3 implementations of the FFT for Arduino AVR platforms!

A simple demo shows how to use the SIMD,Single Instruction Multiple Data, to optimize and accelerate the FFT algorithm.

FFT algorithm for fpga

FFT methods: Rader and Bluestein. Implemented in Python.

Spectrum Visualiser. This is a real-time audio visualization application that captures audio from the system's loopback device and displays it visual as a spectrum analyzer. More colors and renderers.

Fast Fourier Transform Implementation in C++

Chat using „enhanced“ end-to-end-enryption and modulation of audio signal in isolated device, ensuring privacy, anonymity and cybersecurity.

Generating function - Polynomials - Multiply polynomials - FFT/NTT

Fast Fourier transform (FFT) using the Cooley–Tukey algorithm for power-of-two sizes and Bluestein's algorithm for non-power-of-two sizes.

VectorFFT is a vectorized, pure C FFT library optimized for x86 processors (AVX-512, AVX2, SSE2) with zero external dependencies. It implements mixed-radix algorithms for common sizes and Bluestein's method for arbitrary lengths, with OpenMP multi-threading for large transforms. Designed for both digital signal processing and financial applications

Long fast Fourier transform and reverse fast transform. Constant memory consumption

weather, vibration and tilt angle data logger for telescopic bingo antenna

Implementations of most algorithms learnt in the course UE18CS311

Fourier transform algorithms collection.

This is the official repository of LabDeck's FFT(Fast Fourier Transform) examples. It includes both PDF and MDD files. Please note that while GitHub is unable to open and showcase MDD files, you can download and run them without any problems.

Digital Signal Processing Lab Code (MatLab). System and signal analysis and computation.

FFT, Inverse FFT implementation and comparaison of naive multiplication algorithm and FFT based one.

Extracts the dominant frequency sequence from an OGG audio file and exports it as a text file.

Mathematical module for python

This project implements a secure, touchless access control system using voice-based authentication on a Boolean FPGA (Spartan-6). It combines Python-generated audio and Verilog-based FPGA design to analyze and compare dominant audio frequencies, allowing access only when the voice patterns match.