Radix-two fast Fourier transform
For N a power of two, split polynomial coefficients into even and odd indices, recursively transform each half, and combine values using p(z)=p_even(z²)+zp_odd(z²).
Key knowledge
For N a power of two, split polynomial coefficients into even and odd indices, recursively transform each half, and combine values using p(z)=p_even(z²)+zp_odd(z²). The recurrence T(N)=2T(N/2)+Θ(N) gives Θ(N log N) complex arithmetic operations. Transforming, multiplying values and inverting multiplies polynomials after padding beyond the product degree.
Conditions and scope
- The bound counts complex arithmetic operations; bit precision and rounding error need separate analysis.
- Padding avoids wraparound of the polynomial product.
Sources · 1
References
Sources retain their recorded scope. A source link alone does not establish verification of every statement.
Evidence and review
Lecture 5 FFT and inverse algorithms, recurrence and FFT-MULTIPLY in sections 5.1.1–5.1.2; stale integer-multiplication footnote excluded.
2026-10-10 · Independent AI editorial review: All241 compact claims, hypotheses, displayed equations/conventions and all596 origin semantic links read; entire241-entry author exact-source inspection matrix and declared limitations reviewed. Prior105 actual inherited Mathematics/Information records read for whole-inventory breadth. Targeted independent primary sections are listed below; this does NOT claim every cited source body or every proof was independently re-read. This is AI reference-content review, not human disciplinary certification, exhaustive textbook reproduction or experimental replication. Receipt: mathematics-information-independent-content-review.1.
Entry details
Permanent link to this entry ↗- Record identity
- info-fast-fourier-transform
- Revision
- university-core.1
- Structured reference record
- University core expansion