Four Ways to Compute an Inverse FFT Using the Forward FFT Algorithm
If you need to compute inverse fast Fourier transforms (inverse FFTs) but you only have forward FFT software (or forward FFT FPGA cores) available to you, below are four ways to solve your problem. Preliminaries To define what we're...
Summary
This blog explains four practical methods to compute an inverse FFT (IFFT) when only forward FFT software or hardware cores are available. Readers will learn how to transform inputs, reorder data, and adjust scaling/sign conventions so a forward-only FFT can produce correct IFFT results in software and FPGA/embedded environments.
Key Takeaways
- Apply complex conjugation to inputs and outputs to convert a forward FFT into an inverse FFT.
- Use input/output reordering (bit-reversal and index permutation) to emulate IFFT indexing with a forward-only core.
- Adjust scaling and sign/normalization conventions to achieve correct amplitude and phase for the IFFT.
- Implement pre- and post-processing steps for FPGA/embedded FFT cores to reuse forward-only hardware for IFFT tasks.
Who Should Read This
DSP engineers, FPGA/embedded developers, and systems designers who implement FFT/IFFT in software or hardware and need practical techniques to compute IFFT using forward-only FFT routines or cores.
TimelessAdvanced
Related Documents
- A New Approach to Linear Filtering and Prediction Problems TimelessAdvanced
- A Quadrature Signals Tutorial: Complex, But Not Complicated TimelessIntermediate
- An Introduction To Compressive Sampling TimelessIntermediate
- Lecture Notes on Elliptic Filter Design TimelessAdvanced
- Computing FFT Twiddle Factors TimelessAdvanced
