Μετάφραση και ανάλυση λέξεων από την τεχνητή νοημοσύνη ChatGPT
Σε αυτήν τη σελίδα μπορείτε να λάβετε μια λεπτομερή ανάλυση μιας λέξης ή μιας φράσης, η οποία δημιουργήθηκε χρησιμοποιώντας το ChatGPT, την καλύτερη τεχνολογία τεχνητής νοημοσύνης μέχρι σήμερα:
- πώς χρησιμοποιείται η λέξη
- συχνότητα χρήσης
- χρησιμοποιείται πιο συχνά στον προφορικό ή γραπτό λόγο
- επιλογές μετάφρασης λέξεων
- παραδείγματα χρήσης (πολλές φράσεις με μετάφραση)
- ετυμολογία
Τι (ποιος) είναι Fourier transforms - ορισμός
![chord]]. The first three peaks on the left correspond to the frequencies of the [[fundamental frequency]] of the chord (C, E, G). The remaining smaller peaks are higher-frequency [[overtone]]s of the fundamental pitches. A [[pitch detection algorithm]] could use the relative intensity of these peaks to infer which notes the pianist pressed.](https://commons.wikimedia.org/wiki/Special:FilePath/CQT-piano-chord.png?width=200 "chord]]. The first three peaks on the left correspond to the frequencies of the [[fundamental frequency]] of the chord (C, E, G). The remaining smaller peaks are higher-frequency [[overtone]]s of the fundamental pitches. A [[pitch detection algorithm]] could use the relative intensity of these peaks to infer which notes the pianist pressed.")
![Animation showing the Fourier Transform of a time shifted signal. [Top] the original signal (yellow), is continuously time shifted (blue). [Bottom] The resultant Fourier Transform of the time shifted signal. Note how the higher frequency components revolve in complex plane faster than the lower frequency components.](https://commons.wikimedia.org/wiki/Special:FilePath/Fourier transform - time shifted signal.gif?width=200 "Animation showing the Fourier Transform of a time shifted signal. [Top] the original signal (yellow), is continuously time shifted (blue). [Bottom] The resultant Fourier Transform of the time shifted signal. Note how the higher frequency components revolve in complex plane faster than the lower frequency components.")
![The [[rectangular function]] is [[Lebesgue integrable]].](https://commons.wikimedia.org/wiki/Special:FilePath/Rectangular function.svg?width=200 "The [[rectangular function]] is [[Lebesgue integrable]].")
![The [[sinc function]], which is the Fourier transform of the rectangular function, is bounded and continuous, but not Lebesgue integrable.](https://commons.wikimedia.org/wiki/Special:FilePath/Sinc function (normalized).svg?width=200 "The [[sinc function]], which is the Fourier transform of the rectangular function, is bounded and continuous, but not Lebesgue integrable.")
Βικιπαίδεια
In physics and mathematics, the Fourier transform (FT) is a transform that converts a function into a form that describes the frequencies present in the original function. The output of the transform is a complex-valued function of frequency. The term Fourier transform refers to both this complex-valued function and the mathematical operation. When a distinction needs to be made the Fourier transform is sometimes called the frequency domain representation of the original function. The Fourier transform is analogous to decomposing the sound of a musical chord into terms of the intensity of its constituent pitches.
Functions that are localized in the time domain have Fourier transforms that are spread out across the frequency domain and vice versa, a phenomenon known as the uncertainty principle. The critical case for this principle is the Gaussian function, of substantial importance in probability theory and statistics as well as in the study of physical phenomena exhibiting normal distribution (e.g., diffusion). The Fourier transform of a Gaussian function is another Gaussian function. Joseph Fourier introduced the transform in his study of heat transfer, where Gaussian functions appear as solutions of the heat equation.
The Fourier transform can be formally defined as an improper Riemann integral, making it an integral transform, although this definition is not suitable for many applications requiring a more sophisticated integration theory. For example, many relatively simple applications use the Dirac delta function, which can be treated formally as if it were a function, but the justification requires a mathematically more sophisticated viewpoint.
The Fourier transform can also be generalized to functions of several variables on Euclidean space, sending a function of 3-dimensional 'position space' to a function of 3-dimensional momentum (or a function of space and time to a function of 4-momentum). This idea makes the spatial Fourier transform very natural in the study of waves, as well as in quantum mechanics, where it is important to be able to represent wave solutions as functions of either position or momentum and sometimes both. In general, functions to which Fourier methods are applicable are complex-valued, and possibly vector-valued. Still further generalization is possible to functions on groups, which, besides the original Fourier transform on Ror Rn (viewed as groups under addition), notably includes the discrete-time Fourier transform (DTFT, group = Z), the discrete Fourier transform (DFT, group = Z mod N) and the Fourier series or circular Fourier transform (group = S1, the unit circle ≈ closed finite interval with endpoints identified). The latter is routinely employed to handle periodic functions. The fast Fourier transform (FFT) is an algorithm for computing the DFT.
