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Mathematics · unit version 1

Finite Fourier bases, convolution and FFT

Prove finite transform identities, diagonalize circular filters and derive a bounded radix-two implementation with explicit normalization and arithmetic costs.

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Readiness and preparation

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What does multiplication by exp(iθ) do to a complex number?

Fourier coefficients combine rotations and magnitudes; the sign of the angle determines the convention.

Compare reasoning and find a refresher

It rotates by θ without changing magnitude. Conjugation reverses the angle; at θ=−π/2 the multiplier is −i.

Review complex polar form and rotations

Why does an orthogonal basis allow coefficients to be recovered by inner products?

Fourier inversion depends on orthogonality and the norm of each basis vector, not merely on having distinct vectors.

Compare reasoning and find a refresher

Taking the inner product with one basis vector kills the other terms. Divide by its squared norm to recover that coefficient; normalized vectors have squared norm one.

Review complex inner products and normalization

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Transform conventions, singular filters and padding

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Lesson sequence

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  1. Build a finite Fourier basis from roots of unity

    Lesson details and objectives

    Derive the finite inverse transform, energy identity and real-input symmetry from exact geometric sums.

    • Prove root-of-unity orthogonality and the inverse of the stated finite Fourier transform.
    • Interpret unitary normalization and Parseval as a finite-dimensional basis change.
    • Use and prove conjugate symmetry with the correct zero and even-length boundary modes.

    6 practice tasks.

  2. Circular convolution, modes and wraparound

    Lesson details and objectives

    Track cyclic indices through the Fourier transform, identify circulant eigenmodes and determine when padding turns a circular computation into an ordinary convolution.

    • Prove the circular convolution theorem and circulant diagonalization with the specified Fourier signs and normalization.
    • Classify invertibility, attainable outputs and kernel modes by transformed filter values.
    • Derive delay phases and polynomial wraparound, then justify a sufficient zero-padding length for linear convolution.

    6 practice tasks.

  3. Derive a radix-two FFT and count its work

    Lesson details and objectives

    Split a negative-exponent Fourier transform into even and odd subsequences, prove the recursive index contract, and audit exact work and numerical checks.

    • Prove the even/odd butterfly identities and the recursive natural-order output contract for powers of two.
    • Derive exact complex-arithmetic operation counts under a stated treatment of trivial twiddles.
    • Construct the inverse through conjugation and distinguish exact identities from floating-point comparison evidence.

    6 practice tasks.