SYSTEMA CONSTRUCTUM

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discrete-fourier-transform

The discrete Fourier transform (DFT) is a mathematical algorithm that converts a finite sequence of N time-domain samples into a finite sequence of N frequency-domain complex coefficients. It computes X[k] = sum_{n=0}^{N-1} x[n] * exp(-2*p…

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Definition

The discrete Fourier transform (DFT) is a mathematical algorithm that converts a finite sequence of N time-domain samples into a finite sequence of N frequency-domain complex coefficients. It computes X[k] = sum_{n=0}^{N-1} x[n] * exp(-2*pi*i*k*n/N) for k = 0,...,N-1, thereby decomposing a discrete signal into its constituent frequencies. The DFT is the foundational transform of digital signal processing, enabling spectral analysis, filtering, and convolution in the digital domain. [formal: DFT | substrate: mind | horizon: a moment | explicit: yes | epoch: 1.00]

Why it is in scope

The human-made mathematical transform that converts a finite sequence of equally-spaced samples of a function into a same-length sequence of equally-spaced values representing frequency components. Built through the discrete sampling theorem and computational algorithms, designed to bridge continuous and digital signal processing.

Names and aliases

Relations from this entry

  • cmspdibrl04whjlssto99iiufDERIVED_FROM →

    The discrete Fourier transform was derived from the continuous Fourier transform by extending it to discrete sequences. FT existed first as a mathematical tool (1822); DFT was derived from it as the discrete analog. Which came first test: FT predates DFT and fed into DFT's formulation.

  • cmsps9i0v06eejlssqrjcqyviINSTANCE_OF →

    The discrete Fourier transform is a specific signal processing technique for converting time-domain signals to frequency-domain representation. A competent speaker calls DFT a type of signal processing operation. Per Law 9: specific→general INSTANCE_OF. Nearest kind is signal-processing.

  • cmsq4obya07m0jlssh92wv3v0DERIVED_FROM →

    DFT is a specific computational method for producing a spectral representation. Which came first? The general concept of representing signals in the frequency domain (spectral representation) predates the specific algorithm (DFT). spectral-representation=0.03, DFT=0.06 → spectral-representation is older and more general.

Relations to this entry

  • cmspjfefp05lxjlssg1w6gyuv← DERIVED_FROM

    The cepstrum computation fundamentally requires the discrete Fourier transform: cepstrum = IDFT(log(|DFT(x)|²)). Remove DFT and the cepstrum cannot be computed. The DFT concept predates cepstrum (1820s vs 1963).

  • cmsptfl8u06jijlssjffttxhd← DERIVED_FROM

    The cepstrum-coefficient is computed via the inverse DFT of the log-power spectrum: c[n] = IDFT(log(|X[k]|²)). The DFT concept (1820s) predates cepstral coefficients (1963, Bogert). Which-came-first test passes: DFT existed first and fed into cepstrum-coefficient.

  • fast-fourier-transform← DEPENDS_ON

    FFT is an algorithm whose entire operational purpose is to compute the discrete Fourier transform efficiently. Remove DFT and FFT has no mechanism or purpose — present-tense removal test (Law 8) passes. DFT (epoch 0.06) predates FFT (0.83).

  • cmspqokmf0684jlss24yd0c6f← DEPENDS_ON

    Cepstral analysis computes the cepstrum via FFT (DFT) of the log power spectrum. Remove DFT and the cepstrum computation stops working entirely. Removal test passes: cepstral analysis needs DFT as its computational engine.

  • cmsp6zgox04bkjlssq1q4peaf← DEPENDS_ON

    Windowing is applied before DFT to reduce spectral leakage from finite signal truncation. Remove DFT and windowing as a DSP technique has no target — you always window a DFT. Direction: windowing depends on discrete-fourier-transform.

  • cmsp757bx04cojlssckoi3vr7← DEPENDS_ON

    Spectral leakage is a direct consequence of the DFT's finite-length sampling of signals. Remove the discrete Fourier transform and spectral leakage ceases to exist — it is an artifact intrinsic to the DFT's mathematical structure. Epochs confirm DFT (0.06) predates spectral-leakage (0.31).

Record identity

Created
Aug 12, 2026, 7:49 AM UTC
Content hash
b6cdc637c9ff3c06e64b36378a8caf54b5e201174a073c7b5f897540844ff55a

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