one for the vertical imaginary axis. If this 2D function is evaluated along the imaginary axis, the Laplace transform simply becomes the Fourier transform.
Is there away to sort an array of data using the fast Fourier transform and finding the highest lower or average value finding his value or even best his position?
The Fast Fourier Transform is an implementation of the Discrete Fourier Transform. The DFT is a method of processing a time-sampled signal (eg, an audio wave) into a series of sines and cosines. As such, it is not a sorting algorithm, so this question does not make any sense.
For what purpose you use fourier transform in real life?
we use fourier transform to convert our signal form time domain to frequency domain. This tells us how much a certain frequency is involve in our signal. It also gives us many information that we cannot get from time domain. And we can easily compare signals in frequency domain.
What is the Time domain analysis of control system?
Time domain basically means plotting a curve of amplitude over thr time axis. A given function or signal can be converted between the time and frequency domains with a pair of mathematical operators called a transform. An example is the Fourier transform, which decomposes a function into the sum of a (potentially infinite) number of sine wave frequency components. The 'spectrum' of frequency components is the frequency domain representation of the signal. The inverse Fourier transform converts the frequency domain function back to a time function.
What is K space in quantum mechanics?
K space refers to a space where things are in terms of momentum and frequency instead of position and time and the way you convert between real space and k-space (or Fourier space) is a mathematical transformation called the Fourier transform (and Inverse Fourier transform). This K-space also exists in classical physics. In quantum mechanics the space is made up of discrete values of K, whereas in classical physics K can take on a continuum of values.
