Results 221 to 230 of about 306,865 (270)
Some of the next articles are maybe not open access.
Fractional discrete Fourier transforms
Optics Letters, 1996Direct calculation of fractional Fourier transforms from the expressions derived for their optical implementation is laborious. An extension of the discrete Fourier transform would have only O(N(2)) computational complexity. We define such a system, offer a general way to compute the fractional discrete Fourier transform matrix, and numerically ...
Z T, Deng +2 more
openaire +2 more sources
Generalized discrete Fourier transforms: the discrete Fourier-Riccati-Bessel transform
Computer Physics Communications, 1995zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Stade, Eric, Layton, E. G.
openaire +1 more source
2018
Discrete Fourier transform (DFT) is a frequency domain representation of finite-length discrete-time signals. It is also used to represent FIR discrete-time systems in the frequency domain. As the name implies, DFT is a discrete set of frequency samples uniformly distributed around the unit circle in the complex frequency plane that characterizes a ...
+6 more sources
Discrete Fourier transform (DFT) is a frequency domain representation of finite-length discrete-time signals. It is also used to represent FIR discrete-time systems in the frequency domain. As the name implies, DFT is a discrete set of frequency samples uniformly distributed around the unit circle in the complex frequency plane that characterizes a ...
+6 more sources
2020
The ordinary Fourier Transform is for a continuous function. The continuous Fourier Transform is difficult to use in real time because in real time, one is dealing with discrete data sampled using some kind of sensors. For instance, the time series from weather, traffic, stocks etc., one is getting the discrete values at each time point (e.g. 1-s, 2-s,
+4 more sources
The ordinary Fourier Transform is for a continuous function. The continuous Fourier Transform is difficult to use in real time because in real time, one is dealing with discrete data sampled using some kind of sensors. For instance, the time series from weather, traffic, stocks etc., one is getting the discrete values at each time point (e.g. 1-s, 2-s,
+4 more sources
2014
The Fourier transform is an integral of the product of a signal (waveform) to be analyzed and a complex exponential function with an arbitrary frequency (see Eq. ( 2.37)). In theoretical discussions, it is possible to deal with continuous functions.
openaire +2 more sources
The Fourier transform is an integral of the product of a signal (waveform) to be analyzed and a complex exponential function with an arbitrary frequency (see Eq. ( 2.37)). In theoretical discussions, it is possible to deal with continuous functions.
openaire +2 more sources
Discrete Fourier Transformation
2020The Discrete Fourier Transform (DFT) is the discrete version of the Fourier Transform (FT) both in the time domain and in the frequency domain. It can be seen as an adaption of FT for use on computers and digital signal processing (DSP) chips.
Zhiping Shi, Yong Guan, Ximeng Li
openaire +1 more source
2012
From an analytical perspective, the Fourier series represents a periodic signal as an infinite sum of multiples of the fundamental frequencies, while the Fourier transform permits an aperiodic waveform to be described as an integral sum over a continuous range of frequencies.
+4 more sources
From an analytical perspective, the Fourier series represents a periodic signal as an infinite sum of multiples of the fundamental frequencies, while the Fourier transform permits an aperiodic waveform to be described as an integral sum over a continuous range of frequencies.
+4 more sources
2021
In this chapter, Discrete Fourier Transform, the most often used version of Fourier analysis, the DFT, and its inverse are derived with appropriate examples. The DFT, as in all versions of Fourier analysis, represents an arbitrary amplitude profile signal in terms of sinusoidal or equivalent complex exponentials.
openaire +2 more sources
In this chapter, Discrete Fourier Transform, the most often used version of Fourier analysis, the DFT, and its inverse are derived with appropriate examples. The DFT, as in all versions of Fourier analysis, represents an arbitrary amplitude profile signal in terms of sinusoidal or equivalent complex exponentials.
openaire +2 more sources
2002
The Fourier Transform has wide applications in scientific computing and engineering. Although it has a continuous version, we will consider only the discrete version (DFT) and present what is commonly known as the Fast Fourier Transform (FFT) algorithm.
openaire +1 more source
The Fourier Transform has wide applications in scientific computing and engineering. Although it has a continuous version, we will consider only the discrete version (DFT) and present what is commonly known as the Fast Fourier Transform (FFT) algorithm.
openaire +1 more source
Discrete Fourier Transformation
2015This chapter deals with the discrete Fourier transformation. Here, a periodic series in the time domain is mapped onto a periodic series in the frequency domain. Definitions of the discrete Fourier transformation and its inverse are given. Linearity, convolution, cross-correlation, and autocorrelation are treated as well as Parseval’s theorem.
openaire +1 more source