This manuscript describes a number of algorithms that can be used to quickly evaluate a polynomial over a collection of points and interpolate these evaluations back into a polynomial. Engineers define the “Fast Fourier Transform” as a method of solving the interpolation problem where the coefficient ring used to construct the polynomials has a special multiplicative structure. Mathematicians define the “Fast Fourier Transform” as a method of solving the evaluation problem. One purpose of the document is to provide a mathematical treatment of the topic of the “Fast Fourier Transform” that can also be understood by someone who has an understanding of the topic from the engineering perspective.
The manuscript will also introduce several new algorithms that solve the fast multipoint evaluation problem over certain finite fields and require fewer finite field operations than existing techniques. The document will also demonstrate that these new algorithms can be used to multiply polynomials with finite field coefficients with fewer operations than Schonhage's algorithm in most circumstances.
A third objective of this document is to provide a mathematical perspective of several algorithms which can be used to multiply polynomials of size which is not a power of two. Several improvements to these algorithms will also be discussed.
Finally, the document will describe several applications of the “Fast Fourier Transform” algorithms presented and will introduce improvements in several of these applications. In addition to polynomial multiplication, the applications of polynomial division with remainder, the greatest common divisor, decoding of Reed-Solomon error-correcting codes, and the computation of the coefficients of a discrete Fourier Series will be addressed.

/pdf/fast-fourier-transform-algorithms-with-applications-2vinpci6f6.pdf

Fast fourier transform algorithms with applications

This paper presents a new approach to design multiplierless constant rotators. The approach is based on a combined coefficient selection and shift-and-add implementation (CCSSI) for the design of the rotators. First, complete freedom is given to the selection of the coefficients, i.e., no constraints to the coefficients are set in advance and all the alternatives are taken into account. Second, the shift-and-add implementation uses advanced single constant multiplication (SCM) and multiple constant multiplication (MCM) techniques that lead to low-complexity multiplierless implementations. Third, the design of the rotators is done by a joint optimization of the coefficient selection and shift-and-add implementation. As a result, the CCSSI provides an extended design space that offers a larger number of alternatives with respect to previous works. Furthermore, the design space is explored in a simple and efficient way. The proposed approach has wide applications in numerous hardware scenarios. This includes rotations by single or multiple angles, rotators in single or multiple branches, and different scaling of the outputs. Experimental results for various scenarios are provided. In all of them, the proposed approach achieves significant improvements with respect to state of the art.

/pdf/low-complexity-multiplierless-constant-rotators-based-on-1ht89aala7.pdf

Low-Complexity Multiplierless Constant Rotators Based on Combined Coefficient Selection and Shift-and-Add Implementation (CCSSI)

Mixed-scaling-rotation (MSR) coordinate rotation digital computer (CORDIC) is an attractive approach to synthesizing complex rotators. This paper presents the fixed-point error analysis and parameter selections of MSR-CORDIC with applications to the fast Fourier transform (FFT). First, the fixed-point mean squared error of the MSR-CORDIC is analyzed by considering both the angle approximation error and signal round-off error incurred in the finite precision arithmetic. The signal to quantization noise ratio (SQNR) of the output of the FFT synthesized using MSR-CORDIC is thereafter estimated. Based on these analyses, two different parameter selection algorithms of MSR-CORDIC are proposed for general and dedicated MSR-CORDIC structures. The proposed algorithms minimize the number of adders and word-length when the SQNR of the FFT output is constrained. Design examples show that the FFT designed by the proposed method exhibits a lower hardware complexity than existing methods.

Fixed-Point Analysis and Parameter Selections of MSR-CORDIC With Applications to FFT Designs

Multiplication by constants can be efficiently realized using shifts, additions, and subtractions. In this work we consider how to select a fixed-point value for a real valued, rational, or floating-point coefficient to obtain a low-complexity realization. It is shown that the process, denoted addition aware quantization, often can determine coefficients that has as low complexity as the rounded value, but with a smaller approximation error by searching among coefficients with a longer wordlength.

/pdf/addition-aware-quantization-for-low-complexity-and-high-4ugg6uyzls.pdf

Addition Aware Quantization for Low Complexity and High Precision Constant Multiplication

This brief presents a novel approach for improving the accuracy of rotations implemented by complex multipliers, based on scaling the complex coefficients that define these rotations. A method for obtaining the optimum coefficients that lead to the lowest error is proposed. This approach can be used to get more accurate rotations without increasing the coefficient word length and to reduce the word length without increasing the rotation error. This brief analyzes two different situations where the optimization method can be applied: rotations that can be optimized independently and sets of rotations that require the same scaling. These cases appear in important signal processing algorithms such as the discrete cosine transform and the fast Fourier transform (FFT). Experimental results show that the use of scaling for the coefficients clearly improves the accuracy of the algorithms. For instance, improvements of about 8 dB in the Frobenius norm of the FFT are achieved with respect to using non-scaled coefficients.

/pdf/accurate-rotations-based-on-coefficient-scaling-15xjce3axh.pdf

Accurate Rotations Based on Coefficient Scaling

This letter proposes a new multiplierless approximation of the discrete Fourier transform (DFT) called the multiplierless fast Fourier transform-like (ML-FFT) transformation. It makes use of a novel factorization to parameterize the twiddle factors in the conventional radix-2/sup n/ or split-radix FFT algorithms as certain rotation-like matrices and approximates the associated parameters using the sum-of-powers-of-two (SOPOT) or canonical signed digits (CSD) representations. The ML-FFT converges to the DFT when the number of SOPOT terms used increases and has an arithmetic complexity of O(N log/sub 2/ N) additions, where N = 2/sup m/ is the transform length. Design results show that the NM-FFT offers flexible tradeoff between arithmetic complexity and numerical accuracy in approximating the DFT.

/pdf/an-efficient-multiplierless-approximation-of-the-fast-1qjlkur6id.pdf

P.M. Yiu

Papers

An efficient multiplierless approximation of the fast Fourier transform using sum-of-powers-of-two (SOPOT) coefficients