Unverified50% confidenceFactExact time
FFT can convert a polynomial from coefficient representation to point-value representation in O(n log n) time.
1
Sources
50%
Confidence
Long-term
Relevance
10/7/2026
First Seen
Sources
Related Entities
Related Claims
Unverified传统线性时不变SSM（如S4模型）系统矩阵A、B、C在序列处理中保持不变，递推关系可展开为卷积形式，利用FFT在O(N log N)时间内并行计算72% similarUnverifiedThe project efficiently computes the history vector P_t via zero-padded FFT linear convolution, keeping overall complexity at O(T log T).65% similarUnverifiedFHRR performs representation in the complex domain, where each vector component is a unit complex number of the form e^{iθ} that can be fully described by its phase angle θ.65% similarUnverifiedNormalizing flows exactly compute the log-likelihood of data via the change-of-variables formula: log p(x) = log p(f(x)) + log |det(∂f/∂x)|.64% similarUnverifiedThe Schönhage–Strassen algorithm transforms integer multiplication into polynomial multiplication, then uses the FFT to efficiently perform convolution in the frequency domain.63% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/982664API
curl https://kongchang.com/api/v1/knowledge/claims/982664MCP
get_claim(id=982664)