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2020 22th International Conference on Digital Signal Processing and its Applications (DSPA), 2020
The issues of using digital methods of discrete Fourier transform of polyharmonic signals for their deductive processing by elementary devices of nanoelectronics or programmable logic devices are considered.
A. Burova
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The issues of using digital methods of discrete Fourier transform of polyharmonic signals for their deductive processing by elementary devices of nanoelectronics or programmable logic devices are considered.
A. Burova
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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
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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.
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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 ...
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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 ...
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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,
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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,
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Evolution of Forward and Inverse Discrete Fourier Transform
East-West Design & Test Symposium, 2018The problems of the evolution of the forward and inverse discrete Fourier transform are investigated. Forward and inverse discrete Fourier transform is the basis of the classical discrete spectral analysis of signals.
O. Ponomareva +2 more
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Parameter-Efficient Fine-Tuning with Discrete Fourier Transform
International Conference on Machine LearningLow-rank adaptation~(LoRA) has recently gained much interest in fine-tuning foundation models. It effectively reduces the number of trainable parameters by incorporating low-rank matrices $A$ and $B$ to represent the weight change, i.e., $\Delta W=BA ...
Ziqi Gao +6 more
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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
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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.
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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.
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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.
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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